NeurIPS 2026
NeurIPS 2026 is the fortieth annual Conference on Neural Information Processing Systems, with the primary dates listed for Sydney, Australia, and additional satellite locations in Atlanta and Paris.
Reading notes, references, and events
Each item includes a short note so readers can understand why it matters before opening the original source material.
Upcoming
Future events are now tracked in the library
3 upcoming events are currently published. Use the calendar view for a schedule-first view.
GAISS 2026: IEEE GenAI for Secure Systems
GAISS 2026 is an IEEE conference at the University of Texas at Austin focused on generative AI for secure systems, including red teaming, blue-team automation, governance, and agentic secure AI.
IAPP P.S.R. + AI Governance Global 2026
IAPP Privacy. Security. Risk. + AI Governance Global 2026 brings privacy, cybersecurity law, technology, and AI governance professionals together in Seattle.
OpenAI DevDay 2026
OpenAI DevDay 2026 is scheduled for September 29 in San Francisco and is OpenAI’s primary developer event for platform updates.
AGNTCon + MCPCon Europe 2026
AGNTCon + MCPCon Europe 2026 brings agent and MCP builders to Amsterdam to cover agent architectures, protocols, infrastructure, security, observability, and interoperability.
DEF CON 34 / AI Village 2026
DEF CON 34 takes place in Las Vegas and is expected to include AI security activity through villages, workshops, contests, and community-led research tracks as schedules firm up.
Black Hat USA 2026 AI Summit
Black Hat USA 2026 includes an AI Summit and security briefings in Las Vegas focused on how artificial intelligence is changing digital defense.
ICML 2026
ICML 2026 takes place at COEX in Seoul, South Korea, with tutorials, main conference sessions, and workshops covering core machine learning research.
AI Engineer World's Fair - JUNE 29 - JULY 2, 2026 • SAN FRANCISCO, CA
AI Engineer runs the most viewed technical conferences in AI for engineers, with over 10M+ views of our talks online. We are back in SF for the 4th year in a row! This is the one place you can meet with every major frontier lab, leading AI clouds, and AI native/transformed companies — from disruptive AI startups to Fortune 500 AI leaders, and every notable building block in the LLM OS ecosystem.
Data + AI Summit 2026
Data + AI Summit 2026 is Databricks’ global data and AI conference in San Francisco and online, with 800+ sessions across data engineering, analytics, ML, governance, and agent applications.
The AI Summit London 2026
The AI Summit London 2026 is a commercial AI conference at Tobacco Dock focused on enterprise AI strategy, adoption, and responsible scale.
Gartner Security & Risk Management Summit 2026
Gartner Security & Risk Management Summit 2026 brings CISOs and security leaders together in National Harbor, Maryland, with tracks covering AI, cyber risk, application security, data security, operations, privacy, and governance.
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How I deleted 95% of my agent skills and got better results — Nick Nisi, WorkOS
Claude would fake running tests by touching the expected output file. Nick Ni, DX engineer at WorkOS, fixed it by SHA-256 hashing the actual test output and verifying it cryptographically. His principle: make it easier to do the real work than to lie about it, and enforce that through code and state machines, not promp
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How We Built Zeta2: Training an Edit Prediction Model in Production — Ben Kunkle, Zed
To validate settled data, Zed ran 10 frontier model predictions per example and measured Levenshtein distance to the final state. For 100,000 training examples that is a million frontier model requests, which is prohibitively expensive. The fix: Zeta 2's student model now approaches teacher quality, so they run it 50 t
Malicious npm packages abuse dependency confusion to profile developer environments
A dependency confusion campaign leveraged 33 malicious npm packages to collect reconnaissance data from developer and build environments. This report details the attack chain, observed tradecraft, and detection opportunities to help organizations identify and disrupt related activity. The post Malicious npm packages ab
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Why (Senior) Engineers Struggle to Build AI Agents — Philipp Schmid, Google DeepMind
A `deleteItem` endpoint is obvious to the developer who built it. An agent only sees the function schema and docstring. Philipp Schmid from Google DeepMind argues this is why senior engineers struggle most: they carry years of implicit context that agents do not, and design tools assuming it. He names four other shifts
How Braintrust turns customer requests into code with Codex
How Braintrust engineers use Codex with GPT-5.5 to run experiments and code faster.
A shared playbook for trustworthy third party evaluations
OpenAI shares guidance on third-party AI evaluations, covering how to assess model capabilities, safeguards, and validity for frontier systems.
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Reachy Mini: the $300 open source robot you can actually hack — Andres Marafioti, Hugging Face
Qwen3-TTS shipped at 0.8x real time: one second of audio took 1.2 seconds to generate. Andres Marafioti from Hugging Face spent two weeks fixing it. The culprits were no streaming, 500 autoregressive steps per audio packet with a CPU GPU round trip on each, and a dynamic KV cache that blocked compilation. Static KV cac
Boston Children’s uses AI to unlock new diagnoses
Boston Children’s Hospital uses OpenAI technology to improve patient care, reduce operational burden, and help diagnose more than 40 rare disease cases.
Strengthening societal resilience with Rosalind Biodefense
OpenAI launches Rosalind Biodefense, expanding trusted access to GPT-Rosalind for vetted developers and U.S. government partners advancing biodefense, public health, and pandemic preparedness through frontier AI.
Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection
Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection. The post Microsoft is named a Leader in the 2026 Gartner® Magic Quadrant™ for Endpoint Protection appeared first on Microsoft Security Blog .
Typosquatted npm packages used to steal cloud and CI/CD secrets
The Mini Shai-Hulud campaign used malicious npm packages to target cloud and CI/CD credentials across developer environments. This report details the attack chain, detection opportunities, and mitigation guidance to help organizations identify and disrupt related activity. The post Typosquatted npm packages used to ste
Cloud CISO Perspectives: How to build an AI-ready security program for the public sector
From industrial control systems to decades-old municipal databases, here’s our CISO guidance to prep AI-ready security programs for the public sector.
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New Claude Opus 4.8: 15 Things You May’ve Missed
The ‘best’ generally available AI model just dropped, but there is plenty I bet you missed about what it is, how it performs, and what the release tells us. 15 highlights from the 244 page system card, plus private testing, leader interview and more. AI Insiders ($9!): https://www.patreon.com/AIExplained Chapters: 00:0
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Why your agents need decision traces, not just documents — Zach Blumenfeld, Neo4j
A knowledge base tells a financial analyst agent the risk factors. A context graph tells it whether to reject or accept, because it also carries past decision traces, the reasoning behind them, and how similar cases resolved. Zach from Neo4j walks through how context graphs extend a standard RAG setup with three layers
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Reverse engineering a Viking VOIP phone protocol with Claude Code — Boris Starkov, Eleven Labs
A Viking VoIP phone sat in the ElevenLabs San Francisco office for a year. Three senior engineers and ChatGPT could not get it working. Boris from ElevenLabs cracked the undocumented protocol with Claude Code in a couple of days: brute forced all 676 possible two letter command combinations, found 80 valid ones, then s
How Endava builds an agentic organization with Codex
Learn how Endava uses Codex to build an agentic organization, accelerating software delivery and reducing requirements analysis from weeks to hours.
MUFG aims to become AI-native with OpenAI
MUFG uses ChatGPT Enterprise to build an AI-native organization, improve workflows, and deliver new AI-powered financial services at scale.
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How agent o11y differs from traditional o11y — Phil Hetzel, Braintrust
Traditional observability answers one question: is the system up? Phil Hetzel from Braintrust argues that question is not the right one for agents. An individual agent trace can exceed a gigabyte. A single span can hit 20 megabytes. The data is semistructured, packed with unstructured text, and still arrives in real ti
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Most Enterprise Agentic Projects Are Doomed, Here's Why — Jess Grogan-Avignon & Jack Wang, Accenture
Jess Grogan-Avignon and Jack Wang at Accenture built an agentic application in two weeks. Getting it to production took another 12 months. Not because the code was wrong. Because the infrastructure team, the security team, the AI gateway team, the data governance team, and the application team all had to align before a
OpenAI’s Frontier Governance Framework
Explore OpenAI’s Frontier Governance Framework and how our AI safety, security, and risk practices align with emerging EU and California regulations.
The Gentlemen ransomware: Dissecting a self-propagating Go encryptor
Microsoft Threat Intelligence presents a comprehensive analysis of The Gentlemen, a Go-based ransomware deployed by affiliates of Storm-2697 that combines per-file ephemeral key encryption with an aggressive self-propagation module to deploy itself across an entire network using series of simultaneous lateral movement
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Context Graphs for Explainable, Decision-Aware AI Agents — Andreas Kollegger & Zaid Zaim, Neo4j
Prescribing drug X is correct 99% of the time for symptom Y. For the 1% where it is fatal, statistical reasoning does not help you. Andreas Kollegger calls this reference class validation: before the agent acts, it has to know which group it is in. Context graphs give agents the why. Not just knowledge and tools but th
Artificial Intelligence (AI) for Manufacturing Workshop
U.S. manufacturing expects to gain transformative productivity and resilience improvements through AI integration in product development and production processes. Despite AI's potential to transform manufacturing operations and workflows, significant
Cisco and OpenAI redefine enterprise engineering with Codex
Cisco and OpenAI are redefining enterprise engineering with Codex, helping Cisco scale AI-native development, accelerate AI Defense work, and automate defect remediation.
Election information and safeguards in 2026
Ahead of global elections, we’re helping people access information, supporting cyber defenders, and increasing AI transparency
Warp’s big bet on building open source with GPT-5.5
Warp uses GPT-5.5 and OpenAI models to coordinate coding agents across local, cloud, and open-source development workflows.
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Comprehend First, Code Later: The AI Skill I Rely On Daily — Priscila Andre de Oliveira, Sentry
Priscila Andre de Oliveira analyzed 116 of her own Claude sessions from daily work at Sentry. 67% were comprehension. 2% were code generation. Working in a codebase with 15 years of history, around 100 PRs merged per day, and 100,000 organizations depending on it, the unlock is not generation but understanding. She bui
Building self-improving tax agents with Codex
See how OpenAI, Thrive, and Crete built a self-improving tax agent with Codex, automating filings, improving accuracy, and accelerating workflows.
Introducing Google AI Threat Defense to help you outpace the adversary
AI Threat Defense is a comprehensive AI-powered cybersecurity solution, an always-on security platform to outpace AI-driven attacks.
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Why Rust is the Ideal Language for Vibe-Coding — Daniel Szoke, Sentry
TypeScript is easy for models to write because it imposes few constraints. Those same missing constraints let models introduce data races that compile, run, and only fail intermittently. A thread safety bug in Rust does not compile. The compiler names the unsound type, explains why it cannot be sent between threads, an
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The maturity phases of running evals — Phil Hetzel, Braintrust
Most teams approach evals like unit tests and try to cover every possible failure. Phil Hetzel from Braintrust argues that is the wrong frame: enumerate your known failure modes, cover those specifically, and ship. The goal is a flywheel where production traces surface what is going wrong, feed back into offline experi
ACM CAIS 2026
ACM CAIS 2026 is a research-focused conference on compound AI architectures, optimization, deployment, and agentic AI systems in San Jose, California.
From poisoned search results to GPU mining: A cryptojacking campaign abusing ScreenConnect and Microsoft .NET utilities
Microsoft exposes a cryptojacking campaign using SEO poisoning and ScreenConnect to target high-performance PCs, with malicious sites also surfaced through AI chatbots. The post From poisoned search results to GPU mining: A cryptojacking campaign abusing ScreenConnect and Microsoft .NET utilities appeared first on Micr
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Run Frontier AI at Home — Alex Cheema, EXO Labs
Running GLM 5.1, a trillion parameter model released the day before this workshop, across four Mac Studios costs around $40,000 in hardware and tops out at roughly 20 tokens per second. Alex Cheema from EXO Labs thinks both numbers have about 100x left in them. The workshop covers what that 100x looks like across the s
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What the Best Agents Share — Mardu Swanepoel, Flinn AI
Harvey, Cursor, Manus, and Claude operate in completely different domains but share four patterns: focus modes that constrain the action space to improve output quality, transparent execution that surfaces tool calls and reasoning to build user trust, personalization that optimizes for speed to understanding rather tha
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Stop babysitting your agents... — Brandon Walsenuk, Unblocked
Same prompt. Same agent. Same model. Without a context engine: 2.5 hours, 20.9 million tokens, multiple rounds of human correction, and code that compiled but would have broken the entire system if it shipped. With one: 25 minutes, 10.8 million tokens, and a senior engineer who gave one nitpick and approved the merge.
OpenAI, Grupo Folha and Grupo UOL announce strategic content partnership
OpenAI partners with Grupo Folha and Grupo UOL to bring trusted Brazilian journalism to ChatGPT, expanding access to news with attribution and transparency.
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Agentic Evaluations at Scale, For Everybody — Nicholas Kang & Michael Aaron, Google DeepMind
On SWE-Bench Pro, six frontier models land within a couple of percentage points of each other. The harness they run inside shifts performance by 22%. A competing lab once took a Kaggle benchmark, reran it with their own compaction settings, and published much better results. Neither number was wrong. Both were useless.
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Does GenAI "belong" to data scientists? — Phil Hetzel, Braintrust
At most traditional enterprises, GenAI got handed to the ML platform team because it had AI in the name. Phil Hetzel from Braintrust argues that was the wrong move, not because data scientists lack value, but because Anthropic and OpenAI already ran the data pipeline. What is left is prompt and context engineering, dis
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Bounded Autonomy: Between Free Will and Determinism — Angus J. McLean, Oliver
Angus McLean spent time building a complex agent application to generate his CV. Four letters beat it: HTML. He puts the improvement at 100x. The talk is from Oliver's AI Director, where agents generate around 4,000 creative assets a day for 200 plus brands, assets you have probably seen and had no idea were AI. The co
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How Google DeepMind Runs Agents at Scale — KP Sawhney & Ian Ballantyne, Google DeepMind
Google DeepMind employees have worse token quotas than paying customers. That is not a mistake. KP Sawhney explains: customers get priority, and if an internal team spikes usage on a cluster someone monitoring 24/7 will just call and ask them to stop. This panel covers how DeepMind thinks about agents at scale from the
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Scaling the Next Paradigm of Heterogeneous Intelligence — Adrian Bertagnoli, Callosum
A mixture of Qwen 3 VL8B and Kimi K2.5 beat the state of the art on Video Web Arena, outperforming the leading GPT and Gemini models by 18 and 25 percent while costing 3.7 times less and running 3 times faster. The reason it worked is that visual web navigation decomposes into subtasks that do not all need a frontier m
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Your Agent Is an Infinite Canvas — RL Nabors, Dressed for Space
RL Nabors built a comic reader that renders inside Claude. Full panels, navigation, transcript mode, design matched to the original site. No browser tabs. She is reading her own web comic archive entirely through an agent, and it looks like the website. The talk is a case against chat as the permanent UI of agentic sof
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The Missing Primitive for Agent Swarms — Lou Bichard, Ona
Stripe called theirs Minions. RAMP called theirs Inspect. Both are internal infrastructure for running fleets of background agents, and both teams built it from scratch. Lou Bichard's argument is that this shouldn't keep happening. The talk breaks down what agent swarm infrastructure actually needs: a runtime (largely
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Prompt to Pipeline: Building with Google's Gen Media Stack — Paige & Guillaume, Google DeepMind
A public domain book, a notebook, and three gen media models. Guom from Google DeepMind fed Wind in the Willows into Gemini, generated character portraits with Nano Banana, animated chapter scenes with VO, and scored each chapter with LIA, all live in the workshop. The full three hour session covers more ground. Paige
Project Glasswing: An initial update
Anthropic reports early Project Glasswing results using Mythos Preview with infrastructure partners and external testers, including large-scale vulnerability discovery and a cautious disclosure posture.
How Virgin Atlantic ships faster with Codex
How Virgin Atlantic used Codex to ship its revamped mobile app on a fixed holiday travel deadline, reaching near-total unit test coverage and zero P1 defects.
Microsoft recognized as a Leader in The Forrester Wave™ for Workforce Identity Security Platforms
Microsoft has been recognized as a Leader in The Forrester Wave™: Workforce Identity Security Platforms, Q2 2026, receiving the highest scores in both the current offering and strategy categories. The post Microsoft recognized as a Leader in The Forrester Wave™ for Workforce Identity Security Platforms appeared first o
From edge appliance to enterprise compromise: Multi-stage Linux intrusion via F5 and Confluence
A multi-stage attack on Linux devices began with an exposed F5 BIG-IP edge appliance and pivoted to an internal Confluence server for credential theft and identity compromise. Learn how the threat actor attempted Kerberos relay and lateral movement, and how Microsoft Defender detected, blocked, and unraveled the attack
Microsoft Security success stories: How St. Luke’s and ManpowerGroup are securing AI foundations
How Frontier firms secure AI at scale: read how Microsoft customers embed governance, identity, and cloud security to make protection an enabler of AI growth. The post Microsoft Security success stories: How St. Luke’s and ManpowerGroup are securing AI foundations appeared first on Microsoft Security Blog .
Measuring LLMs' Ability to Develop Exploits
Anthropic evaluates Mythos Preview against ExploitBench, ExploitGym, and an updated smart-contract exploitation benchmark, showing a step change in models that can turn vulnerabilities into working exploit chains.
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Fast Models Need Slow Developers — Sarah Chieng, Cerebras
Codex Spark, a model Cerebras built with OpenAI, generates code at 1,200 tokens per second. The Sonnet and Opus families run at 40 to 60. At that 20x difference, a context window that used to take ten minutes to fill now takes 30 seconds, and every habit built around slow generation starts producing technical debt at a
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Lobster Trap: OpenClaw in Containers from Local to K8s and Back — Sally Ann O'Malley, Red Hat
Sharing a good agent setup usually means handing someone a pile of markdown, config files, and YAML and hoping they reproduce what you have. The answer in this demo is a container image: spin up a sub agent in two seconds from a Podman command, flip a flag for Kubernetes, and your personal setup becomes the team baseli
OpenAI named a Leader in enterprise coding agents by Gartner
OpenAI is named a leader in the 2026 Gartner Magic Quadrant for Enterprise AI Coding Agents, with Codex recognized for innovation and enterprise-scale deployment.
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AI on Android: Ask me Anything — Florina Muntenescu & Oli Gaymond, Google DeepMind
Gemini Nano on device weighs three to four gigabytes. Shipping that per app is not realistic, which is why AI core puts it in the system once and every app shares it. Foreground apps get top priority. Background batch jobs queue and run overnight on charge. The developer never manages any of that. The tradeoff is reach
ChatGPT Enterprise & Edu Codex release notes: May 2026
OpenAI’s Enterprise and Edu release notes describe Codex updates including goal mode, browser improvements, locked computer use, app-window context, admin analytics, and plugin sharing status.
AdventHealth advances whole-person care with OpenAI
AdventHealth is using ChatGPT for Healthcare to streamline workflows, reduce administrative burden, and return more time to patient care.
What’s new in Microsoft Security: May 2026
Microsoft Security’s latest updates extend visibility, control, and protection across expanding ecosystems as organizations accelerate AI adoption. The post What’s new in Microsoft Security: May 2026 appeared first on Microsoft Security Blog .
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Cooking with Agents in VS Code — Liam Hampton, Microsoft
One codebase, three problems, three agents running at the same time. Liam Hampton from Microsoft demos the full loop in VS Code: a local agent with Claude Opus writing and fixing unit tests with him in the loop, a background agent using a git work tree to build a front end from a GitHub issue without him touching it, a
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Scaling Agents on Kubernetes with acpx and ACP — Onur Solmaz, OpenClaw
OpenClaw receives 300 to 500 pull requests per day. Most arrive AI generated, most are not mergeable, and every one of them is signal about something broken in the codebase. Onur Solmaz built acpx to process them without him in the loop. acpx is a headless CLI for the Agent Client Protocol. It replaces PTY scraping wit
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Your Coding Agent Should Do AI System Engineering — Ben Burtenshaw, Hugging Face
An agent written RMSNorm kernel hit 1.88x speedups on H100s. A finetuned Qwen3 0.6B hit 35% on LiveCodeBench. Neither result required a systems engineer. Just coding agents with the right skills loaded. Ben Burtenshaw from Hugging Face walks through three levels: using Claude Code interactively to write and benchmark C
An OpenAI model has disproved a central conjecture in discrete geometry
An OpenAI model solved the 80-year-old unit distance problem, disproving a major conjecture in discrete geometry and marking a milestone in AI-driven mathematics.
How Ramp engineers accelerate code review with Codex
How Ramp engineers use Codex with GPT-5.5 to review code and ship improvements, allowing them to get substantive feedback in minutes instead of hours.
Mini Shai Hulud: Compromised @antv npm packages enable CI/CD credential theft
Compromised @antv npm packages deploy the Mini Shai-Hulud payload to steal CI/CD secrets from Linux-based automation environments. The malware executes during npm install and targets credentials across GitHub, AWS, Kubernetes, Vault, npm, and 1Password platforms. The post Mini Shai Hulud: Compromised @antv npm packages
Securing the gaming culture of cultures
Read about the unique challenges and rewards of securing gaming platforms and how to better protect gaming communities. The post Securing the gaming culture of cultures appeared first on Microsoft Security Blog .
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Two Rival Bets on AGI: Google I/O Highlights
The biggest Google AI push of the year, but what is the bigger story? Why is Google pursuing a different fork in the road than OpenAI or Anthropic? https://assemblyai.com/aiexplained What does Gemini 3.5 Flash mean for the near-term future of AI? Plus the highlights from a provocative new paper on AI, 8 key moments you
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Any-to-Any: Building Native Multimodal Agents - Patrick Löber, Google DeepMind
Draw arrows on a map and ask Gemini to generate a picture of what you see. It produces the Golden Gate Bridge. Not because it matched pixels, but because the image generation model is built on top of Gemini's world understanding and knows what those arrows are pointing at. Patrick Löber walks through the full any-to-an
The next phase of OpenAI’s Education for Countries
OpenAI advances Education for Countries, expanding AI adoption in schools with new partnerships, teacher training, and tools to improve global learning outcomes.
Introducing RAMPART and Clarity: Open source tools to bring safety into Agent development workflow
The AI systems shipping inside enterprises today are fundamentally different from the ones we were building even two years ago, because they have moved well past answering questions and into accessing your email, retrieving records from your CRM, writing and executing code, and taking actions on your behalf across doze
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Skill issue: Lessons from skilling up coding agents to use Langfuse - Marc Klingen, Clickhouse
Without a skill, Claude Code adds Langfuse using stale pre-training context, ships broken instrumentation, then catches the failure and fetches current docs to fix it. The resulting trace captures two LLM calls with no visibility into what the agent actually did. Marc Klingen covers the six learnings from building a sk
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From 46% to 90%: Fine-Tuning Tiny LLMs for On-Device Agents — Cormac Brick, Google
Function Gemma ships at 270 million parameters and processes nearly 2,000 tokens per second prefill on a Pixel 7. Out of the box, on a fixed set of app intents, it hits 46% accuracy. Fine-tuned on a synthetically generated dataset, it clears 90% on eight of ten functions. Cormac Brick covers the two options developers
The European Union is deploying AI across strategic sectors
Explore how the EU is deploying trustworthy AI in healthcare, manufacturing, mobility and agriculture to boost competitiveness. The post The European Union is deploying AI across strategic sectors appeared first on OECD.AI .
Introducing OpenAI for Singapore
OpenAI for Singapore launches a multi-year AI partnership to expand deployment, build local talent, and support businesses and public services with AI.
Advancing content provenance for a safer, more transparent AI ecosystem
OpenAI advances AI content provenance with Content Credentials, SynthID, and a verification tool to help people identify and trust AI-generated media.
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What Breaks When You Build AI Under Sovereignty Constraints - Bilge Yücel, deepset GmbH
If you send EU citizen data to an embedding API hosted in Virginia, you have already violated GDPR. That is one hidden assumption. Most production AI systems have dozens more, baked into the architecture long before anyone asked whether the system was sovereign. Bilge Yücel walks through the four sovereignty pillars (d
Exposing Fox Tempest: A malware-signing service operation
Fox Tempest is a financially motivated threat actor operating a malware‑signing‑as‑a‑service (MSaaS) used by other cybercriminals, including Vanilla Tempest and Storm groups, to more effectively distribute malicious code, including ransomware. The post Exposing Fox Tempest: A malware-signing service operation appeared
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Don't Build Slop (4 Levels of AI Agent Maturity) - Ara Khan, Cline
The prompt for GPT-5.3 is one-third the size of the one written for GPT-5. Frontier models are so capable that longer system prompts cause sensory overload and degrade performance. The rule Ara Khan keeps returning to: every single thing you add to an agent risks making it worse. The talk breaks agent-building into fou
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Personalization in the Era of LLMs - Shivam Verma, Spotify
Spotify represents Ariana Grande and Bruno Mars as sequences of six tokens. The first two are shared because both are pop artists. The remaining tokens diverge to capture what makes each distinct. That is a Semantic ID, and it is how Spotify teaches open-weight LLMs to reason over a catalog of 100 million tracks the sa
OpenAI and Dell partner to bring Codex to hybrid and on-premise enterprise environments
OpenAI and Dell partner to bring Codex to hybrid and on-premise environments, helping enterprises deploy AI coding agents securely across data and workflows.
How Storm-2949 turned a compromised identity into a cloud-wide breach
Storm-2949 turned stolen credentials into a cloud-wide breach, moving from identity compromise to large-scale data theft without using malware. This incident shows how threat actors can exploit trusted systems to operate undetected. The post How Storm-2949 turned a compromised identity into a cloud-wide breach appeared
How to better protect your growing business in an AI-powered world
See how built-in security helps keep your growing business running, protect customer trust, and support growth. The post How to better protect your growing business in an AI-powered world appeared first on Microsoft Security Blog .
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Rewiring the State — Eoin Mulgrew, 10 Downing Street
The cabinet office was about to spend one and a half million pounds on an outside law firm to analyze the UK statute book. One engineer embedded with the in-house legal team for two weeks instead. The tool now lives with that team and can be run whenever they want. Eoin Mulgrew from the Number 10 data science team uses
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Let's go Bananas with GenMedia — Guillaume Vernade, Google DeepMind
Guillaume Vernade from Google DeepMind takes a public domain book and runs it through the full gen media stack live. Gemini reads the whole text and writes image prompts for each character and chapter. Imagen generates the portraits. Veo animates them into video clips using those images as first frames. Lyria composes
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Build Agents That Run for Hours (Without Losing the Plot) — Ash Prabaker & Andrew Wilson, Anthropic
Why self-evaluation is a trap and adversarial evaluator agents work better; why context compaction doesn't cure coherence drift but structured handoffs do; how to decompose work into testable sprint contracts; how to grade subjective output with rubrics an LLM can actually apply; and how to read traces as your primary
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Harnesses in AI: A Deep Dive — Tejas Kumar, IBM
The agent hit a login page, panicked, reported success anyway, and the upvote never happened. Tejas Kumar's diagnosis: not a prompt problem. A harness problem. The demo builds a browser agent on GPT-3.5 Turbo (consciously choosing a VERY old model to show how good harness eng can improve it a lot) against Hacker News a
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Fighting AI with AI — Lawrence Jones, Incident
Incident's AI SRE runs hundreds of prompts per investigation across logs, metrics, traces, and code. When it produces a wrong root cause analysis, there is no tractable way for a human to read through the full trace and find where the reasoning went sideways. Lawrence Jones, founding engineer at Incident.io, describes
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Why Your AI UX Is Broken (and It's Not the Model's Fault) — Mike Christensen, Ably
SSE ties a response stream to a single connection. The user refreshes the page, walks out of WiFi range, or opens a second tab and the in-progress response is gone. Abort and resume are mutually exclusive for the same reason: the only signal a client can send over a one-way pipe is closing it, so the agent cannot tell
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AIE Singapore Day 2 ft. Google DeepMind, OpenClaw, Adaption, Arize, Cloudflare, Robot Company & more
May 17, 2026 - all times in SGT -- 9am - kickoff https://www.ai.engineer/singapore#schedule join us in person and on all side events https://luma.com/1eofvp02?tk=kN58jG
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Beyond Code Coverage: Functionality Testing with Playwright — Marlene Mhangami, Microsoft
When an LLM writes your tests, it tends to write tests that confirm what the code does rather than tests that verify what the user experiences. Your test suite goes green. The app still breaks in ways none of those tests would catch. Marlene Mhangami from Microsoft makes the case for flipping the order: get the agent t
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How to Leverage Domain Expertise — Chris Lovejoy, Notius Labs
Granola's first employee was a writer who still reviews meeting note outputs and tweaks prompts directly. Chris Lovejoy says that is not a gap in the org chart. There is no objectively perfect meeting note, so you need someone with taste doing both the assessment and the improvement. He frames this as one of three patt
OpenAI and Malta partner to bring ChatGPT Plus to all citizens
OpenAI and Malta partner to expand AI access, offering ChatGPT Plus and training to help citizens build practical AI skills and use AI responsibly.
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Connecting the Dots with Context Graphs — Stephen Chin, Neo4j
Ask a vector RAG system about a patient's emphysema care plan and it returns generic advice: respiratory therapy, deep breathing. Give it a graph grounded in that patient's actual history and it knows they smoke, knows they've had an operation, and gives recommendations that reflect it. The information existed in both
How business operations teams use Codex
See how business operations teams can use Codex to create initiative briefs, strategy updates, leadership decision packets, progress updates, and more from real work inputs.
Databricks brings GPT-5.5 to enterprise agent workflows
Databricks uses GPT-5.5 for enterprise agent workflows after the model set a new state of the art on the OfficeQA Pro benchmark.
How data science teams use Codex
See how data science teams can use Codex to build root-cause briefs, impact readouts, KPI memos, scoped analyses, and dashboard specs from real work inputs.
A new personal finance experience in ChatGPT
Preview a new personal finance experience in ChatGPT for Pro users in the U.S. Securely connect your financial accounts and get AI-powered insights and guidance grounded in your financial context, goals, and priorities.
How sales teams use Codex
See how sales teams can use Codex to create pipeline briefs, meeting prep packets, forecast reviews, account plans, and stalled-deal diagnoses from real work inputs.
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Agents Don't Do Standups: Building the Post-Engineer Engineering Org — Mike Spitz, PFF
PFF ran a three-month case study: two engineers against a team of ten, same codebase, same customers. The two shipped five times a day. The ten shipped once every five days. Output measured by ticket complexity came out at 10x. Customer satisfaction went up, not down. Mike Spitz, their CTO, started with one reframe: st
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Combine Skills and MCP to Close the Context Gap — Pedro Rodrigues, Supabase
Agents working with Postgres will confidently create a view over a table with row-level security enabled and silently bypass that security in the process. Not because they can't reason. Because they don't know about the security_invoker flag, and nobody told them. Pedro Rodrigues from Supabase ran this exact test: same
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How Building with AI Can Double the Throughput of Your Engineering Team — Brian Scanlan, Intercom
Intercom hit 2x engineering throughput in under a year. Not by prompting better. By treating Claude Code like a new hire: onboarding it to a Rails monolith built over 15 years, writing skills for every recurring task, connecting it to production systems and internal tooling, and going all in on one platform instead of
Sea's View on the Future of Agentic Software Development with Codex
Sea Limited's CPO explains why the company is deploying Codex across engineering teams to accelerate AI-native software development in Asia.
Work with Codex from anywhere
Use Codex anywhere with the ChatGPT mobile app. Monitor, steer, and approve coding tasks in real time across devices and remote environments.
Helping ChatGPT better recognize context in sensitive conversations
Learn how new ChatGPT safety updates improve context awareness in sensitive conversations, helping detect risk over time and respond more safely.
Defense in depth for autonomous AI agents
Microsoft lays out a defense-in-depth model for autonomous agents, covering new threat classes such as agent hijacking, intent breaking, sensitive data leakage, supply-chain compromise, and inappropriate reliance.
Kazuar: Anatomy of a nation-state botnet
Kazuar, a sophisticated malware family attributed to the Russian state actor Secret Blizzard, has been under constant development for years and continues to evolve in support of espionage-focused operations. Over time, Kazuar has expanded from a relatively traditional backdoor into a highly modular peer-to-peer (P2P) b
Cloud CISO Perspectives: How Google + Wiz changes multicloud strategy for CISOs
By centering developers and shifting security left, Wiz has seen a significant increase in security resolution. Here’s why this strategy matters for CISOs.
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AIE Singapore Day 1 ft. Minister, NanoClaw, OpenAI, Google, Vercel, Cursor & more
May 16, 2026 - all times in SGT -- 8.30am - kickoff https://www.ai.engineer/singapore#schedule join us in person and on all side events https://luma.com/1eofvp02?tk=kN58jG
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Ship Real Agents: Hands-On Evals for Agentic Applications — Laurie Voss, Arize
Most agents get tested by running a few queries and checking if it looks right. Laurie calls this the vibes problem: it doesn't catch regressions, doesn't run in CI, and doesn't tell you whether a prompt fix broke three other things. This workshop builds a complete eval pipeline from scratch on a financial analysis age
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Mind the Gap (In your Agent Observability) — Amy Boyd & Nitya Narasimhan, Microsoft
Agents drift. Models change, prompts get tweaked, edge cases accumulate, and the gap between what your agent does and what you need it to do widens without you noticing. Amy and Nitya walk through Microsoft Foundry's observability stack: tracing built on OpenTelemetry, built-in evaluators for quality, safety, and agent
When configuration becomes a vulnerability: Exploitable misconfigurations in AI apps
Exposed UIs, weak authentication, and risky defaults could turn cloud-native AI apps on Kubernetes into potential targets by threat actors. Learn how exploitable misconfigurations lead to RCE and data leaks. The post When configuration becomes a vulnerability: Exploitable misconfigurations in AI apps appeared first on
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Make your own event-sourced agent harness using stream processors — Jonas Templestein, Iterate
The abstraction is three things: state, a synchronous reducer that derives state from events, and an after-append hook for side effects. The split matters: when your program restarts after 100 events, you want to catch up state without replaying LLM requests. Everything that happens (streaming chunks, tool calls, error
Building a safe, effective sandbox to enable Codex on Windows
Learn how OpenAI built a secure sandbox for Codex on Windows, enabling safe, efficient coding agents with controlled file access and network restrictions.
Our response to the TanStack npm supply chain attack
OpenAI describes its response to the TanStack npm supply-chain attack, including certificate rotation for macOS apps and guidance to update ChatGPT, Codex, and related desktop tooling from official channels.
The new era of SaMD: Why cloud infrastructure is the foundation for digital health in 2026
As SaMD moves from reactive diagnostics to proactive learning systems, cloud has become a superior foundation for regulated medical software.
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Your Agent Can Now Train Models — Merve Noyan, Hugging Face
Open-source models have caught up. GLM 5.1 is leading the Artificial Analysis intelligence index over closed models, and the gap is closing fast with each release cycle. The practical upside beyond benchmarks: full weight access means you can quantize, fine-tune, and deploy to edge devices or browsers without data leav
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Building a Chess Coach — Anant Dole and Asbjorn Steinskog, Take Take Take
LLMs can explain things clearly but can't play chess reliably. Take Take Take (Magnus Carlsen's app) solved this by separating concerns: Stockfish handles position evaluation, tactical and positional detectors extract concepts like forks, pins, and structural weaknesses, and the LLM's only job is translating those stru
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CI/CD Is Dead, Agents Need Continuous Compute and Computers — Hugo Santos and Madison Faulkner
Traditional CI/CD was built for humans pushing one or two diffs a week. Scale to thousands of autonomous agents opening PRs continuously and you get runner saturation, cold Docker builds on every branch, cache thrash, and a merge queue that starts behaving like a serialized database lock where time-to-commit becomes th
Patch Tuesday, May 2026 Edition
Artificial intelligence platforms may be just as susceptible to social engineering as human beings, but they are proving remarkably good at finding security vulnerabilities in human-made computer code. That reality is on full display this month with some of the more widely-used software makers -- including Apple, Googl
Beyond source code: The files AI coding agents trust — and attackers exploit
As AI coding agents become embedded in developer workflows, defenders must rethink how to protect against malicious files. Here’s what you need to know.
How finance teams use Codex
See how finance teams can use Codex to build MBRs, reporting packs, variance bridges, model checks, and planning scenarios from real work inputs.
How NVIDIA engineers and researchers build with Codex
Teams use Codex with GPT-5.5 to ship production systems and turn research ideas into runnable experiments.
What Parameter Golf taught us about AI-assisted research
Parameter Golf brought together 1,000+ participants and 2,000+ submissions to explore AI-assisted machine learning research, coding agents, quantization, and novel model design under strict constraints.
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Build & deploy AI-powered apps — Paige Bailey, Google DeepMind
Got a massive idea but stuck in the "just talking about it" phase? This session cuts the fluff and dives straight into how to build and prototype at lightning speed using AI Studio Build and Antigravity for free. It breaks down Google DeepMind's AI tech stack so viewers know exactly which tools to use, when to reach fo
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Everything I Learned Training Frontier Small Models — Maxime Labonne, Liquid AI
A new class of small models is emerging with the ability to reliably follow instructions and call tools while running on-device under 1 GB of memory. In this talk, we'll break down how to post-train frontier small models using the LFM2.5 recipe: on-policy preference alignment, agentic reinforcement learning, and curric
Anthropic Responsible Scaling Policy v3.2
Anthropic’s current Responsible Scaling Policy page lists v3.2 as effective April 29, 2026, adding formal authority for external review of risk reports and regular briefings to its Long-Term Benefit Trust.
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Building your own software factory — Eric Zakariasson, Cursor
Most of us are pair-programming with one agent and stopping there. There's a lot more on the table. This workshop is about going from one agent to many. We'll start with codebase setup, the foundational work that makes agents effective on their own. Then we'll scale up to running agents in parallel, kicking off async w
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Why building eval platforms is hard — Phil Hetzel, Braintrust
An eval platform is not just a test runner. You are building shared definitions of "good," reliable data pipelines, labelling workflows, versioning, and trust in results across many teams and model changes. This session breaks down the hidden complexity, the common failure modes, and the design principles that make eva
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One Login to Rule Them All: Cross-App Access for MCP — Garrett Galow, WorkOS
Connecting a coding agent to multiple services often means facing a dozen OAuth consent screens, a dozen token lifecycles, and a dozen chances for something to break. Despite having Single Sign-On, users still find themselves signing in repeatedly. This talk explores how Cross-App Access leverages a three-way trust bet
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Open Models at Google DeepMind — Cassidy Hardin, Google DeepMind
Open models are getting smaller, faster, and far more capable. In this talk, Cassidy Hardin walks through the latest advances in the Gemma family, with a focus on Gemma 4 and what it enables for developers building on-device and open-weight AI systems. She covers the architecture behind Gemma’s dense, effective, and mi
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Lessons from Scaling GitHub's Remote MCP Server — Sam Morrow, GitHub
GitHub operates one of the most heavily-utilised MCP servers in the ecosystem, with over 4 million downloads of the stdio server alone. Discover the architectural decisions, technical challenges and lessons learned while building and scaling a remote MCP server on production infrastructure. The session walks through th
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Bringing MCPs to the Enterprise — Karan Sampath, Anthropic
MCPs are often flaky, face multiple security vulnerabilities, and are generally hard to scale. Most enterprises struggle to use more than single digit numbers of MCPs due to issues with security, observability, and access control. In this talk, we'll explore the approaches and learnings we at Anthropic have been taking
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Collaborative AI Engineering — Maggie Appleton, GitHub Next
Agentic engineering so far has been a solo story: one developer and a dozen agents moving at warp speed. But speed without thoughtful planning and team alignment is just wasting tokens. When everyone on a team is directing agents alone in their personal CLI tools with no shared context, you get duplicate work, conflict
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MCP = Mega Context Problem - Matt Carey
The best MCP server is the one you didn't have to build. At Cloudflare we have a lot of products. Our REST OpenAPI spec is over 2.3 million tokens. When teams started building MCP servers, they did what everyone does: cherry-picked important endpoints for their product, wrote some tool definitions and shipped a separat
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Full Walkthrough: Workflow for AI Coding from Planning to Production — Matt Pocock (@mattpocockuk )
A hands-on workshop covering the full lifecycle of AI-assisted development, from turning ambiguous requirements into agent-ready plans to running autonomous coding agents that ship production features. You'll learn to stress-test vague briefs into structured PRDs, slice work into thin "tracer bullet" vertical slices, a
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AgentCraft: Putting the Orc in Orchestration — Ido Salomon
AI Engineer session on AgentCraft: Putting the Orc in Orchestration, presented by Ido Salomon. It adds practical context for how teams are building and operating AI systems in production.
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It Ain't Broke: Why Software Fundamentals Matter More Than Ever — Matt Pocock, AI Hero @mattpocockuk
AI Engineer session on It Ain't Broke: Why Software Fundamentals Matter More Than Ever, presented by Matt Pocock, AI Hero @mattpocockuk. It adds practical context for how teams are building and operating AI systems in production.
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The End of Apps — Kitze, Sizzy.co
AI Engineer session on The End of Apps, presented by Kitze, Sizzy.co. It adds practical context for how teams are building and operating AI systems in production.
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What Do Models Still Suck At? - Peter Gostev, Arena.ai, BullshitBench
AI Engineer session on What Do Models Still Suck At? - Peter Gostev, Arena.ai, BullshitBench. It adds practical context for how teams are building and operating AI systems in production.
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GPT 5.5 Arrives, DeepSeek V4 Drops, and the Compute War Intensifies
GPT 5.5 full analysis, plus DeepSeek V4 paper highlights, comparisons with Mythos, a vibe-coded game w/ GPT Image 2, and 50 data-points you wouldn’t get from just reading the headlines. https://80000hours.org/aiexplained Check out my fast-growing (!) app, free to use, and code INSIDER15 for paid tiers: https://lmcounci
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Agents need more than a chat - Jacob Lauritzen, CTO Legora
AI Engineer session on Agents need more than a chat - Jacob Lauritzen, CTO Legora. It adds practical context for how teams are building and operating AI systems in production.
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Building Generative Image & Video models at Scale - Sander Dieleman (Veo and Nano Banana)
AI Engineer session on Building Generative Image & Video models at Scale - Sander Dieleman (Veo and Nano Banana). It adds practical context for how teams are building and operating AI systems in production.
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How AI is changing Software Engineering: A Conversation with Gergely Orosz, @The Pragmatic Engineer
AI Engineer session on How AI is changing Software Engineering: A Conversation with Gergely Orosz, @The Pragmatic Engineer. It adds practical context for how teams are building and operating AI systems in production.
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AIE Miami Day 2 ft. Cerebras, OpenCode, Cursor, Arize AI, and more!
April 21, 2026 - all times in EST -- 9:00am - Welcome to Day 2 -- 9:10am - David House, G2i Transforming Programming Mindsets: Case Studies in Agentic Coding Adoption -- 9:35am - Sarah Chieng, Cerebras Help! We're DEEP in (latency) Debt -- 10:00am - Lech Kalinowski, CallStack Ambient Generative AI: Deploying Latent Dif
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Full Workshop: Build Your Own Deep Research Agents - Louis-François Bouchard, Paul Iusztin, Samridhi
AI Engineer session on Full Workshop: Build Your Own Deep Research Agents - Louis-François Bouchard, Paul Iusztin, Samridhi. It adds practical context for how teams are building and operating AI systems in production.
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Gemma, DeepMind's Family of Open Models — Omar Sanseviero, Google DeepMind
AI Engineer session on Gemma, DeepMind's Family of Open Models, presented by Omar Sanseviero, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Running LLMs on your iPhone: 40 tok/s Gemma 4 with MLX — Adrien Grondin, Locally AI
AI Engineer session on Running LLMs on your iPhone: 40 tok/s Gemma 4 with MLX, presented by Adrien Grondin, Locally AI. It adds practical context for how teams are building and operating AI systems in production.
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Taste & Craft: A Conversation with Tuomas Artman, CTO Linear & Gergely Orosz, @The Pragmatic Engineer
AI Engineer session on Taste & Craft: A Conversation with Tuomas Artman, CTO Linear & Gergely Orosz, @The Pragmatic Engineer. It adds practical context for how teams are building and operating AI systems in production.
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The New Application Layer - Malte Ubl, CTO Vercel
AI Engineer session on The New Application Layer - Malte Ubl, CTO Vercel. It adds practical context for how teams are building and operating AI systems in production.
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AIE Miami Keynote & Talks ft. OpenCode. Google Deepmind, OpenAI, and more!
April 20, 2026 - all times in EST -- 9:00am - Welcome to AI Engineer Miami -- 9:10am - Gabe Greenberg, G2i Opening Remarks -- 9:15am - Dax Raad, OpenCode Keynote -- 9:40am - Dexter Horthy, HumanLayer Everything We got Wrong About RPI -- 10:05am - Max Stoiber, OpenAI Coming Soon -- 10:30am - Morning Break -- 11:00am - B
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Code Mode: Let the Code do the Talking - Sunil Pai, Cloudflare
AI Engineer session on Code Mode: Let the Code do the Talking - Sunil Pai, Cloudflare. It adds practical context for how teams are building and operating AI systems in production.
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The Future of MCP — David Soria Parra, Anthropic
AI Engineer session on The Future of MCP, presented by David Soria Parra, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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Frontier AI and the Future of Intelligence — Raia Hadsell, VP of Research, Google DeepMind
AI Engineer session on Frontier AI and the Future of Intelligence, presented by Raia Hadsell, VP of Research, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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"The moments where you want to skip thinking are EXACTLY where thinking matters most" — Earendil
AI Engineer session on "The moments where you want to skip thinking are EXACTLY where thinking matters most", presented by Earendil. It adds practical context for how teams are building and operating AI systems in production.
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State of the Claw — Peter Steinberger
AI Engineer session on State of the Claw, presented by Peter Steinberger. It adds practical context for how teams are building and operating AI systems in production.
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Building pi in a World of Slop — Mario Zechner
AI Engineer session on Building pi in a World of Slop, presented by Mario Zechner. It adds practical context for how teams are building and operating AI systems in production.
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Claude Opus 4.7 - A New Frontier, in Performance … and Drama
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Harness Engineering: How to Build Software When Humans Steer, Agents Execute — Ryan Lopopolo, OpenAI
AI Engineer session on Harness Engineering: How to Build Software When Humans Steer, Agents Execute, presented by Ryan Lopopolo, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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$1 AI Guardrails: The Unreasonable Effectiveness of Finetuned ModernBERTs — Diego Carpentero
AI Engineer session on $1 AI Guardrails: The Unreasonable Effectiveness of Finetuned ModernBERTs, presented by Diego Carpentero. It adds practical context for how teams are building and operating AI systems in production.
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Attacking AI - Jason Haddix - NDC Security 2026
Attacking AI is a one of a kind session releasing case studies, tactics, and methodology from Arcanum’s AI assessments in 2024 and 2025. While most AI assessment material focuses on academic AI red team content, “Attacking AI” is focused on the task of assessing AI enabled systems.
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Paperclip: Open Source Human Control Plane for AI Labor — Dotta Bippa
AI Engineer session on Paperclip: Open Source Human Control Plane for AI Labor, presented by Dotta Bippa. It adds practical context for how teams are building and operating AI systems in production.
Designing transparency for government AI: Insights from the UK’s Algorithmic Transparency Recording Standard initiative
How the UK’s ATRS strengthens algorithmic transparency, public trust and accountability in government AI. The post Designing transparency for government AI: Insights from the UK’s Algorithmic Transparency Recording Standard initiative appeared first on OECD.AI .
Patch Tuesday, April 2026 Edition
Krebs on Security covers April 2026 patching activity, including a record-sized Microsoft release and active exploitation notes.
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Agentic Engineering: Working With AI, Not Just Using It — Brendan O'Leary
AI Engineer session on Agentic Engineering: Working With AI, Not Just Using It, presented by Brendan O'Leary. It adds practical context for how teams are building and operating AI systems in production.
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AI Didn’t Kill the Web, It Moved in! — Olivier Leplus (AWS) & Yohan Lasorsa (Microsoft)
AI Engineer session on AI Didn’t Kill the Web, It Moved in!, presented by Olivier Leplus (AWS) & Yohan Lasorsa (Microsoft). It adds practical context for how teams are building and operating AI systems in production.
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Bending a Public MCP Server Without Breaking It — Nimrod Hauser, Baz
AI Engineer session on Bending a Public MCP Server Without Breaking It, presented by Nimrod Hauser, Baz. It adds practical context for how teams are building and operating AI systems in production.
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Cognitive Exhaust Fumes, or: Read-Only AI Is Underrated — Šimon Podhajský, Head of AI, Waypoint
AI Engineer session on Cognitive Exhaust Fumes, or: Read-Only AI Is Underrated, presented by Šimon Podhajský, Head of AI, Waypoint. It adds practical context for how teams are building and operating AI systems in production.
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Contact Center Voice AI: Low-Latency Intelligence Extraction from Messy Audio Streams — Dippu Singh
AI Engineer session on Contact Center Voice AI: Low-Latency Intelligence Extraction from Messy Audio Streams, presented by Dippu Singh. It adds practical context for how teams are building and operating AI systems in production.
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From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work — Sandipan Bhaumik
AI Engineer session on From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work, presented by Sandipan Bhaumik. It adds practical context for how teams are building and operating AI systems in production.
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Judge the Judge: Building LLM Evaluators That Actually Work with GEPA — Mahmoud Mabrouk, Agenta AI
AI Engineer session on Judge the Judge: Building LLM Evaluators That Actually Work with GEPA, presented by Mahmoud Mabrouk, Agenta AI. It adds practical context for how teams are building and operating AI systems in production.
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Let LLMs Wander: Engineering RL Environments — Stefano Fiorucci
AI Engineer session on Let LLMs Wander: Engineering RL Environments, presented by Stefano Fiorucci. It adds practical context for how teams are building and operating AI systems in production.
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One Registry to Rule them All - Sonny Merla, Mauro Luchetti, & Mattia Redaelli, Quantyca
AI Engineer session on One Registry to Rule them All - Sonny Merla, Mauro Luchetti, & Mattia Redaelli, Quantyca. It adds practical context for how teams are building and operating AI systems in production.
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OpenRAG: An open-source stack for RAG — Phil Nash
AI Engineer session on OpenRAG: An open-source stack for RAG, presented by Phil Nash. It adds practical context for how teams are building and operating AI systems in production.
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Platforms for Humans and Machines: Engineering for the Age of Agents — Juan Herreros Elorza
AI Engineer session on Platforms for Humans and Machines: Engineering for the Age of Agents, presented by Juan Herreros Elorza. It adds practical context for how teams are building and operating AI systems in production.
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Running LLMs locally: Practical LLM Performance on DGX Spark — Mozhgan Kabiri chimeh, NVIDIA
AI Engineer session on Running LLMs locally: Practical LLM Performance on DGX Spark, presented by Mozhgan Kabiri chimeh, NVIDIA. It adds practical context for how teams are building and operating AI systems in production.
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Why, and how you need to sandbox AI-Generated Code? — Harshil Agrawal, Cloudflare
AI Engineer session on Why, and how you need to sandbox AI-Generated Code?, presented by Harshil Agrawal, Cloudflare. It adds practical context for how teams are building and operating AI systems in production.
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Your Insecure MCP Server Won't Survive Production — Tun Shwe, Lenses
AI Engineer session on Your Insecure MCP Server Won't Survive Production, presented by Tun Shwe, Lenses. It adds practical context for how teams are building and operating AI systems in production.
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Claude Mythos: Highlights from 244-page Release
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
NIST AI RMF and Critical Infrastructure Profile
NIST’s AI RMF hub now highlights its April 2026 concept note for a Trustworthy AI in Critical Infrastructure profile, extending the framework toward sector-specific operational risk management.
Assessing Claude Mythos Preview’s cybersecurity capabilities
Claude Mythos Preview is a new general-purpose language model that is strikingly capable at computer security tasks. This post provides technical details for researchers and practitioners who want to understand exactly how we have been testing this model, and what we have found over the past month. We hope this will sh
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Two AI Models Set to “stir government urgency”, But Will This Challenge Undo Them?
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
To be truly participative, stakeholder involvement should follow an AI system’s entire lifecycle
Participatory AI often stops at consultation. Why governance infrastructure, community authority and lifecycle oversight are essential for trustworthy AI. The post To be truly participative, stakeholder involvement should follow an AI system’s entire lifecycle appeared first on OECD.AI .
Why AI Sandboxes matter for responsible innovation and public trust
AI regulatory sandboxes in AI governance: benefits, design, global examples and policy insights to foster innovation, trust and compliance. The post Why AI Sandboxes matter for responsible innovation and public trust appeared first on OECD.AI .
Detecting and analyzing prompt abuse in AI tools
Microsoft Incident Response explains how to detect prompt abuse using logging, telemetry, and incident response workflows.
Designing AI agents to resist prompt injection
OpenAI frames prompt injection as an agent-security problem that increasingly resembles social engineering rather than simple string matching.
OpenAI to acquire Promptfoo
OpenAI announced plans to acquire Promptfoo, highlighting automated AI security testing, red teaming, and evaluation as core enterprise requirements.
How AI Assistants are Moving the Security Goalposts
AI-based assistants or "agents" -- autonomous programs that have access to the user's computer, files, online services and can automate virtually any task -- are growing in popularity with developers and IT workers. But as so many eyebrow-raising headlines over the past few weeks have shown, these powerful and assertiv
Reverse engineering Claude's CVE-2026-2796 exploit
This post dives deep into how Claude wrote an exploit for one of the vulnerabilities it found in Firefox.
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What the New ChatGPT 5.4 Means for the World
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Deadline extension 20 March: Global call for ‘Governing with Artificial Intelligence’: Share your initiatives and insights on AI-driven innovation in government
OECD launches a Global Call for Governing with AI, inviting governments to share AI use cases, policy initiatives, and implementation tools to support trustworthy AI in public administration. The post Deadline extension 20 March: Global call for ‘Governing with Artificial Intelligence’: Share your initiativ
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Deadline Day for Autonomous AI Weapons & Mass Surveillance
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Gemini 3.1 Pro and the Downfall of Benchmarks: Welcome to the Vibe Era of AI
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
The OECD’s new responsible AI guidance: A compass for businesses in a complex terrain
OECD Due Diligence Guidance for Responsible AI helps businesses manage AI risks, meet global standards and build trustworthy AI value chains. The post The OECD’s new responsible AI guidance: A compass for businesses in a complex terrain appeared first on OECD.AI .
MITRE ATLAS OpenClaw Investigation Discovers New and Likeliest Techniques
MITRE maps incidents in an open-source agentic ecosystem to ATLAS techniques, showing how AI-first systems create distinct attacker paths.
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The Two Best AI Models/Enemies Just Got Released Simultaneously
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
LLM-discovered 0-days
AI models can now find high-severity vulnerabilities at scale. This is a moment to empower defenders. We're now using Claude to find and help fix vulnerabilities in open source software.
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Claude AI Co-founder Publishes 4 Big Claims about Near Future: Breakdown
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
AI Act
The European Commission’s AI Act hub centralizes the EU’s risk-based AI compliance framework, implementation guidance, and enforcement resources.
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AGI: The Path Forward — Jason Warner & Eiso Kant, Poolside
AI Engineer session on AGI: The Path Forward, presented by Jason Warner & Eiso Kant, Poolside. It adds practical context for how teams are building and operating AI systems in production.
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Automating Large Scale Refactors with Parallel Agents - Robert Brennan, OpenHands
AI Engineer session on Automating Large Scale Refactors with Parallel Agents - Robert Brennan, OpenHands. It adds practical context for how teams are building and operating AI systems in production.
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Build a Prompt Learning Loop - SallyAnn DeLucia & Fuad Ali, Arize
AI Engineer session on Build a Prompt Learning Loop - SallyAnn DeLucia & Fuad Ali, Arize. It adds practical context for how teams are building and operating AI systems in production.
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Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel
AI Engineer session on Building durable Agents with Workflow DevKit & AI SDK - Peter Wielander, Vercel. It adds practical context for how teams are building and operating AI systems in production.
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Building Intelligent Research Agents with Manus - Ivan Leo, Manus AI (now Meta Superintelligence)
AI Engineer session on Building Intelligent Research Agents with Manus - Ivan Leo, Manus AI (now Meta Superintelligence). It adds practical context for how teams are building and operating AI systems in production.
![Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic video thumbnail](https://i.ytimg.com/vi/TqC1qOfiVcQ/hqdefault.jpg)
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Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic
AI Engineer session on Claude Agent SDK [Full Workshop], presented by Thariq Shihipar, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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DSPy: The End of Prompt Engineering - Kevin Madura, AlixPartners
AI Engineer session on DSPy: The End of Prompt Engineering - Kevin Madura, AlixPartners. It adds practical context for how teams are building and operating AI systems in production.
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How Claude Code Works - Jared Zoneraich, PromptLayer
AI Engineer session on How Claude Code Works - Jared Zoneraich, PromptLayer. It adds practical context for how teams are building and operating AI systems in production.
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How METR measures Long Tasks and Experienced Open Source Dev Productivity - Joel Becker, METR
AI Engineer session on How METR measures Long Tasks and Experienced Open Source Dev Productivity - Joel Becker, METR. It adds practical context for how teams are building and operating AI systems in production.
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Identity for AI Agents - Patrick Riley & Carlos Galan, Auth0
AI Engineer session on Identity for AI Agents - Patrick Riley & Carlos Galan, Auth0. It adds practical context for how teams are building and operating AI systems in production.
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Jack Morris: Stuffing Context is not Memory, Updating Weights is
AI Engineer session on Jack Morris: Stuffing Context is not Memory, Updating Weights is. It adds practical context for how teams are building and operating AI systems in production.
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OpenAI + @Temporalio : Building Durable, Production Ready Agents - Cornelia Davis, Temporal
AI Engineer session on OpenAI + @Temporalio : Building Durable, Production Ready Agents - Cornelia Davis, Temporal. It adds practical context for how teams are building and operating AI systems in production.
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Shipping AI That Works: An Evaluation Framework for PMs — Aman Khan, Arize
AI Engineer session on Shipping AI That Works: An Evaluation Framework for PMs, presented by Aman Khan, Arize. It adds practical context for how teams are building and operating AI systems in production.
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Spec-Driven Development: Agentic Coding at FAANG Scale and Quality — Al Harris, Amazon Kiro
AI Engineer session on Spec-Driven Development: Agentic Coding at FAANG Scale and Quality, presented by Al Harris, Amazon Kiro. It adds practical context for how teams are building and operating AI systems in production.
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Welcome to AIE CODE - Jed Borovik, Google DeepMind
AI Engineer session on Welcome to AIE CODE - Jed Borovik, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Why Agent Hype can fall short of reality — Joel Becker, METR
AI Engineer session on Why Agent Hype can fall short of reality, presented by Joel Becker, METR. It adds practical context for how teams are building and operating AI systems in production.
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Your MCP Server is Bad (and you should feel bad) - Jeremiah Lowin, Prefect
AI Engineer session on Your MCP Server is Bad (and you should feel bad) - Jeremiah Lowin, Prefect. It adds practical context for how teams are building and operating AI systems in production.
AI Models on Realistic Cyber Ranges
In a recent evaluation of AI models’ cyber capabilities, current Claude models can now succeed at multistage attacks on networks with dozens of hosts using only standard, open-source tools, instead of the custom tools needed by previous generations.
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Anthropic: Our AI just created a tool that can ‘automate all white collar work’, Me:
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Finding Bugs with Claude and Property-based Testing
Ensuring that programs are bug-free is one of the most challenging aspects of software engineering. We developed an agent that can efficiently identify bugs in large software projects. Our agent infers general properties of code that should be true, and then applies property-based testing. After extensive manual valida
Experimenting with AI to Defend Critical Infrastructure
AI could help defenders of critical infrastructure identify the vulnerabilities that attackers might exploit—and close them before they are exploited. Anthropic has partnered with Pacific Northwest National Laboratory (PNNL) to explore this defensive application of AI, demonstrating both the potential of AI-accelerated
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2026: The Year The IDE Died — Steve Yegge & Gene Kim, Authors, Vibe Coding
AI Engineer session on 2026: The Year The IDE Died, presented by Steve Yegge & Gene Kim, Authors, Vibe Coding. It adds practical context for how teams are building and operating AI systems in production.
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Agent Reinforcement Fine Tuning — Will Hang & Cathy Zhou, OpenAI
AI Engineer session on Agent Reinforcement Fine Tuning, presented by Will Hang & Cathy Zhou, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Agents are Robots Too: What Self-Driving Taught Me About Building Agents — Jesse Hu, Abundant
AI Engineer session on Agents are Robots Too: What Self-Driving Taught Me About Building Agents, presented by Jesse Hu, Abundant. It adds practical context for how teams are building and operating AI systems in production.
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AI Consulting in Practice — NLW, Superintelligent, @AIDailyBrief
AI Engineer session on AI Consulting in Practice, presented by NLW, Superintelligent, @AIDailyBrief. It adds practical context for how teams are building and operating AI systems in production.
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AI Copilots for Tech Architecture: The Highest-ROI Use Case You’re Not Building — Boris B., Catio
AI Engineer session on AI Copilots for Tech Architecture: The Highest-ROI Use Case You’re Not Building, presented by Boris B., Catio. It adds practical context for how teams are building and operating AI systems in production.
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AI Kernel Generation: What's working, what's not, what's next — Natalie Serrino, Gimlet Labs
AI Engineer session on AI Kernel Generation: What's working, what's not, what's next, presented by Natalie Serrino, Gimlet Labs. It adds practical context for how teams are building and operating AI systems in production.
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Amp Code: Next Generation AI Coding — Beyang Liu, Amp Code
AI Engineer session on Amp Code: Next Generation AI Coding, presented by Beyang Liu, Amp Code. It adds practical context for how teams are building and operating AI systems in production.
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Backlog.md: Terminal Kanban Board for Managing Tasks with AI Agents — Alex Gavrilescu, Funstage
AI Engineer session on Backlog.md: Terminal Kanban Board for Managing Tasks with AI Agents, presented by Alex Gavrilescu, Funstage. It adds practical context for how teams are building and operating AI systems in production.
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Building Cursor Composer — Lee Robinson, Cursor
AI Engineer session on Building Cursor Composer, presented by Lee Robinson, Cursor. It adds practical context for how teams are building and operating AI systems in production.
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Building in the Gemini Era — Kat Kampf & Ammaar Reshi, Google DeepMind
AI Engineer session on Building in the Gemini Era, presented by Kat Kampf & Ammaar Reshi, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Can you prove AI ROI in Software Eng? (Stanford 120k Devs Study) — Yegor Denisov-Blanch, Stanford
AI Engineer session on Can you prove AI ROI in Software Eng? (Stanford 120k Devs Study), presented by Yegor Denisov-Blanch, Stanford. It adds practical context for how teams are building and operating AI systems in production.
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Code World Model: Building World Models for Computation — Jacob Kahn, FAIR Meta
AI Engineer session on Code World Model: Building World Models for Computation, presented by Jacob Kahn, FAIR Meta. It adds practical context for how teams are building and operating AI systems in production.
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Coding Evals: From Code Snippets to Codebases — Naman Jain, Cursor
AI Engineer session on Coding Evals: From Code Snippets to Codebases, presented by Naman Jain, Cursor. It adds practical context for how teams are building and operating AI systems in production.
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Compilers in the Age of LLMs — Yusuf Olokoba, Muna
AI Engineer session on Compilers in the Age of LLMs, presented by Yusuf Olokoba, Muna. It adds practical context for how teams are building and operating AI systems in production.
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Context Engineering: Connecting the Dots with Graphs — Stephen Chin, Neo4j
AI Engineer session on Context Engineering: Connecting the Dots with Graphs, presented by Stephen Chin, Neo4j. It adds practical context for how teams are building and operating AI systems in production.
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Context Platform Engineering to Reduce Token Anxiety — Val Bercovici, WEKA
AI Engineer session on Context Platform Engineering to Reduce Token Anxiety, presented by Val Bercovici, WEKA. It adds practical context for how teams are building and operating AI systems in production.
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Defying Gravity - Kevin Hou, Google DeepMind
AI Engineer session on Defying Gravity - Kevin Hou, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Developer Experience in the Age of AI Coding Agents — Max Kanat-Alexander, Capital One
AI Engineer session on Developer Experience in the Age of AI Coding Agents, presented by Max Kanat-Alexander, Capital One. It adds practical context for how teams are building and operating AI systems in production.
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Developing Taste in Coding Agents: Applied Meta Neuro-Symbolic RL — Ahmad Awais, CommandCode
AI Engineer session on Developing Taste in Coding Agents: Applied Meta Neuro-Symbolic RL, presented by Ahmad Awais, CommandCode. It adds practical context for how teams are building and operating AI systems in production.
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Dispatch from the Future: building an AI-native Company — Dan Shipper, Every, AI & I
AI Engineer session on Dispatch from the Future: building an AI-native Company, presented by Dan Shipper, Every, AI & I. It adds practical context for how teams are building and operating AI systems in production.
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Don't Build Agents, Build Skills Instead — Barry Zhang & Mahesh Murag, Anthropic
AI Engineer session on Don't Build Agents, Build Skills Instead, presented by Barry Zhang & Mahesh Murag, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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Efficient Reinforcement Learning — Rhythm Garg & Linden Li, Applied Compute
AI Engineer session on Efficient Reinforcement Learning, presented by Rhythm Garg & Linden Li, Applied Compute. It adds practical context for how teams are building and operating AI systems in production.
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Enterprise Deep Research: The Next Killer App for Enterprise AI — Ofer Mendelevitch, Vectara
AI Engineer session on Enterprise Deep Research: The Next Killer App for Enterprise AI, presented by Ofer Mendelevitch, Vectara. It adds practical context for how teams are building and operating AI systems in production.
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From Arc to Dia: Lessons learned building AI Browsers — Samir Mody, The Browser Company of New York
AI Engineer session on From Arc to Dia: Lessons learned building AI Browsers, presented by Samir Mody, The Browser Company of New York. It adds practical context for how teams are building and operating AI systems in production.
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From Stateless Nightmares to Durable Agents — Samuel Colvin, Pydantic
AI Engineer session on From Stateless Nightmares to Durable Agents, presented by Samuel Colvin, Pydantic. It adds practical context for how teams are building and operating AI systems in production.
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From Vibe Coding To Vibe Engineering — Kitze, Sizzy
AI Engineer session on From Vibe Coding To Vibe Engineering, presented by Kitze, Sizzy. It adds practical context for how teams are building and operating AI systems in production.
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Future-Proof Coding Agents — Bill Chen & Brian Fioca, OpenAI
AI Engineer session on Future-Proof Coding Agents, presented by Bill Chen & Brian Fioca, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Government Agents: AI Agents Meet Tough Regulations — Mark Myshatyn, Los Alamos National Lab
AI Engineer session on Government Agents: AI Agents Meet Tough Regulations, presented by Mark Myshatyn, Los Alamos National Lab. It adds practical context for how teams are building and operating AI systems in production.
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Hacking Subagents Into Codex CLI — Brian John, Betterup
AI Engineer session on Hacking Subagents Into Codex CLI, presented by Brian John, Betterup. It adds practical context for how teams are building and operating AI systems in production.
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Hard Won Lessons from Building Effective AI Coding Agents — Nik Pash, Cline
AI Engineer session on Hard Won Lessons from Building Effective AI Coding Agents, presented by Nik Pash, Cline. It adds practical context for how teams are building and operating AI systems in production.
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Infra that fixes itself, thanks to coding agents — Mahmoud Abdelwahab, Railway
AI Engineer session on Infra that fixes itself, thanks to coding agents, presented by Mahmoud Abdelwahab, Railway. It adds practical context for how teams are building and operating AI systems in production.
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Katelyn Lesse — Evolving Claude APIs for Agents, Anthropic
AI Engineer session on Katelyn Lesse, presented by Evolving Claude APIs for Agents, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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Leadership in AI Assisted Engineering — Justin Reock, DX (acq. Atlassian)
AI Engineer session on Leadership in AI Assisted Engineering, presented by Justin Reock, DX (acq. Atlassian). It adds practical context for how teams are building and operating AI systems in production.
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Making Codebases Agent Ready — Eno Reyes, Factory AI
AI Engineer session on Making Codebases Agent Ready, presented by Eno Reyes, Factory AI. It adds practical context for how teams are building and operating AI systems in production.
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Minimax M2: Building the #1 Open Model — Olive Song, MiniMax
AI Engineer session on Minimax M2: Building the #1 Open Model, presented by Olive Song, MiniMax. It adds practical context for how teams are building and operating AI systems in production.
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Moving away from Agile: What's Next — Martin Harrysson & Natasha Maniar, McKinsey & Company
AI Engineer session on Moving away from Agile: What's Next, presented by Martin Harrysson & Natasha Maniar, McKinsey & Company. It adds practical context for how teams are building and operating AI systems in production.
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Music from AIE Code Summit - Instrumentals
AI Engineer session on Music from AIE Code Summit - Instrumentals. It adds practical context for how teams are building and operating AI systems in production.
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No More Slop — swyx
AI Engineer session on No More Slop, presented by swyx. It adds practical context for how teams are building and operating AI systems in production.
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No Vibes Allowed: Solving Hard Problems in Complex Codebases — Dex Horthy, HumanLayer
AI Engineer session on No Vibes Allowed: Solving Hard Problems in Complex Codebases, presented by Dex Horthy, HumanLayer. It adds practical context for how teams are building and operating AI systems in production.
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Paying Engineers like Salespeople — Arman Hezarkhani, Tenex
AI Engineer session on Paying Engineers like Salespeople, presented by Arman Hezarkhani, Tenex. It adds practical context for how teams are building and operating AI systems in production.
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Proactive Agents — Kath Korevec, Google Labs
AI Engineer session on Proactive Agents, presented by Kath Korevec, Google Labs. It adds practical context for how teams are building and operating AI systems in production.
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RL Environments at Scale — Will Brown, Prime Intellect
AI Engineer session on RL Environments at Scale, presented by Will Brown, Prime Intellect. It adds practical context for how teams are building and operating AI systems in production.
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Small Bets, Big Impact Building GenBI at a Fortune 100 — Asaf Bord, Northwestern Mutual
AI Engineer session on Small Bets, Big Impact Building GenBI at a Fortune 100, presented by Asaf Bord, Northwestern Mutual. It adds practical context for how teams are building and operating AI systems in production.
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The 3 Pillars of Autonomy — Michele Catasta, Replit
AI Engineer session on The 3 Pillars of Autonomy, presented by Michele Catasta, Replit. It adds practical context for how teams are building and operating AI systems in production.
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The Cure for the Vibe Coding Hangover — Corey J. Gallon, Rexmore
AI Engineer session on The Cure for the Vibe Coding Hangover, presented by Corey J. Gallon, Rexmore. It adds practical context for how teams are building and operating AI systems in production.
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The Infinite Software Crisis — Jake Nations, Netflix
AI Engineer session on The Infinite Software Crisis, presented by Jake Nations, Netflix. It adds practical context for how teams are building and operating AI systems in production.
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The State of AI Code Quality: Hype vs Reality — Itamar Friedman, Qodo
AI Engineer session on The State of AI Code Quality: Hype vs Reality, presented by Itamar Friedman, Qodo. It adds practical context for how teams are building and operating AI systems in production.
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The Unbearable Lightness of Agent Optimization — Alberto Romero, Jointly
AI Engineer session on The Unbearable Lightness of Agent Optimization, presented by Alberto Romero, Jointly. It adds practical context for how teams are building and operating AI systems in production.
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The Unreasonable Effectiveness of Prompt Learning — Aparna Dhinakaran, Arize
AI Engineer session on The Unreasonable Effectiveness of Prompt Learning, presented by Aparna Dhinakaran, Arize. It adds practical context for how teams are building and operating AI systems in production.
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Vision: Zero Bugs — Johann Schleier-Smith, Temporal
AI Engineer session on Vision: Zero Bugs, presented by Johann Schleier-Smith, Temporal. It adds practical context for how teams are building and operating AI systems in production.
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VoiceVision RAG - Integrating Visual Document Intelligence with Voice Response — Suman Debnath, AWS
AI Engineer session on VoiceVision RAG - Integrating Visual Document Intelligence with Voice Response, presented by Suman Debnath, AWS. It adds practical context for how teams are building and operating AI systems in production.
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Welcome to AIE LEAD - Alex Lieberman, Tenex
AI Engineer session on Welcome to AIE LEAD - Alex Lieberman, Tenex. It adds practical context for how teams are building and operating AI systems in production.
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What Data from 20m Pull Requests Reveal About AI Transformation — Nick Arcolano, Jellyfish
AI Engineer session on What Data from 20m Pull Requests Reveal About AI Transformation, presented by Nick Arcolano, Jellyfish. It adds practical context for how teams are building and operating AI systems in production.
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What We Learned Deploying AI within Bloomberg’s Engineering Organization — Lei Zhang, Bloomberg
AI Engineer session on What We Learned Deploying AI within Bloomberg’s Engineering Organization, presented by Lei Zhang, Bloomberg. It adds practical context for how teams are building and operating AI systems in production.
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Your Support Team Should Ship Code — Lisa Orr, Zapier
AI Engineer session on Your Support Team Should Ship Code, presented by Lisa Orr, Zapier. It adds practical context for how teams are building and operating AI systems in production.
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What the Freakiness of 2025 in AI Tells Us About 2026
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Continuously hardening ChatGPT Atlas against prompt injection attacks
OpenAI describes using automated red teaming and reinforcement learning to discover agent prompt injection attacks before they appear in the wild.
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Gemini Exponential, Demis Hassabis' ‘Proto-AGI’ coming, but …
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 5.2: OpenAI Strikes Back
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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You Are Being Told Contradictory Things About AI
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Building a Production-Ready AI Security Foundation
Google Cloud outlines a defense-in-depth view of AI security spanning application controls, data protections, and infrastructure isolation.
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AI changes *Nothing* — Dax Raad, OpenCode
AI Engineer session on AI changes *Nothing*, presented by Dax Raad, OpenCode. It adds practical context for how teams are building and operating AI systems in production.
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Z.ai GLM 4.6: What We Learned From 100 Million Open Source Downloads — Yuxuan Zhang, Z.ai
AI Engineer session on Z.ai GLM 4.6: What We Learned From 100 Million Open Source Downloads, presented by Yuxuan Zhang, Z.ai. It adds practical context for how teams are building and operating AI systems in production.
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Nano Banana Pro: But Did You Catch These 10 Details?
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Gemini 3 Pro: Breakdown
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Is GPT-5.1 Really an Upgrade? But Models Can Auto-Hack Govts, so … there’s that
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Bubble or No Bubble, AI Keeps Progressing (ft. Relentless Learning + Introspection)
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
Understanding prompt injections: a frontier security challenge
An accessible explanation of prompt injection risk in real AI products, including how third-party content can redirect or manipulate agent behavior.
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Did you miss these 2 AI stories? A *Real* LLM-crafted Breakthrough + Continual Learning Blocked?
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Sora 2 - It will only get more realistic from here
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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OpenAI Tests if GPT-5 Can Automate Your Job - 4 Unexpected Findings
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Building an Agentic Platform — Ben Kus, CTO Box
AI Engineer session on Building an Agentic Platform, presented by Ben Kus, CTO Box. It adds practical context for how teams are building and operating AI systems in production.
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Rishabh Garg, Tesla Optimus — Challenges in High Performance Robotics Systems
AI Engineer session on Rishabh Garg, Tesla Optimus, presented by Challenges in High Performance Robotics Systems. It adds practical context for how teams are building and operating AI systems in production.
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ChatGPT Can Now Call the Cops, but 'Wait till 2100 for Full Job Impact' - Altman
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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An ‘AI Bubble’? What Altman Actually said, the Facts and Nano Banana
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
![[Full Workshop] Building Conversational AI Agents - Thor Schaeff, ElevenLabs video thumbnail](https://i.ytimg.com/vi/MPtCBaZn84A/hqdefault.jpg)
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[Full Workshop] Building Conversational AI Agents - Thor Schaeff, ElevenLabs
AI Engineer session on [Full Workshop] Building Conversational AI Agents - Thor Schaeff, ElevenLabs. It adds practical context for how teams are building and operating AI systems in production.
![[Full Workshop] Building Metrics that actually work — David Karam, Pi Labs (fmr Google Search) video thumbnail](https://i.ytimg.com/vi/jxrGodnopHo/hqdefault.jpg)
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[Full Workshop] Building Metrics that actually work — David Karam, Pi Labs (fmr Google Search)
AI Engineer session on [Full Workshop] Building Metrics that actually work, presented by David Karam, Pi Labs (fmr Google Search). It adds practical context for how teams are building and operating AI systems in production.
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#define AI Engineer - Greg Brockman, OpenAI (ft. Jensen Huang)
AI Engineer session on #define AI Engineer - Greg Brockman, OpenAI (ft. Jensen Huang). It adds practical context for how teams are building and operating AI systems in production.
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2025 is the Year of Evals! Just like 2024, and 2023, and … — John Dickerson, CEO Mozilla AI
AI Engineer session on 2025 is the Year of Evals! Just like 2024, and 2023, and …, presented by John Dickerson, CEO Mozilla AI. It adds practical context for how teams are building and operating AI systems in production.
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A2A & MCP Workshop: Automating Business Processes with LLMs — Damien Murphy, Bench
AI Engineer session on A2A & MCP Workshop: Automating Business Processes with LLMs, presented by Damien Murphy, Bench. It adds practical context for how teams are building and operating AI systems in production.
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Agents vs Workflows: Why Not Both? — Sam Bhagwat, Mastra.ai
AI Engineer session on Agents vs Workflows: Why Not Both?, presented by Sam Bhagwat, Mastra.ai. It adds practical context for how teams are building and operating AI systems in production.
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AI That Pays: Lessons from Revenue Cycle — Nathan Wan, Ensemble Health
AI Engineer session on AI That Pays: Lessons from Revenue Cycle, presented by Nathan Wan, Ensemble Health. It adds practical context for how teams are building and operating AI systems in production.
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AX is the only Experience that Matters - Ivan Burazin, Daytona
AI Engineer session on AX is the only Experience that Matters - Ivan Burazin, Daytona. It adds practical context for how teams are building and operating AI systems in production.
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Beyond the Prototype: Using AI to Write High-Quality Code - Josh Albrecht, Imbue
AI Engineer session on Beyond the Prototype: Using AI to Write High-Quality Code - Josh Albrecht, Imbue. It adds practical context for how teams are building and operating AI systems in production.
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Building a Smarter AI Agent with Neural RAG - Will Bryk, Exa.ai
AI Engineer session on Building a Smarter AI Agent with Neural RAG - Will Bryk, Exa.ai. It adds practical context for how teams are building and operating AI systems in production.
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Building Agents at Cloud Scale — Antje Barth, AWS
AI Engineer session on Building Agents at Cloud Scale, presented by Antje Barth, AWS. It adds practical context for how teams are building and operating AI systems in production.
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Building AI Products That Actually Work — Ben Hylak (Raindrop), Sid Bendre (Oleve)
AI Engineer session on Building AI Products That Actually Work, presented by Ben Hylak (Raindrop), Sid Bendre (Oleve). It adds practical context for how teams are building and operating AI systems in production.
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Building Alice’s Brain: an AI Sales Rep that Learns Like a Human - Sherwood & Satwik, 11x
AI Engineer session on Building Alice’s Brain: an AI Sales Rep that Learns Like a Human - Sherwood & Satwik, 11x. It adds practical context for how teams are building and operating AI systems in production.
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Building Applications with AI Agents — Michael Albada, Microsoft
AI Engineer session on Building Applications with AI Agents, presented by Michael Albada, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Building the platform for agent coordination — Tom Moor, Linear
AI Engineer session on Building the platform for agent coordination, presented by Tom Moor, Linear. It adds practical context for how teams are building and operating AI systems in production.
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Designing AI-Intensive Applications - swyx
AI Engineer session on Designing AI-Intensive Applications - swyx. It adds practical context for how teams are building and operating AI systems in production.
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Devin 2.0 and the Future of SWE - Scott Wu, Cognition
AI Engineer session on Devin 2.0 and the Future of SWE - Scott Wu, Cognition. It adds practical context for how teams are building and operating AI systems in production.
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Evals Are Not Unit Tests — Ido Pesok, Vercel v0
AI Engineer session on Evals Are Not Unit Tests, presented by Ido Pesok, Vercel v0. It adds practical context for how teams are building and operating AI systems in production.
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Evaluating AI Search: A Practical Framework for Augmented AI Systems — Quotient AI + Tavily
AI Engineer session on Evaluating AI Search: A Practical Framework for Augmented AI Systems, presented by Quotient AI + Tavily. It adds practical context for how teams are building and operating AI systems in production.
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Everything is ugly, so go build something that isn't — Raiza Martin, Huxe (ex NotebookLM)
AI Engineer session on Everything is ugly, so go build something that isn't, presented by Raiza Martin, Huxe (ex NotebookLM). It adds practical context for how teams are building and operating AI systems in production.
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Five hard earned lessons about Evals — Ankur Goyal, Braintrust
AI Engineer session on Five hard earned lessons about Evals, presented by Ankur Goyal, Braintrust. It adds practical context for how teams are building and operating AI systems in production.
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Form factors for your new AI coworkers — Craig Wattrus, Flatfile
AI Engineer session on Form factors for your new AI coworkers, presented by Craig Wattrus, Flatfile. It adds practical context for how teams are building and operating AI systems in production.
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From Self-driving to Autonomous Voice Agents — Brooke Hopkins, Coval
AI Engineer session on From Self-driving to Autonomous Voice Agents, presented by Brooke Hopkins, Coval. It adds practical context for how teams are building and operating AI systems in production.
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Full Workshop: Realtime Voice AI — Mark Backman, Daily
AI Engineer session on Full Workshop: Realtime Voice AI, presented by Mark Backman, Daily. It adds practical context for how teams are building and operating AI systems in production.
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Fuzzing in the GenAI Era — Leonard Tang, Haize Labs
AI Engineer session on Fuzzing in the GenAI Era, presented by Leonard Tang, Haize Labs. It adds practical context for how teams are building and operating AI systems in production.
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Hacking the Inference Pareto Frontier - Kyle Kranen, NVIDIA
AI Engineer session on Hacking the Inference Pareto Frontier - Kyle Kranen, NVIDIA. It adds practical context for how teams are building and operating AI systems in production.
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How BlackRock Builds Custom Knowledge Apps at Scale — Vaibhav Page & Infant Vasanth, BlackRock
AI Engineer session on How BlackRock Builds Custom Knowledge Apps at Scale, presented by Vaibhav Page & Infant Vasanth, BlackRock. It adds practical context for how teams are building and operating AI systems in production.
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How to defend your sites from AI bots — David Mytton, Arcjet
AI Engineer session on How to defend your sites from AI bots, presented by David Mytton, Arcjet. It adds practical context for how teams are building and operating AI systems in production.
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How to Improve your Vibe Coding — Ian Butler
AI Engineer session on How to Improve your Vibe Coding, presented by Ian Butler. It adds practical context for how teams are building and operating AI systems in production.
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How to look at your data — Jeff Huber (Chroma) + Jason Liu (567)
AI Engineer session on How to look at your data, presented by Jeff Huber (Chroma) + Jason Liu (567). It adds practical context for how teams are building and operating AI systems in production.
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How to Secure Agents using OAuth — Jared Hanson (Keycard, Passport.js)
AI Engineer session on How to Secure Agents using OAuth, presented by Jared Hanson (Keycard, Passport.js). It adds practical context for how teams are building and operating AI systems in production.
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How we hacked YC Spring 2025 batch’s AI agents — Rene Brandel, Casco
AI Engineer session on How we hacked YC Spring 2025 batch’s AI agents, presented by Rene Brandel, Casco. It adds practical context for how teams are building and operating AI systems in production.
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Human seeded Evals — Samuel Colvin, Pydantic
AI Engineer session on Human seeded Evals, presented by Samuel Colvin, Pydantic. It adds practical context for how teams are building and operating AI systems in production.
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Information Retrieval from the Ground Up - Philipp Krenn, Elastic
AI Engineer session on Information Retrieval from the Ground Up - Philipp Krenn, Elastic. It adds practical context for how teams are building and operating AI systems in production.
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Infrastructure for the Singularity — Jesse Han, Morph
AI Engineer session on Infrastructure for the Singularity, presented by Jesse Han, Morph. It adds practical context for how teams are building and operating AI systems in production.
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Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten
AI Engineer session on Introduction to LLM serving with SGLang - Philip Kiely and Yineng Zhang, Baseten. It adds practical context for how teams are building and operating AI systems in production.
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Latent Space Paper Club: AIEWF Special Edition (Test of Time, DeepSeek R1/V3) — VIbhu Sapra
AI Engineer session on Latent Space Paper Club: AIEWF Special Edition (Test of Time, DeepSeek R1/V3), presented by VIbhu Sapra. It adds practical context for how teams are building and operating AI systems in production.
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Layering every technique in RAG, one query at a time - David Karam, Pi Labs (fmr. Google Search)
AI Engineer session on Layering every technique in RAG, one query at a time - David Karam, Pi Labs (fmr. Google Search). It adds practical context for how teams are building and operating AI systems in production.
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Make your LLM app a Domain Expert: How to Build an Expert System — Christopher Lovejoy, Anterior
AI Engineer session on Make your LLM app a Domain Expert: How to Build an Expert System, presented by Christopher Lovejoy, Anterior. It adds practical context for how teams are building and operating AI systems in production.
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Mentoring the Machine — Eric Hou, Augment Code
AI Engineer session on Mentoring the Machine, presented by Eric Hou, Augment Code. It adds practical context for how teams are building and operating AI systems in production.
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Multi Agent AI and Network Knowledge Graphs for Change — Ola Mabadeje, Cisco
AI Engineer session on Multi Agent AI and Network Knowledge Graphs for Change, presented by Ola Mabadeje, Cisco. It adds practical context for how teams are building and operating AI systems in production.
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On Engineering AI Systems that Endure The Bitter Lesson - Omar Khattab, DSPy & Databricks
AI Engineer session on On Engineering AI Systems that Endure The Bitter Lesson - Omar Khattab, DSPy & Databricks. It adds practical context for how teams are building and operating AI systems in production.
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OpenAI on Securing Code-Executing AI Agents — Fouad Matin (Codex, Agent Robustness)
AI Engineer session on OpenAI on Securing Code-Executing AI Agents, presented by Fouad Matin (Codex, Agent Robustness). It adds practical context for how teams are building and operating AI systems in production.
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Perceptual Evaluations: Evals for Aesthetics — Diego Rodriguez, Krea.ai
AI Engineer session on Perceptual Evaluations: Evals for Aesthetics, presented by Diego Rodriguez, Krea.ai. It adds practical context for how teams are building and operating AI systems in production.
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Piloting agents in GitHub Copilot - Christopher Harrison, Microsoft
AI Engineer session on Piloting agents in GitHub Copilot - Christopher Harrison, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Pipecat Cloud: Enterprise Voice Agents Built On Open Source - Kwindla Hultman Kramer, Daily
AI Engineer session on Pipecat Cloud: Enterprise Voice Agents Built On Open Source - Kwindla Hultman Kramer, Daily. It adds practical context for how teams are building and operating AI systems in production.
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Practical tactics to build reliable AI apps — Dmitry Kuchin, Multinear
AI Engineer session on Practical tactics to build reliable AI apps, presented by Dmitry Kuchin, Multinear. It adds practical context for how teams are building and operating AI systems in production.
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Real World Development with GitHub Copilot and VS Code — Harald Kirschner, Christopher Harrison
AI Engineer session on Real World Development with GitHub Copilot and VS Code, presented by Harald Kirschner, Christopher Harrison. It adds practical context for how teams are building and operating AI systems in production.
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Real-time Experiments with an AI Co-Scientist - Stefania Druga, fmr. Google Deepmind
AI Engineer session on Real-time Experiments with an AI Co-Scientist - Stefania Druga, fmr. Google Deepmind. It adds practical context for how teams are building and operating AI systems in production.
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Rise of the AI Architect — Clay Bavor, Cofounder, Sierra w/ Alessio Fanelli
AI Engineer session on Rise of the AI Architect, presented by Clay Bavor, Cofounder, Sierra w/ Alessio Fanelli. It adds practical context for how teams are building and operating AI systems in production.
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Robotics: why now? - Quan Vuong and Jost Tobias Springberg, Physical Intelligence
AI Engineer session on Robotics: why now? - Quan Vuong and Jost Tobias Springberg, Physical Intelligence. It adds practical context for how teams are building and operating AI systems in production.
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Scaling AI Agents Without Breaking Reliability — Preeti Somal, Temporal
AI Engineer session on Scaling AI Agents Without Breaking Reliability, presented by Preeti Somal, Temporal. It adds practical context for how teams are building and operating AI systems in production.
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Scaling Enterprise-Grade RAG: Lessons from Legal Frontier - Calvin Qi (Harvey), Chang She (Lance)
AI Engineer session on Scaling Enterprise-Grade RAG: Lessons from Legal Frontier - Calvin Qi (Harvey), Chang She (Lance). It adds practical context for how teams are building and operating AI systems in production.
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Serving Voice AI at $1/hr: Open-source, LoRAs, Latency, Load Balancing - Neil Dwyer, Gabber
AI Engineer session on Serving Voice AI at $1/hr: Open-source, LoRAs, Latency, Load Balancing - Neil Dwyer, Gabber. It adds practical context for how teams are building and operating AI systems in production.
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Ship Agents that Ship: A Hands-On Workshop - Kyle Penfound, Jeremy Adams, Dagger
AI Engineer session on Ship Agents that Ship: A Hands-On Workshop - Kyle Penfound, Jeremy Adams, Dagger. It adds practical context for how teams are building and operating AI systems in production.
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Ship Production Software in Minutes, Not Months — Eno Reyes, Factory
AI Engineer session on Ship Production Software in Minutes, Not Months, presented by Eno Reyes, Factory. It adds practical context for how teams are building and operating AI systems in production.
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Shipping Products When You Don't Know What they Can Do — Ben Stein, Teammates
AI Engineer session on Shipping Products When You Don't Know What they Can Do, presented by Ben Stein, Teammates. It adds practical context for how teams are building and operating AI systems in production.
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Shipping something to someone always wins — Kenneth Auchenberg (ex. Stripe, VSCode)
AI Engineer session on Shipping something to someone always wins, presented by Kenneth Auchenberg (ex. Stripe, VSCode). It adds practical context for how teams are building and operating AI systems in production.
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Software Development Agents: What Works and What Doesn't - Robert Brennan, OpenHands
AI Engineer session on Software Development Agents: What Works and What Doesn't - Robert Brennan, OpenHands. It adds practical context for how teams are building and operating AI systems in production.
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State of Startups and AI 2025 - Sarah Guo, Conviction
AI Engineer session on State of Startups and AI 2025 - Sarah Guo, Conviction. It adds practical context for how teams are building and operating AI systems in production.
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Strategies for LLM Evals (GuideLLM, lm-eval-harness, OpenAI Evals Workshop) — Taylor Jordan Smith
AI Engineer session on Strategies for LLM Evals (GuideLLM, lm-eval-harness, OpenAI Evals Workshop), presented by Taylor Jordan Smith. It adds practical context for how teams are building and operating AI systems in production.
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Structuring a modern AI team — Denys Linkov, Wisedocs
AI Engineer session on Structuring a modern AI team, presented by Denys Linkov, Wisedocs. It adds practical context for how teams are building and operating AI systems in production.
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The 2025 AI Engineering Report — Barr Yaron, Amplify
AI Engineer session on The 2025 AI Engineering Report, presented by Barr Yaron, Amplify. It adds practical context for how teams are building and operating AI systems in production.
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The AI Engineer’s Guide to Raising VC — Dani Grant (Jam), Chelcie Taylor (Notable)
AI Engineer session on The AI Engineer’s Guide to Raising VC, presented by Dani Grant (Jam), Chelcie Taylor (Notable). It adds practical context for how teams are building and operating AI systems in production.
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The Future of Evals - Ankur Goyal, Braintrust
AI Engineer session on The Future of Evals - Ankur Goyal, Braintrust. It adds practical context for how teams are building and operating AI systems in production.
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The Next Unicorns: 7 Top AI startups from the HF0 Residency
AI Engineer session on The Next Unicorns: 7 Top AI startups from the HF0 Residency. It adds practical context for how teams are building and operating AI systems in production.
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The Rise of Open Models in the Enterprise — Amir Haghighat, Baseten
AI Engineer session on The Rise of Open Models in the Enterprise, presented by Amir Haghighat, Baseten. It adds practical context for how teams are building and operating AI systems in production.
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The Unofficial Guide to Apple’s Private Cloud Compute - Jmo, CONFSEC
AI Engineer session on The Unofficial Guide to Apple’s Private Cloud Compute - Jmo, CONFSEC. It adds practical context for how teams are building and operating AI systems in production.
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Useful General Intelligence — Danielle Perszyk, Amazon AGI
AI Engineer session on Useful General Intelligence, presented by Danielle Perszyk, Amazon AGI. It adds practical context for how teams are building and operating AI systems in production.
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Vibe Coding with Confidence — Itamar Friedman, Qodo
AI Engineer session on Vibe Coding with Confidence, presented by Itamar Friedman, Qodo. It adds practical context for how teams are building and operating AI systems in production.
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Vibes won't cut it — Chris Kelly, Augment Code
AI Engineer session on Vibes won't cut it, presented by Chris Kelly, Augment Code. It adds practical context for how teams are building and operating AI systems in production.
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Vision AI in 2025 — Peter Robicheaux, Roboflow
AI Engineer session on Vision AI in 2025, presented by Peter Robicheaux, Roboflow. It adds practical context for how teams are building and operating AI systems in production.
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Waymo's EMMA: Teaching Cars to Think - Jyh Jing Hwang, Waymo
AI Engineer session on Waymo's EMMA: Teaching Cars to Think - Jyh Jing Hwang, Waymo. It adds practical context for how teams are building and operating AI systems in production.
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What Is a Humanoid Foundation Model? An Introduction to GR00T N1 - Annika & Aastha
AI Engineer session on What Is a Humanoid Foundation Model? An Introduction to GR00T N1 - Annika & Aastha. It adds practical context for how teams are building and operating AI systems in production.
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Why ChatGPT Keeps Interrupting You — Dr. Tom Shapland, LiveKit
AI Engineer session on Why ChatGPT Keeps Interrupting You, presented by Dr. Tom Shapland, LiveKit. It adds practical context for how teams are building and operating AI systems in production.
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Why We Don’t Need More Data Centers - Dr. Jasper Zhang, Hyperbolic
AI Engineer session on Why We Don’t Need More Data Centers - Dr. Jasper Zhang, Hyperbolic. It adds practical context for how teams are building and operating AI systems in production.
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Why you should care about AI interpretability - Mark Bissell, Goodfire AI
AI Engineer session on Why you should care about AI interpretability - Mark Bissell, Goodfire AI. It adds practical context for how teams are building and operating AI systems in production.
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Why your product needs an AI product manager, and why it should be you — James Lowe, i.AI
AI Engineer session on Why your product needs an AI product manager, and why it should be you, presented by James Lowe, i.AI. It adds practical context for how teams are building and operating AI systems in production.
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Wisdom-Driven Knowledge Augmented Generation at Scale - Chin Keong Lam, Patho AI
AI Engineer session on Wisdom-Driven Knowledge Augmented Generation at Scale - Chin Keong Lam, Patho AI. It adds practical context for how teams are building and operating AI systems in production.
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Your Coding Agent Just Got Cloned And Your Brain Isn't Ready - Rustin Banks, Google Jules
AI Engineer session on Your Coding Agent Just Got Cloned And Your Brain Isn't Ready - Rustin Banks, Google Jules. It adds practical context for how teams are building and operating AI systems in production.
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Your realtime AI is ngmi — Sean DuBois (OpenAI), Kwindla Kramer (Daily)
AI Engineer session on Your realtime AI is ngmi, presented by Sean DuBois (OpenAI), Kwindla Kramer (Daily). It adds practical context for how teams are building and operating AI systems in production.
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GPT-5 has Arrived
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Genie 3: The World Becomes Playable (DeepMind)
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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"Data readiness" is a Myth: Reliable AI with an Agentic Semantic Layer — Anushrut Gupta, PromptQL
AI Engineer session on "Data readiness" is a Myth: Reliable AI with an Agentic Semantic Layer, presented by Anushrut Gupta, PromptQL. It adds practical context for how teams are building and operating AI systems in production.
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(possible dupe but better sound) What does Enterprise Ready MCP mean? — Tobin South, WorkOS
AI Engineer session on (possible dupe but better sound) What does Enterprise Ready MCP mean?, presented by Tobin South, WorkOS. It adds practical context for how teams are building and operating AI systems in production.
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[Evals Workshop] Mastering AI Evaluation: From Playground to Production
AI Engineer session on [Evals Workshop] Mastering AI Evaluation: From Playground to Production. It adds practical context for how teams are building and operating AI systems in production.
![[Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han video thumbnail](https://i.ytimg.com/vi/OkEGJ5G3foU/hqdefault.jpg)
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[Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents — Daniel Han
AI Engineer session on [Full Workshop] Reinforcement Learning, Kernels, Reasoning, Quantization & Agents, presented by Daniel Han. It adds practical context for how teams are building and operating AI systems in production.
![[Full Workshop] Vibe Coding at Scale: Customizing AI Assistants for Enterprise Environments video thumbnail](https://i.ytimg.com/vi/EAfP8pDs7h4/hqdefault.jpg)
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[Full Workshop] Vibe Coding at Scale: Customizing AI Assistants for Enterprise Environments
AI Engineer session on [Full Workshop] Vibe Coding at Scale: Customizing AI Assistants for Enterprise Environments. It adds practical context for how teams are building and operating AI systems in production.
![[Workshop] AI Pipelines and Agents in Pure TypeScript with Mastra.ai — Nick Nisi, Zack Proser video thumbnail](https://i.ytimg.com/vi/FWlRHPZWyHE/hqdefault.jpg)
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[Workshop] AI Pipelines and Agents in Pure TypeScript with Mastra.ai — Nick Nisi, Zack Proser
AI Engineer session on [Workshop] AI Pipelines and Agents in Pure TypeScript with Mastra.ai, presented by Nick Nisi, Zack Proser. It adds practical context for how teams are building and operating AI systems in production.
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12-Factor Agents: Patterns of reliable LLM applications — Dex Horthy, HumanLayer
AI Engineer session on 12-Factor Agents: Patterns of reliable LLM applications, presented by Dex Horthy, HumanLayer. It adds practical context for how teams are building and operating AI systems in production.
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2025 in LLMs so far, illustrated by Pelicans on Bicycles — Simon Willison
AI Engineer session on 2025 in LLMs so far, illustrated by Pelicans on Bicycles, presented by Simon Willison. It adds practical context for how teams are building and operating AI systems in production.
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3 ingredients for building reliable enterprise agents - Harrison Chase, LangChain/LangGraph
AI Engineer session on 3 ingredients for building reliable enterprise agents - Harrison Chase, LangChain/LangGraph. It adds practical context for how teams are building and operating AI systems in production.
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360Brew: LLM-based Personalized Ranking and Recommendation - Hamed and Maziar, LinkedIn AI
AI Engineer session on 360Brew: LLM-based Personalized Ranking and Recommendation - Hamed and Maziar, LinkedIn AI. It adds practical context for how teams are building and operating AI systems in production.
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A Taxonomy for Next-gen Reasoning — Nathan Lambert, Allen Institute (AI2) & Interconnects.ai
AI Engineer session on A Taxonomy for Next-gen Reasoning, presented by Nathan Lambert, Allen Institute (AI2) & Interconnects.ai. It adds practical context for how teams are building and operating AI systems in production.
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A year of Gemini progress + what comes next — Logan Kilpatrick, Google DeepMind
AI Engineer session on A year of Gemini progress + what comes next, presented by Logan Kilpatrick, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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Agentic Excellence: Mastering AI Agent Evals w/ Azure AI Evaluation SDK — Cedric Vidal, Microsoft
AI Engineer session on Agentic Excellence: Mastering AI Agent Evals w/ Azure AI Evaluation SDK, presented by Cedric Vidal, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Agentic GraphRAG: AI’s Logical Edge — Stephen Chin, Neo4j
AI Engineer session on Agentic GraphRAG: AI’s Logical Edge, presented by Stephen Chin, Neo4j. It adds practical context for how teams are building and operating AI systems in production.
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Agentic GraphRAG: Simplifying Retrieval Across Structured & Unstructured Data — Zach Blumenfeld
AI Engineer session on Agentic GraphRAG: Simplifying Retrieval Across Structured & Unstructured Data, presented by Zach Blumenfeld. It adds practical context for how teams are building and operating AI systems in production.
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Agents, Access, and the Future of Machine Identity — Nick Nisi (WorkOS) + Lizzie Siegle (Cloudflare)
AI Engineer session on Agents, Access, and the Future of Machine Identity, presented by Nick Nisi (WorkOS) + Lizzie Siegle (Cloudflare). It adds practical context for how teams are building and operating AI systems in production.
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AI Engineering with the Google Gemini 2.5 Model Family - Philipp Schmid, Google DeepMind
AI Engineer session on AI Engineering with the Google Gemini 2.5 Model Family - Philipp Schmid, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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AI powered entomology: Lessons from millions of AI code reviews — Tomas Reimers, Graphite
AI Engineer session on AI powered entomology: Lessons from millions of AI code reviews, presented by Tomas Reimers, Graphite. It adds practical context for how teams are building and operating AI systems in production.
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AI Red Teaming Agent: Azure AI Foundry — Nagkumar Arkalgud & Keiji Kanazawa, Microsoft
AI Engineer session on AI Red Teaming Agent: Azure AI Foundry, presented by Nagkumar Arkalgud & Keiji Kanazawa, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Architecting Agent Memory: Principles, Patterns, and Best Practices — Richmond Alake, MongoDB
AI Engineer session on Architecting Agent Memory: Principles, Patterns, and Best Practices, presented by Richmond Alake, MongoDB. It adds practical context for how teams are building and operating AI systems in production.
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Automating Escrow with USDC and AI - Corey Cooper, Circle
AI Engineer session on Automating Escrow with USDC and AI - Corey Cooper, Circle. It adds practical context for how teams are building and operating AI systems in production.
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Benchmarks Are Memes: How What We Measure Shapes AI — and Us - Alex Duffy, Every.to
AI Engineer session on Benchmarks Are Memes: How What We Measure Shapes AI, presented by and Us - Alex Duffy, Every.to. It adds practical context for how teams are building and operating AI systems in production.
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Bolt.new: How we scaled $0-20m ARR in 60 days, with 15 people — Eric Simons, Bolt
AI Engineer session on Bolt.new: How we scaled $0-20m ARR in 60 days, with 15 people, presented by Eric Simons, Bolt. It adds practical context for how teams are building and operating AI systems in production.
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Books reimagined: AI to create new experiences for things you know — Lukasz Gandecki, TheBrain.pro
AI Engineer session on Books reimagined: AI to create new experiences for things you know, presented by Lukasz Gandecki, TheBrain.pro. It adds practical context for how teams are building and operating AI systems in production.
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Build Dynamic Products, and Stop the AI Sideshow — Eliza Cabrera (Workday) + Jeremy Silva (Freeplay)
AI Engineer session on Build Dynamic Products, and Stop the AI Sideshow, presented by Eliza Cabrera (Workday) + Jeremy Silva (Freeplay). It adds practical context for how teams are building and operating AI systems in production.
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Building a 10 person unicorn - Max Brodeur-Urbas, Gumloop
AI Engineer session on Building a 10 person unicorn - Max Brodeur-Urbas, Gumloop. It adds practical context for how teams are building and operating AI systems in production.
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Building agent fleet architectures your CISO doesn't hate — Lou Bichard, Gitpod
AI Engineer session on Building agent fleet architectures your CISO doesn't hate, presented by Lou Bichard, Gitpod. It adds practical context for how teams are building and operating AI systems in production.
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Building Agentic Applications w/ Heroku Managed Inference and Agents — Julián Duque & Anush Dsouza
AI Engineer session on Building Agentic Applications w/ Heroku Managed Inference and Agents, presented by Julián Duque & Anush Dsouza. It adds practical context for how teams are building and operating AI systems in production.
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Building Agents (the hard parts!) - Rita Kozlov, Cloudflare
AI Engineer session on Building Agents (the hard parts!) - Rita Kozlov, Cloudflare. It adds practical context for how teams are building and operating AI systems in production.
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Building Code First AI Agents with Azure AI Agent Service — Cedric Vidal, Microsoft
AI Engineer session on Building Code First AI Agents with Azure AI Agent Service, presented by Cedric Vidal, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Building Effective Voice Agents — Toki Sherbakov + Anoop Kotha, OpenAI
AI Engineer session on Building Effective Voice Agents, presented by Toki Sherbakov + Anoop Kotha, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Building Multimodal AI Agents From Scratch — Apoorva Joshi, MongoDB
AI Engineer session on Building Multimodal AI Agents From Scratch, presented by Apoorva Joshi, MongoDB. It adds practical context for how teams are building and operating AI systems in production.
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Building voice agents with OpenAI — Dominik Kundel, OpenAI
AI Engineer session on Building voice agents with OpenAI, presented by Dominik Kundel, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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CI in the Era of AI: From Unit Tests to Stochastic Evals — Nathan Sobo, Zed
AI Engineer session on CI in the Era of AI: From Unit Tests to Stochastic Evals, presented by Nathan Sobo, Zed. It adds practical context for how teams are building and operating AI systems in production.
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CIAM for AI: Authn/Authz for Agents — Michael Grinich, CEO of WorkOS
AI Engineer session on CIAM for AI: Authn/Authz for Agents, presented by Michael Grinich, CEO of WorkOS. It adds practical context for how teams are building and operating AI systems in production.
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Claude Code & the evolution of agentic coding — Boris Cherny, Anthropic
AI Engineer session on Claude Code & the evolution of agentic coding, presented by Boris Cherny, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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Collaborating with Agents in your Software Dev Workflow - Jon Peck & Christopher Harrison, Microsoft
AI Engineer session on Collaborating with Agents in your Software Dev Workflow - Jon Peck & Christopher Harrison, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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ComfyUI Full Workshop — first workshop from ComfyAnonymous himself!
AI Engineer session on ComfyUI Full Workshop, presented by first workshop from ComfyAnonymous himself!. It adds practical context for how teams are building and operating AI systems in production.
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Conquering Agent Chaos — Rick Blalock, Agentuity
AI Engineer session on Conquering Agent Chaos, presented by Rick Blalock, Agentuity. It adds practical context for how teams are building and operating AI systems in production.
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Containing Agent Chaos — Solomon Hykes, Dagger
AI Engineer session on Containing Agent Chaos, presented by Solomon Hykes, Dagger. It adds practical context for how teams are building and operating AI systems in production.
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Continuous Profiling for GPUs — Matthias Loibl, Polar Signals
AI Engineer session on Continuous Profiling for GPUs, presented by Matthias Loibl, Polar Signals. It adds practical context for how teams are building and operating AI systems in production.
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Critical AI Inference your CIO can Trust — Sahil Yadav, Hariharan Ganesan, Telemetrak
AI Engineer session on Critical AI Inference your CIO can Trust, presented by Sahil Yadav, Hariharan Ganesan, Telemetrak. It adds practical context for how teams are building and operating AI systems in production.
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Data is Your Differentiator: Building Secure and Tailored AI Systems — Mani Khanuja, AWS
AI Engineer session on Data is Your Differentiator: Building Secure and Tailored AI Systems, presented by Mani Khanuja, AWS. It adds practical context for how teams are building and operating AI systems in production.
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Design like Karpathy is watching — Zeke Sikelianos, Replicate
AI Engineer session on Design like Karpathy is watching, presented by Zeke Sikelianos, Replicate. It adds practical context for how teams are building and operating AI systems in production.
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Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford
AI Engineer session on Does AI Actually Boost Developer Productivity? (100k Devs Study) - Yegor Denisov-Blanch, Stanford. It adds practical context for how teams are building and operating AI systems in production.
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Don’t get one-shotted: Use AI to test, review, merge, and deploy code — Tomas Reimers, Graphite
AI Engineer session on Don’t get one-shotted: Use AI to test, review, merge, and deploy code, presented by Tomas Reimers, Graphite. It adds practical context for how teams are building and operating AI systems in production.
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Dream Machine: Scaling to 1m users in 4 days — Keegan McCallum, Luma AI
AI Engineer session on Dream Machine: Scaling to 1m users in 4 days, presented by Keegan McCallum, Luma AI. It adds practical context for how teams are building and operating AI systems in production.
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Effective agent design patterns in production — Laurie Voss, LlamaIndex
AI Engineer session on Effective agent design patterns in production, presented by Laurie Voss, LlamaIndex. It adds practical context for how teams are building and operating AI systems in production.
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Engineering Better Evals: Scalable LLM Evaluation Pipelines That Work — Dat Ngo, Aman Khan, Arize
AI Engineer session on Engineering Better Evals: Scalable LLM Evaluation Pipelines That Work, presented by Dat Ngo, Aman Khan, Arize. It adds practical context for how teams are building and operating AI systems in production.
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Evals 101 — Doug Guthrie, Braintrust
AI Engineer session on Evals 101, presented by Doug Guthrie, Braintrust. It adds practical context for how teams are building and operating AI systems in production.
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Events are the Wrong Abstraction for Your AI Agents - Mason Egger, Temporal.io
AI Engineer session on Events are the Wrong Abstraction for Your AI Agents - Mason Egger, Temporal.io. It adds practical context for how teams are building and operating AI systems in production.
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Excalidraw: AI and Human Whiteboarding Partnership - Christopher Chedeau
AI Engineer session on Excalidraw: AI and Human Whiteboarding Partnership - Christopher Chedeau. It adds practical context for how teams are building and operating AI systems in production.
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Forget RAG Pipelines — Build Production Ready Agents in 15 Mins: Nina Lopatina, Rajiv Shah, Contextual
AI Engineer session on Forget RAG Pipelines, presented by Build Production Ready Agents in 15 Mins: Nina Lopatina, Rajiv Shah, Contextual. It adds practical context for how teams are building and operating AI systems in production.
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Foundry Local: Cutting-Edge AI experiences on device with ONNX Runtime/Olive — Emma Ning, Microsoft
AI Engineer session on Foundry Local: Cutting-Edge AI experiences on device with ONNX Runtime/Olive, presented by Emma Ning, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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From Copilot to Colleague: Trustworthy Agents for High-Stakes - Joel Hron, CTO Thomson Reuters
AI Engineer session on From Copilot to Colleague: Trustworthy Agents for High-Stakes - Joel Hron, CTO Thomson Reuters. It adds practical context for how teams are building and operating AI systems in production.
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From Hype to Habit: How We’re Building an AI-First SaaS Company — While Still Shipping the Roadmap
AI Engineer session on From Hype to Habit: How We’re Building an AI-First SaaS Company, presented by While Still Shipping the Roadmap. It adds practical context for how teams are building and operating AI systems in production.
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From Mixture of Experts to Mixture of Agents with Super Fast Inference - Daniel Kim & Daria Soboleva
AI Engineer session on From Mixture of Experts to Mixture of Agents with Super Fast Inference - Daniel Kim & Daria Soboleva. It adds practical context for how teams are building and operating AI systems in production.
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Full Spec MCP: Hidden Capabilities of the MCP spec — Harald Kirschner, Microsoft/VSCode
AI Engineer session on Full Spec MCP: Hidden Capabilities of the MCP spec, presented by Harald Kirschner, Microsoft/VSCode. It adds practical context for how teams are building and operating AI systems in production.
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Fun stories from building OpenRouter and where all this is going - Alex Atallah, OpenRouter
AI Engineer session on Fun stories from building OpenRouter and where all this is going - Alex Atallah, OpenRouter. It adds practical context for how teams are building and operating AI systems in production.
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Good design hasn’t changed with AI — John Pham, SF Compute
AI Engineer session on Good design hasn’t changed with AI, presented by John Pham, SF Compute. It adds practical context for how teams are building and operating AI systems in production.
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Google Photos Magic Editor: GenAI Under the Hood of a Billion-User App - Kelvin Ma, Google Photos
AI Engineer session on Google Photos Magic Editor: GenAI Under the Hood of a Billion-User App - Kelvin Ma, Google Photos. It adds practical context for how teams are building and operating AI systems in production.
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Graph Intelligence: Enhance Reasoning and Retrieval Using Graph Analytics - Alison & Andreas, Neo4j
AI Engineer session on Graph Intelligence: Enhance Reasoning and Retrieval Using Graph Analytics - Alison & Andreas, Neo4j. It adds practical context for how teams are building and operating AI systems in production.
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GraphRAG methods to create optimized LLM context windows for Retrieval — Jonathan Larson, Microsoft
AI Engineer session on GraphRAG methods to create optimized LLM context windows for Retrieval, presented by Jonathan Larson, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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How agents will unlock the $500B promise of AI - Donald Hruska, Retool
AI Engineer session on How agents will unlock the $500B promise of AI - Donald Hruska, Retool. It adds practical context for how teams are building and operating AI systems in production.
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How fast are LLM inference engines anyway? — Charles Frye, Modal
AI Engineer session on How fast are LLM inference engines anyway?, presented by Charles Frye, Modal. It adds practical context for how teams are building and operating AI systems in production.
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How Intuit uses LLMs to explain taxes to millions of taxpayers - Jaspreet Singh, Intuit
AI Engineer session on How Intuit uses LLMs to explain taxes to millions of taxpayers - Jaspreet Singh, Intuit. It adds practical context for how teams are building and operating AI systems in production.
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How LLMs work for Web Devs: GPT in 600 lines of Vanilla JS - Ishan Anand
AI Engineer session on How LLMs work for Web Devs: GPT in 600 lines of Vanilla JS - Ishan Anand. It adds practical context for how teams are building and operating AI systems in production.
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How to build Enterprise Aware Agents - Chau Tran, Glean
AI Engineer session on How to build Enterprise Aware Agents - Chau Tran, Glean. It adds practical context for how teams are building and operating AI systems in production.
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How to Build Planning Agents without losing control - Yogendra Miraje, Factset
AI Engineer session on How to Build Planning Agents without losing control - Yogendra Miraje, Factset. It adds practical context for how teams are building and operating AI systems in production.
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How to build world-class AI products — Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust)
AI Engineer session on How to build world-class AI products, presented by Sarah Sachs (AI lead @ Notion) & Carlos Esteban (Braintrust). It adds practical context for how teams are building and operating AI systems in production.
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How to Hire AI Engineers when EVERYONE is cheating with AI — Beth Glenfield, DevDay
AI Engineer session on How to Hire AI Engineers when EVERYONE is cheating with AI, presented by Beth Glenfield, DevDay. It adds practical context for how teams are building and operating AI systems in production.
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How to run Evals at Scale: Thinking beyond Accuracy or Similarity — Muktesh Mishra, Adobe
AI Engineer session on How to run Evals at Scale: Thinking beyond Accuracy or Similarity, presented by Muktesh Mishra, Adobe. It adds practical context for how teams are building and operating AI systems in production.
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How to Train Your Agent: Building Reliable Agents with RL — Kyle Corbitt, OpenPipe
AI Engineer session on How to Train Your Agent: Building Reliable Agents with RL, presented by Kyle Corbitt, OpenPipe. It adds practical context for how teams are building and operating AI systems in production.
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HybridRAG: A Fusion of Graph and Vector Retrieval - Mitesh Patel, NVIDIA
AI Engineer session on HybridRAG: A Fusion of Graph and Vector Retrieval - Mitesh Patel, NVIDIA. It adds practical context for how teams are building and operating AI systems in production.
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Intro to GraphRAG — Zach Blumenfeld
AI Engineer session on Intro to GraphRAG, presented by Zach Blumenfeld. It adds practical context for how teams are building and operating AI systems in production.
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Introducing Strands Agents, an Open Source AI Agents SDK — Suman Debnath, AWS
AI Engineer session on Introducing Strands Agents, an Open Source AI Agents SDK, presented by Suman Debnath, AWS. It adds practical context for how teams are building and operating AI systems in production.
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Knowledge Graphs in Litigation Agents — Tom Smoker, WhyHow
AI Engineer session on Knowledge Graphs in Litigation Agents, presented by Tom Smoker, WhyHow. It adds practical context for how teams are building and operating AI systems in production.
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Machines of Buying and Selling Grace - Adam Behrens, New Generation
AI Engineer session on Machines of Buying and Selling Grace - Adam Behrens, New Generation. It adds practical context for how teams are building and operating AI systems in production.
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Mastering Engineering Flow with Windsurf - Eashan Sinha, Windsurf
AI Engineer session on Mastering Engineering Flow with Windsurf - Eashan Sinha, Windsurf. It adds practical context for how teams are building and operating AI systems in production.
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MCP is all you need — Samuel Colvin, Pydantic
AI Engineer session on MCP is all you need, presented by Samuel Colvin, Pydantic. It adds practical context for how teams are building and operating AI systems in production.
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MCP Is Not Good Yet — David Cramer, Sentry
AI Engineer session on MCP Is Not Good Yet, presented by David Cramer, Sentry. It adds practical context for how teams are building and operating AI systems in production.
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Measuring AGI: Interactive Reasoning Benchmarks for ARC-AGI-3 — Greg Kamradt, ARC Prize Foundation
AI Engineer session on Measuring AGI: Interactive Reasoning Benchmarks for ARC-AGI-3, presented by Greg Kamradt, ARC Prize Foundation. It adds practical context for how teams are building and operating AI systems in production.
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Memory Masterclass: Make Your AI Agents Remember What They Do! — Mark Bain, AIUS
AI Engineer session on Memory Masterclass: Make Your AI Agents Remember What They Do!, presented by Mark Bain, AIUS. It adds practical context for how teams are building and operating AI systems in production.
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Milliseconds to Magic: Real‑Time Workflows using the Gemini Live API and Pipecat
AI Engineer session on Milliseconds to Magic: Real‑Time Workflows using the Gemini Live API and Pipecat. It adds practical context for how teams are building and operating AI systems in production.
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Monetizing AI — Alvaro Morales, Orb
AI Engineer session on Monetizing AI, presented by Alvaro Morales, Orb. It adds practical context for how teams are building and operating AI systems in production.
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Netflix's Big Bet: One model to rule recommendations: Yesu Feng, Netflix
AI Engineer session on Netflix's Big Bet: One model to rule recommendations: Yesu Feng, Netflix. It adds practical context for how teams are building and operating AI systems in production.
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New York Times' Connections: A Case Study on NLP in Word Games — Shafik Quoraishee, NYT Games
AI Engineer session on New York Times' Connections: A Case Study on NLP in Word Games, presented by Shafik Quoraishee, NYT Games. It adds practical context for how teams are building and operating AI systems in production.
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On Curiosity — Sharif Shameem, Lexica
AI Engineer session on On Curiosity, presented by Sharif Shameem, Lexica. It adds practical context for how teams are building and operating AI systems in production.
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OpenThoughts: Data Recipes for Reasoning Models — Ryan Marten, Bespoke Labs
AI Engineer session on OpenThoughts: Data Recipes for Reasoning Models, presented by Ryan Marten, Bespoke Labs. It adds practical context for how teams are building and operating AI systems in production.
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Optimizing inference for voice models in production - Philip Kiely, Baseten
AI Engineer session on Optimizing inference for voice models in production - Philip Kiely, Baseten. It adds practical context for how teams are building and operating AI systems in production.
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POC to PROD: Hard Lessons from 200+ Enterprise GenAI Deployments - Randall Hunt, Caylent
AI Engineer session on POC to PROD: Hard Lessons from 200+ Enterprise GenAI Deployments - Randall Hunt, Caylent. It adds practical context for how teams are building and operating AI systems in production.
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Practical GraphRAG: Making LLMs smarter with Knowledge Graphs — Michael, Jesus, and Stephen, Neo4j
AI Engineer session on Practical GraphRAG: Making LLMs smarter with Knowledge Graphs, presented by Michael, Jesus, and Stephen, Neo4j. It adds practical context for how teams are building and operating AI systems in production.
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Production software keeps breaking and it will only get worse — Anish Agarwal, Traversal.ai
AI Engineer session on Production software keeps breaking and it will only get worse, presented by Anish Agarwal, Traversal.ai. It adds practical context for how teams are building and operating AI systems in production.
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Prompt Engineering and AI Red Teaming — Sander Schulhoff, HackAPrompt/LearnPrompting
AI Engineer session on Prompt Engineering and AI Red Teaming, presented by Sander Schulhoff, HackAPrompt/LearnPrompting. It adds practical context for how teams are building and operating AI systems in production.
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Prompt Engineering is Dead — Nir Gazit, Traceloop
AI Engineer session on Prompt Engineering is Dead, presented by Nir Gazit, Traceloop. It adds practical context for how teams are building and operating AI systems in production.
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RAG in 2025: State of the Art and the Road Forward — Tengyu Ma, MongoDB (acq. Voyage AI)
AI Engineer session on RAG in 2025: State of the Art and the Road Forward, presented by Tengyu Ma, MongoDB (acq. Voyage AI). It adds practical context for how teams are building and operating AI systems in production.
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Real world MCPs in GitHub Copilot Agent Mode — Jon Peck, Microsoft
AI Engineer session on Real world MCPs in GitHub Copilot Agent Mode, presented by Jon Peck, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Realtime Conversational Video with Pipecat and Tavus — Chad Bailey and Brian Johnson, Daily & Tavus
AI Engineer session on Realtime Conversational Video with Pipecat and Tavus, presented by Chad Bailey and Brian Johnson, Daily & Tavus. It adds practical context for how teams are building and operating AI systems in production.
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Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon
AI Engineer session on Recsys Keynote: Improving Recommendation Systems & Search in the Age of LLMs - Eugene Yan, Amazon. It adds practical context for how teams are building and operating AI systems in production.
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Rethinking Team Building: how a 30-person Startup serves 50 Million Users — Grant Lee, Gamma
AI Engineer session on Rethinking Team Building: how a 30-person Startup serves 50 Million Users, presented by Grant Lee, Gamma. It adds practical context for how teams are building and operating AI systems in production.
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Revenue Engineering: How to Price (and Reprice) Your AI Product — Kshitij Grover, Orb
AI Engineer session on Revenue Engineering: How to Price (and Reprice) Your AI Product, presented by Kshitij Grover, Orb. It adds practical context for how teams are building and operating AI systems in production.
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RL for Autonomous Coding — Aakanksha Chowdhery, Reflection.ai
AI Engineer session on RL for Autonomous Coding, presented by Aakanksha Chowdhery, Reflection.ai. It adds practical context for how teams are building and operating AI systems in production.
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Robots as professional Chefs - Nikhil Abraham, CloudChef
AI Engineer session on Robots as professional Chefs - Nikhil Abraham, CloudChef. It adds practical context for how teams are building and operating AI systems in production.
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Securing Agents with Open Standards — Bobby Tiernay and Kam Sween, Auth0
AI Engineer session on Securing Agents with Open Standards, presented by Bobby Tiernay and Kam Sween, Auth0. It adds practical context for how teams are building and operating AI systems in production.
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Serving Voice AI at Scale — Arjun Desai (Cartesia) & Rohit Talluri (AWS)
AI Engineer session on Serving Voice AI at Scale, presented by Arjun Desai (Cartesia) & Rohit Talluri (AWS). It adds practical context for how teams are building and operating AI systems in production.
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Ship it! Building Production Ready Agents — Mike Chambers, AWS
AI Engineer session on Ship it! Building Production Ready Agents, presented by Mike Chambers, AWS. It adds practical context for how teams are building and operating AI systems in production.
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Shipping an Enterprise Voice AI Agent in 100 Days - Peter Bar, Intercom Fin
AI Engineer session on Shipping an Enterprise Voice AI Agent in 100 Days - Peter Bar, Intercom Fin. It adds practical context for how teams are building and operating AI systems in production.
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Small AI Teams with Huge Impact — Vik Paruchuri, Datalab
AI Engineer session on Small AI Teams with Huge Impact, presented by Vik Paruchuri, Datalab. It adds practical context for how teams are building and operating AI systems in production.
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Stateful environments for vertical agents — Josh Purtell, Synth Labs
AI Engineer session on Stateful environments for vertical agents, presented by Josh Purtell, Synth Labs. It adds practical context for how teams are building and operating AI systems in production.
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Stop Using RAG as Memory — Daniel Chalef, Zep
AI Engineer session on Stop Using RAG as Memory, presented by Daniel Chalef, Zep. It adds practical context for how teams are building and operating AI systems in production.
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Survive the AI Knife Fight: Building Products That Win — Brian Balfour, Reforge
AI Engineer session on Survive the AI Knife Fight: Building Products That Win, presented by Brian Balfour, Reforge. It adds practical context for how teams are building and operating AI systems in production.
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Taming Rogue AI Agents with Observability-Driven Evaluation — Jim Bennett, Galileo
AI Engineer session on Taming Rogue AI Agents with Observability-Driven Evaluation, presented by Jim Bennett, Galileo. It adds practical context for how teams are building and operating AI systems in production.
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Teaching Gemini to Speak YouTube: Adapting LLMs for Video Recommendations to 2B+DAU - Devansh Tandon
AI Engineer session on Teaching Gemini to Speak YouTube: Adapting LLMs for Video Recommendations to 2B+DAU - Devansh Tandon. It adds practical context for how teams are building and operating AI systems in production.
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The Agent Awakens: Collaborative Development with Copilot - Christopher Harrison, GitHub
AI Engineer session on The Agent Awakens: Collaborative Development with Copilot - Christopher Harrison, GitHub. It adds practical context for how teams are building and operating AI systems in production.
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The Billable Hour is Dead; Long Live the Billable Hour — Kevin Madura + Mo Bhasin, Alix Partners
AI Engineer session on The Billable Hour is Dead; Long Live the Billable Hour, presented by Kevin Madura + Mo Bhasin, Alix Partners. It adds practical context for how teams are building and operating AI systems in production.
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The Bitter Layout or: How I Learned to Love the Model Picker — Maximillian Piras, Yutori
AI Engineer session on The Bitter Layout or: How I Learned to Love the Model Picker, presented by Maximillian Piras, Yutori. It adds practical context for how teams are building and operating AI systems in production.
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The Build-Operate Divide: Bridging Product Vision and AI Operational Reality
AI Engineer session on The Build-Operate Divide: Bridging Product Vision and AI Operational Reality. It adds practical context for how teams are building and operating AI systems in production.
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The emerging skillset of wielding coding agents — Beyang Liu, Sourcegraph / Amp
AI Engineer session on The emerging skillset of wielding coding agents, presented by Beyang Liu, Sourcegraph / Amp. It adds practical context for how teams are building and operating AI systems in production.
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The Eyes Are The (Context) Window to The Soul: How Windsurf Gets to Know You — Sam Fertig, Windsurf
AI Engineer session on The Eyes Are The (Context) Window to The Soul: How Windsurf Gets to Know You, presented by Sam Fertig, Windsurf. It adds practical context for how teams are building and operating AI systems in production.
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The New Code — Sean Grove, OpenAI
AI Engineer session on The New Code, presented by Sean Grove, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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The New Lean Startup — Sid Bendre, Oleve
AI Engineer session on The New Lean Startup, presented by Sid Bendre, Oleve. It adds practical context for how teams are building and operating AI systems in production.
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The rise of the agentic economy on the shoulders of MCP — Jan Curn, Apify
AI Engineer session on The rise of the agentic economy on the shoulders of MCP, presented by Jan Curn, Apify. It adds practical context for how teams are building and operating AI systems in production.
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The State of AI Powered Search and Retrieval — Frank Liu, MongoDB (prev Voyage AI)
AI Engineer session on The State of AI Powered Search and Retrieval, presented by Frank Liu, MongoDB (prev Voyage AI). It adds practical context for how teams are building and operating AI systems in production.
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The State of Generative Media - Gorkem Yurtseven, FAL
AI Engineer session on The State of Generative Media - Gorkem Yurtseven, FAL. It adds practical context for how teams are building and operating AI systems in production.
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Thinking Deeper in Gemini — Jack Rae, Google DeepMind
AI Engineer session on Thinking Deeper in Gemini, presented by Jack Rae, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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tldraw.computer - Steve Ruiz, tldraw
AI Engineer session on tldraw.computer - Steve Ruiz, tldraw. It adds practical context for how teams are building and operating AI systems in production.
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To the moon! Navigating deep context in legacy code with Augment Agent — Forrest Brazeal, Matt Ball
AI Engineer session on To the moon! Navigating deep context in legacy code with Augment Agent, presented by Forrest Brazeal, Matt Ball. It adds practical context for how teams are building and operating AI systems in production.
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Top Ten Challenges to Reach AGI — Stephen Chin, Andreas Kollegger
AI Engineer session on Top Ten Challenges to Reach AGI, presented by Stephen Chin, Andreas Kollegger. It adds practical context for how teams are building and operating AI systems in production.
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Training Agentic Reasoners — Will Brown, Prime Intellect
AI Engineer session on Training Agentic Reasoners, presented by Will Brown, Prime Intellect. It adds practical context for how teams are building and operating AI systems in production.
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Transforming search and discovery using LLMs — Tejaswi & Vinesh, Instacart
AI Engineer session on Transforming search and discovery using LLMs, presented by Tejaswi & Vinesh, Instacart. It adds practical context for how teams are building and operating AI systems in production.
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Trends Across the AI Frontier — George Cameron, ArtificialAnalysis.ai
AI Engineer session on Trends Across the AI Frontier, presented by George Cameron, ArtificialAnalysis.ai. It adds practical context for how teams are building and operating AI systems in production.
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Turning Fails into Features: Zapier’s Hard-Won Eval Lessons — Rafal Willinski, Vitor Balocco, Zapier
AI Engineer session on Turning Fails into Features: Zapier’s Hard-Won Eval Lessons, presented by Rafal Willinski, Vitor Balocco, Zapier. It adds practical context for how teams are building and operating AI systems in production.
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Unlocking AI Powered DevOps Within Your Organization — Jon Peck, GitHub
AI Engineer session on Unlocking AI Powered DevOps Within Your Organization, presented by Jon Peck, GitHub. It adds practical context for how teams are building and operating AI systems in production.
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Using OSS models to build AI apps with millions of users — Hassan El Mghari
AI Engineer session on Using OSS models to build AI apps with millions of users, presented by Hassan El Mghari. It adds practical context for how teams are building and operating AI systems in production.
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UX Design Principles for Semi Autonomous Multi Agent Systems — Victor Dibia, Microsoft
AI Engineer session on UX Design Principles for Semi Autonomous Multi Agent Systems, presented by Victor Dibia, Microsoft. It adds practical context for how teams are building and operating AI systems in production.
![Vector Search Benchmark[eting] - Philipp Krenn, Elastic video thumbnail](https://i.ytimg.com/vi/YrUBFXa1KUY/hqdefault.jpg)
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Vector Search Benchmark[eting] - Philipp Krenn, Elastic
AI Engineer session on Vector Search Benchmark[eting] - Philipp Krenn, Elastic. It adds practical context for how teams are building and operating AI systems in production.
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Vibe Coding at Scale: Customizing AI Assistants for Enterprise Environments - Harald Kirshner,
AI Engineer session on Vibe Coding at Scale: Customizing AI Assistants for Enterprise Environments - Harald Kirshner,. It adds practical context for how teams are building and operating AI systems in production.
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What every AI engineer needs to know about GPUs — Charles Frye, Modal
AI Engineer session on What every AI engineer needs to know about GPUs, presented by Charles Frye, Modal. It adds practical context for how teams are building and operating AI systems in production.
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What We Learned from Using LLMs in Pinterest — Mukuntha Narayanan, Han Wang, Pinterest
AI Engineer session on What We Learned from Using LLMs in Pinterest, presented by Mukuntha Narayanan, Han Wang, Pinterest. It adds practical context for how teams are building and operating AI systems in production.
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When Vectors Break Down: Graph-Based RAG for Dense Enterprise Knowledge - Sam Julien, Writer
AI Engineer session on When Vectors Break Down: Graph-Based RAG for Dense Enterprise Knowledge - Sam Julien, Writer. It adds practical context for how teams are building and operating AI systems in production.
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Why should anyone care about Evals? — Manu Goyal, Braintrust
AI Engineer session on Why should anyone care about Evals?, presented by Manu Goyal, Braintrust. It adds practical context for how teams are building and operating AI systems in production.
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Why Your Agent’s Brain Needs a Playbook: Practical Wins from Using Ontologies - Jesús Barrasa, Neo4j
AI Engineer session on Why Your Agent’s Brain Needs a Playbook: Practical Wins from Using Ontologies - Jesús Barrasa, Neo4j. It adds practical context for how teams are building and operating AI systems in production.
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Your Personal Open-Source Humanoid Robot for $8,999 — JX Mo, K-Scale Labs
AI Engineer session on Your Personal Open-Source Humanoid Robot for $8,999, presented by JX Mo, K-Scale Labs. It adds practical context for how teams are building and operating AI systems in production.
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How Not to Read a Headline on AI (ft. new Olympiad Gold, GPT-5 …)
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Grok 4 - 10 New Things to Know
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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7 Habits of Highly Effective Generative AI Evaluations - Justin Muller
AI Engineer session on 7 Habits of Highly Effective Generative AI Evaluations - Justin Muller. It adds practical context for how teams are building and operating AI systems in production.
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Agentic Enterprise - What your CEO must know about AI - Hubert Misztela
AI Engineer session on Agentic Enterprise - What your CEO must know about AI - Hubert Misztela. It adds practical context for how teams are building and operating AI systems in production.
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Agents reported thousands of bugs, how many were real? - Ian Butler and Nick Gregory
AI Engineer session on Agents reported thousands of bugs, how many were real? - Ian Butler and Nick Gregory. It adds practical context for how teams are building and operating AI systems in production.
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Analyzing 10,000 Sales Calls With AI In 2 Weeks — Charlie Guo
AI Engineer session on Analyzing 10,000 Sales Calls With AI In 2 Weeks, presented by Charlie Guo. It adds practical context for how teams are building and operating AI systems in production.
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Are MCPs Overhyped? A Rant about MCPs — Henry Mao, Smithery
AI Engineer session on Are MCPs Overhyped? A Rant about MCPs, presented by Henry Mao, Smithery. It adds practical context for how teams are building and operating AI systems in production.
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Arrakis: How To Build An AI Sandbox From Scratch - Abhishek Bhardwaj, OpenAI
AI Engineer session on Arrakis: How To Build An AI Sandbox From Scratch - Abhishek Bhardwaj, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Beyond Conversation: Why Documents Transform Natural Language into Code - Filip Kozera
AI Engineer session on Beyond Conversation: Why Documents Transform Natural Language into Code - Filip Kozera. It adds practical context for how teams are building and operating AI systems in production.
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Blender MCP and The Future Of Creative Tools - Siddharth Ahuja
AI Engineer session on Blender MCP and The Future Of Creative Tools - Siddharth Ahuja. It adds practical context for how teams are building and operating AI systems in production.
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Break It 'Til You Make It: Building the Self-Improving Stack for AI Agents - Aparna Dhinakaran
AI Engineer session on Break It 'Til You Make It: Building the Self-Improving Stack for AI Agents - Aparna Dhinakaran. It adds practical context for how teams are building and operating AI systems in production.
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Breaking the Chain: Agent Continuations for Resumable AI Workflows - Greg Benson
AI Engineer session on Breaking the Chain: Agent Continuations for Resumable AI Workflows - Greg Benson. It adds practical context for how teams are building and operating AI systems in production.
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Building Agents with Amazon Nova Act and MCP - Du'An Lightfoot, Amazon (Full Workshop)
AI Engineer session on Building Agents with Amazon Nova Act and MCP - Du'An Lightfoot, Amazon (Full Workshop). It adds practical context for how teams are building and operating AI systems in production.
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Building AI Agents that actually automate Knowledge Work - Jerry Liu, LlamaIndex
AI Engineer session on Building AI Agents that actually automate Knowledge Work - Jerry Liu, LlamaIndex. It adds practical context for how teams are building and operating AI systems in production.
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Building Protected MCP Servers — Den Delimarsky and Julia Kasper, MCP Steering Committee & Microsoft
AI Engineer session on Building Protected MCP Servers, presented by Den Delimarsky and Julia Kasper, MCP Steering Committee & Microsoft. It adds practical context for how teams are building and operating AI systems in production.
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Building Reliable Support Agents Using the Effect Typescript Library - Michael Fester
AI Engineer session on Building Reliable Support Agents Using the Effect Typescript Library - Michael Fester. It adds practical context for how teams are building and operating AI systems in production.
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Buy Now, Maybe Pay Later: Dealing with Prompt-Tax While Staying at the Frontier - Andrew Thomspson
AI Engineer session on Buy Now, Maybe Pay Later: Dealing with Prompt-Tax While Staying at the Frontier - Andrew Thomspson. It adds practical context for how teams are building and operating AI systems in production.
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Case Study + Deep Dive: Telemedicine Support Agents with LangGraph/MCP - Dan Mason
AI Engineer session on Case Study + Deep Dive: Telemedicine Support Agents with LangGraph/MCP - Dan Mason. It adds practical context for how teams are building and operating AI systems in production.
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ChatGPT is poorly designed. So I fixed it
AI Engineer session on ChatGPT is poorly designed. So I fixed it. It adds practical context for how teams are building and operating AI systems in production.
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Cognitive Shield Real Time Real Smart - Rachna Srivastava
AI Engineer session on Cognitive Shield Real Time Real Smart - Rachna Srivastava. It adds practical context for how teams are building and operating AI systems in production.
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Designing AI To Scale Human Thought — Jun Yu Tan, Tusk
AI Engineer session on Designing AI To Scale Human Thought, presented by Jun Yu Tan, Tusk. It adds practical context for how teams are building and operating AI systems in production.
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Effective AI Agents Need Data Flywheels, Not The Next Biggest LLM — Sylendran Arunagiri, NVIDIA
AI Engineer session on Effective AI Agents Need Data Flywheels, Not The Next Biggest LLM, presented by Sylendran Arunagiri, NVIDIA. It adds practical context for how teams are building and operating AI systems in production.
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Exposing Agents as MCP servers with mcp-agent: Sarmad Qadri
AI Engineer session on Exposing Agents as MCP servers with mcp-agent: Sarmad Qadri. It adds practical context for how teams are building and operating AI systems in production.
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From PM at Stripe to Building an AI startup, a recent founder's journey - Mounir Mouawad
AI Engineer session on From PM at Stripe to Building an AI startup, a recent founder's journey - Mounir Mouawad. It adds practical context for how teams are building and operating AI systems in production.
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GPU-less, Trust-less, Limit-less: Reimagining the Confidential AI Cloud - Mike Bursell
AI Engineer session on GPU-less, Trust-less, Limit-less: Reimagining the Confidential AI Cloud - Mike Bursell. It adds practical context for how teams are building and operating AI systems in production.
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Grounded Reasoning Systems for Cloud Architecture - Iman Makaremi
AI Engineer session on Grounded Reasoning Systems for Cloud Architecture - Iman Makaremi. It adds practical context for how teams are building and operating AI systems in production.
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How agents broke app-level infrastructure - Evan Boyle
AI Engineer session on How agents broke app-level infrastructure - Evan Boyle. It adds practical context for how teams are building and operating AI systems in production.
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How to Build Trustworthy AI — Allie Howe
AI Engineer session on How to Build Trustworthy AI, presented by Allie Howe. It adds practical context for how teams are building and operating AI systems in production.
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Invisible Users, Invisible Interfaces: Accelerating Design Iteration with AI Simulation - Alex Liss
AI Engineer session on Invisible Users, Invisible Interfaces: Accelerating Design Iteration with AI Simulation - Alex Liss. It adds practical context for how teams are building and operating AI systems in production.
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Just do it. (let your tools think for themselves) - Robert Chandler
AI Engineer session on Just do it. (let your tools think for themselves) - Robert Chandler. It adds practical context for how teams are building and operating AI systems in production.
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Letting AI Interface with your App with MCP — Kent C Dodds
AI Engineer session on Letting AI Interface with your App with MCP, presented by Kent C Dodds. It adds practical context for how teams are building and operating AI systems in production.
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Luminal - Search-Based Deep Learning Compilers - Joe Fioti
AI Engineer session on Luminal - Search-Based Deep Learning Compilers - Joe Fioti. It adds practical context for how teams are building and operating AI systems in production.
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MCP Agent Fine tuning Workshop - Ronan McGovern
AI Engineer session on MCP Agent Fine tuning Workshop - Ronan McGovern. It adds practical context for how teams are building and operating AI systems in production.
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MCP: Origins and Requests For Startups — Theodora Chu, Model Context Protocol PM, Anthropic
AI Engineer session on MCP: Origins and Requests For Startups, presented by Theodora Chu, Model Context Protocol PM, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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MCPs are Boring (or: Why we are losing the Sparkle of LLMs) - Manuel Odendahl
AI Engineer session on MCPs are Boring (or: Why we are losing the Sparkle of LLMs) - Manuel Odendahl. It adds practical context for how teams are building and operating AI systems in production.
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My AI Thinks I'm Eating My Feelings (and Other Nutritional Insights) - Rami Alhamad
AI Engineer session on My AI Thinks I'm Eating My Feelings (and Other Nutritional Insights) - Rami Alhamad. It adds practical context for how teams are building and operating AI systems in production.
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open-rag-eval: RAG Evaluation without "golden" answers — Ofer Mendelevitch, Vectara
AI Engineer session on open-rag-eval: RAG Evaluation without "golden" answers, presented by Ofer Mendelevitch, Vectara. It adds practical context for how teams are building and operating AI systems in production.
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RAG Evaluation Is Broken! Here's Why (And How to Fix It) - Yuval Belfer and Niv Granot
AI Engineer session on RAG Evaluation Is Broken! Here's Why (And How to Fix It) - Yuval Belfer and Niv Granot. It adds practical context for how teams are building and operating AI systems in production.
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Real AI Agents Need Planning, Not Just Prompting - Yuval Belfer
AI Engineer session on Real AI Agents Need Planning, Not Just Prompting - Yuval Belfer. It adds practical context for how teams are building and operating AI systems in production.
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Remote MCPs: What we learned from shipping — John Welsh, Anthropic
AI Engineer session on Remote MCPs: What we learned from shipping, presented by John Welsh, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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RFT, DPO, SFT: Fine-tuning with OpenAI — Ilan Bigio, OpenAI
AI Engineer session on RFT, DPO, SFT: Fine-tuning with OpenAI, presented by Ilan Bigio, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Rust is the language of the AGI - Michael Yuan
AI Engineer session on Rust is the language of the AGI - Michael Yuan. It adds practical context for how teams are building and operating AI systems in production.
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Stop Ordering AI Takeout A Cookbook for Winning When You Build In House - Jan Siml
AI Engineer session on Stop Ordering AI Takeout A Cookbook for Winning When You Build In House - Jan Siml. It adds practical context for how teams are building and operating AI systems in production.
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Supercharging developer workflow with Amazon Q Developer - Vikash Agrawal
AI Engineer session on Supercharging developer workflow with Amazon Q Developer - Vikash Agrawal. It adds practical context for how teams are building and operating AI systems in production.
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Text-to-Speech Data Preparation and Fine-tuning Workshop - Ronan McGovern
AI Engineer session on Text-to-Speech Data Preparation and Fine-tuning Workshop - Ronan McGovern. It adds practical context for how teams are building and operating AI systems in production.
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The 4 Patterns of AI Native Development — Patrick Debois
AI Engineer session on The 4 Patterns of AI Native Development, presented by Patrick Debois. It adds practical context for how teams are building and operating AI systems in production.
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The Agent Native Company — Rick Blalock, Agentuity
AI Engineer session on The Agent Native Company, presented by Rick Blalock, Agentuity. It adds practical context for how teams are building and operating AI systems in production.
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The Benchmarks Game: Why It's Rigged and How You Can (Really) Win - Darius Emrani
AI Engineer session on The Benchmarks Game: Why It's Rigged and How You Can (Really) Win - Darius Emrani. It adds practical context for how teams are building and operating AI systems in production.
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The Coherence Trap: Why LLMs Feel Smart (But Aren’t Thinking) - Travis Frisinger
AI Engineer session on The Coherence Trap: Why LLMs Feel Smart (But Aren’t Thinking) - Travis Frisinger. It adds practical context for how teams are building and operating AI systems in production.
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The Current State of Browser Agents - Jerry Wu and Wyatt Marshall
AI Engineer session on The Current State of Browser Agents - Jerry Wu and Wyatt Marshall. It adds practical context for how teams are building and operating AI systems in production.
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The Demo I Wish I'd Had: OpenAI's Agents SDK... serverless! - Brook Riggio
AI Engineer session on The Demo I Wish I'd Had: OpenAI's Agents SDK... serverless! - Brook Riggio. It adds practical context for how teams are building and operating AI systems in production.
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The End of Awkward AI Transcriptions - Travis Bartley and Myungjong Kim
AI Engineer session on The End of Awkward AI Transcriptions - Travis Bartley and Myungjong Kim. It adds practical context for how teams are building and operating AI systems in production.
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The Future of Qwen: A Generalist Agent Model — Junyang Lin, Alibaba Qwen
AI Engineer session on The Future of Qwen: A Generalist Agent Model, presented by Junyang Lin, Alibaba Qwen. It adds practical context for how teams are building and operating AI systems in production.
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The Geopolitics of AI Infrastructure - Dylan Patel, SemiAnalysis
AI Engineer session on The Geopolitics of AI Infrastructure - Dylan Patel, SemiAnalysis. It adds practical context for how teams are building and operating AI systems in production.
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The Knowledge Graph Mullet: Trimming GraphRAG Complexity - William Lyon
AI Engineer session on The Knowledge Graph Mullet: Trimming GraphRAG Complexity - William Lyon. It adds practical context for how teams are building and operating AI systems in production.
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The Many Ends of Programming - Ray Myers
AI Engineer session on The Many Ends of Programming - Ray Myers. It adds practical context for how teams are building and operating AI systems in production.
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The RAG Stack We Landed On After 37 Fails - Jonathan Fernandes
AI Engineer session on The RAG Stack We Landed On After 37 Fails - Jonathan Fernandes. It adds practical context for how teams are building and operating AI systems in production.
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The Robots are coming for your job, and that's okay - Elmer Thomas and Maria Bermudez
AI Engineer session on The Robots are coming for your job, and that's okay - Elmer Thomas and Maria Bermudez. It adds practical context for how teams are building and operating AI systems in production.
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The State of MCP observability: Observable.tools — Alex Volkov and Benjamin Eckel, W&B and Dylibso
AI Engineer session on The State of MCP observability: Observable.tools, presented by Alex Volkov and Benjamin Eckel, W&B and Dylibso. It adds practical context for how teams are building and operating AI systems in production.
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The Voice-First AI Overlay: Designing Conversational Co-Pilots - Gregory Bruss
AI Engineer session on The Voice-First AI Overlay: Designing Conversational Co-Pilots - Gregory Bruss. It adds practical context for how teams are building and operating AI systems in production.
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The Web Browser Is All You Need - Paul Klein IV, Browserbase
AI Engineer session on The Web Browser Is All You Need - Paul Klein IV, Browserbase. It adds practical context for how teams are building and operating AI systems in production.
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Unlocking Africa's Potential with AI — Thabang Ledwaba
AI Engineer session on Unlocking Africa's Potential with AI, presented by Thabang Ledwaba. It adds practical context for how teams are building and operating AI systems in production.
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Veo 3 for Developers — Paige Bailey, Google DeepMind
AI Engineer session on Veo 3 for Developers, presented by Paige Bailey, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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When Will AI Models Blackmail You, and Why?
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Why Bolt.new Won and Most DevTools AI Pivots Failed - Victoria Melnikova
AI Engineer session on Why Bolt.new Won and Most DevTools AI Pivots Failed - Victoria Melnikova. It adds practical context for how teams are building and operating AI systems in production.
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Why the Best AI Agents Are Built Without Frameworks (Primitives over Frameworks) — Ahmad Awais, CHAI
AI Engineer session on Why the Best AI Agents Are Built Without Frameworks (Primitives over Frameworks), presented by Ahmad Awais, CHAI. It adds practical context for how teams are building and operating AI systems in production.
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Will Agent evaluation via MCP Stabilize Agent Networks? - Ari Heljakka
AI Engineer session on Will Agent evaluation via MCP Stabilize Agent Networks? - Ari Heljakka. It adds practical context for how teams are building and operating AI systems in production.
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Windsurf everywhere, doing everything, all at once - Kevin Hou, Windsurf
AI Engineer session on Windsurf everywhere, doing everything, all at once - Kevin Hou, Windsurf. It adds practical context for how teams are building and operating AI systems in production.
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Apple’s ‘AI Can’t Reason’ Claim Seen By 13M+, What You Need to Know
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Cloud CISO Perspectives: How Google secures AI Agents
Google’s CISO perspective on why agents need a new security paradigm and what changes when models can observe, plan, and act.
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AI Accelerates: New Gemini Model + AI Unemployment Stories Analysed
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Creating Agents that Co-Create — Karina Nguyen, OpenAI
AI Engineer session on Creating Agents that Co-Create, presented by Karina Nguyen, OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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How to Build Your Own AI Data Center in 2025 — Paul Gilbert, Arista Networks
AI Engineer session on How to Build Your Own AI Data Center in 2025, presented by Paul Gilbert, Arista Networks. It adds practical context for how teams are building and operating AI systems in production.
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Claude 4: Full 120 Page Breakdown … Is it the Best New Model?
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Google Takes No Prisoners Amid Torrent of AI Announcements
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Improves at Self-improving
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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"OpenAI is Not God” - The DeepSeek Documentary on Liang Wenfeng, R1 and What's Next
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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o3 breaks (some) records, but AI becomes pay-to-win
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
![[Full Workshop from Microsoft] Github Copilot - The World's Most Widely Adopted AI Developer Tool video thumbnail](https://i.ytimg.com/vi/sKiTUuEV1rw/hqdefault.jpg)
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[Full Workshop from Microsoft] Github Copilot - The World's Most Widely Adopted AI Developer Tool
AI Engineer session on [Full Workshop from Microsoft] Github Copilot - The World's Most Widely Adopted AI Developer Tool. It adds practical context for how teams are building and operating AI systems in production.
![[Full Workshop] How to add secure code interpreting in your AI app: Vasek Mlejnsky video thumbnail](https://i.ytimg.com/vi/k0VIgKAUkP4/hqdefault.jpg)
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[Full Workshop] How to add secure code interpreting in your AI app: Vasek Mlejnsky
AI Engineer session on [Full Workshop] How to add secure code interpreting in your AI app: Vasek Mlejnsky. It adds practical context for how teams are building and operating AI systems in production.
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[Full Workshop] Llama 3 at 1,000 tok/s on the SambaNova AI Platform
AI Engineer session on [Full Workshop] Llama 3 at 1,000 tok/s on the SambaNova AI Platform. It adds practical context for how teams are building and operating AI systems in production.
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10x Development: LLMs For the working Programmer - Manuel Odendahl
AI Engineer session on 10x Development: LLMs For the working Programmer - Manuel Odendahl. It adds practical context for how teams are building and operating AI systems in production.
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A Practical Guide to Efficient AI: Shelby Heinecke
AI Engineer session on A Practical Guide to Efficient AI: Shelby Heinecke. It adds practical context for how teams are building and operating AI systems in production.
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Accelerate your AI journey with Azure AI model catalog: Sharmila Chokalingam
AI Engineer session on Accelerate your AI journey with Azure AI model catalog: Sharmila Chokalingam. It adds practical context for how teams are building and operating AI systems in production.
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Accelerating Mixture of Experts Training With Rail Optimized InfiniBand Networking in Crusoe Cloud
AI Engineer session on Accelerating Mixture of Experts Training With Rail Optimized InfiniBand Networking in Crusoe Cloud. It adds practical context for how teams are building and operating AI systems in production.
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Agent Evals: Finally, With The Map
AI Engineer session on Agent Evals: Finally, With The Map. It adds practical context for how teams are building and operating AI systems in production.
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Agentic Workflows on Vertex AI: Rukma Sen
AI Engineer session on Agentic Workflows on Vertex AI: Rukma Sen. It adds practical context for how teams are building and operating AI systems in production.
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AI + Security & Safety — Don Bosco Durai
AI Engineer session on AI + Security & Safety, presented by Don Bosco Durai. It adds practical context for how teams are building and operating AI systems in production.
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AI Agents, Meet Test Driven Development
AI Engineer session on AI Agents, Meet Test Driven Development. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineering at Jane Street - John Crepezzi
AI Engineer session on AI Engineering at Jane Street - John Crepezzi. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineering Without Borders — swyx
AI Engineer session on AI Engineering Without Borders, presented by swyx. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineers: The Next Generation — Stefania Druga, Google Gemini
AI Engineer session on AI Engineers: The Next Generation, presented by Stefania Druga, Google Gemini. It adds practical context for how teams are building and operating AI systems in production.
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AI Frontiers in Trust and Safety Combatting Multifaceted Harm on Tinder at Scale: Vibhor Kumar
AI Engineer session on AI Frontiers in Trust and Safety Combatting Multifaceted Harm on Tinder at Scale: Vibhor Kumar. It adds practical context for how teams are building and operating AI systems in production.
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AI Music Generation, From Prompt to Production: Phlo Young
AI Engineer session on AI Music Generation, From Prompt to Production: Phlo Young. It adds practical context for how teams are building and operating AI systems in production.
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AI Platform Engineering: Patrick Debois
AI Engineer session on AI Platform Engineering: Patrick Debois. It adds practical context for how teams are building and operating AI systems in production.
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AI Templates: Gabriela and Aishwarya
AI Engineer session on AI Templates: Gabriela and Aishwarya. It adds practical context for how teams are building and operating AI systems in production.
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Anchoring Enterprise GenAI with Knowledge Graphs: Jonathan Lowe (Pfizer), Stephen Chin (Neo4j)
AI Engineer session on Anchoring Enterprise GenAI with Knowledge Graphs: Jonathan Lowe (Pfizer), Stephen Chin (Neo4j). It adds practical context for how teams are building and operating AI systems in production.
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Anthropic in the Enterprise — Alexander Bricken & Joe Bayley
AI Engineer session on Anthropic in the Enterprise, presented by Alexander Bricken & Joe Bayley. It adds practical context for how teams are building and operating AI systems in production.
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Architecting and Testing Controllable Agents: Lance Martin
AI Engineer session on Architecting and Testing Controllable Agents: Lance Martin. It adds practical context for how teams are building and operating AI systems in production.
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Best Practices for Evaluating Large Language Model Applications with llmeval: Niklas Nielsen
AI Engineer session on Best Practices for Evaluating Large Language Model Applications with llmeval: Niklas Nielsen. It adds practical context for how teams are building and operating AI systems in production.
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Beyond APIs: How AI Web Agents Are Automating the "Long Tail" of Knowledge Work
AI Engineer session on Beyond APIs: How AI Web Agents Are Automating the "Long Tail" of Knowledge Work. It adds practical context for how teams are building and operating AI systems in production.
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BotDojo Launch: Enhancing AI Assistants with Evaluations and Synthetic Data
AI Engineer session on BotDojo Launch: Enhancing AI Assistants with Evaluations and Synthetic Data. It adds practical context for how teams are building and operating AI systems in production.
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Breaking AI's 1-GHz Barrier: Sunny Madra (Groq)
AI Engineer session on Breaking AI's 1-GHz Barrier: Sunny Madra (Groq). It adds practical context for how teams are building and operating AI systems in production.
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Build an AI Research Agent: Apoorva Joshi
AI Engineer session on Build an AI Research Agent: Apoorva Joshi. It adds practical context for how teams are building and operating AI systems in production.
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Build enterprise generative AI apps using Llama 3 at 1,000 tokens/s on the SambaNova AI platform
AI Engineer session on Build enterprise generative AI apps using Llama 3 at 1,000 tokens/s on the SambaNova AI platform. It adds practical context for how teams are building and operating AI systems in production.
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Build, Evaluate and Deploy a RAG-Based Retail Copilot with Azure AI: Cedric Vidal and David Smith
AI Engineer session on Build, Evaluate and Deploy a RAG-Based Retail Copilot with Azure AI: Cedric Vidal and David Smith. It adds practical context for how teams are building and operating AI systems in production.
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Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic
AI Engineer session on Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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Building AI Agents with Real ROI in the Enterprise SDLC: Bruno (Booking.com) & Beyang (Sourcegraph)
AI Engineer session on Building AI Agents with Real ROI in the Enterprise SDLC: Bruno (Booking.com) & Beyang (Sourcegraph). It adds practical context for how teams are building and operating AI systems in production.
![Building an AI assistant that makes phone calls [Convex Workshop] video thumbnail](https://i.ytimg.com/vi/idDnpGqJd80/hqdefault.jpg)
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Building an AI assistant that makes phone calls [Convex Workshop]
AI Engineer session on Building an AI assistant that makes phone calls [Convex Workshop]. It adds practical context for how teams are building and operating AI systems in production.
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Building and evaluating AI Agents — Sayash Kapoor, AI Snake Oil
AI Engineer session on Building and evaluating AI Agents, presented by Sayash Kapoor, AI Snake Oil. It adds practical context for how teams are building and operating AI systems in production.
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Building and Scaling an AI Agent Swarm of low latency real time voice bots: Damien Murphy
AI Engineer session on Building and Scaling an AI Agent Swarm of low latency real time voice bots: Damien Murphy. It adds practical context for how teams are building and operating AI systems in production.
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Building efficient hybrid context query for LLM grounding: Simrat Hanspal
AI Engineer session on Building efficient hybrid context query for LLM grounding: Simrat Hanspal. It adds practical context for how teams are building and operating AI systems in production.
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Building LinkedIn's GenAI Platform — Xiaofeng Wang
AI Engineer session on Building LinkedIn's GenAI Platform, presented by Xiaofeng Wang. It adds practical context for how teams are building and operating AI systems in production.
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Building Multi agent Systems with Finite State Machines
AI Engineer session on Building Multi agent Systems with Finite State Machines. It adds practical context for how teams are building and operating AI systems in production.
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Building Reliable Agentic Systems: Eno Reyes
AI Engineer session on Building Reliable Agentic Systems: Eno Reyes. It adds practical context for how teams are building and operating AI systems in production.
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Building security around ML: Dr. Andrew Davis
AI Engineer session on Building security around ML: Dr. Andrew Davis. It adds practical context for how teams are building and operating AI systems in production.
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Building State of the Art Open Weights Tool Use: The Command R Family: Sandra Kublik
AI Engineer session on Building State of the Art Open Weights Tool Use: The Command R Family: Sandra Kublik. It adds practical context for how teams are building and operating AI systems in production.
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Building with Anthropic Claude: Prompt Workshop with Zack Witten
AI Engineer session on Building with Anthropic Claude: Prompt Workshop with Zack Witten. It adds practical context for how teams are building and operating AI systems in production.
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Claude plays Minecraft!
AI Engineer session on Claude plays Minecraft!. It adds practical context for how teams are building and operating AI systems in production.
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Code Generation and Maintenance at Scale: Morgante Pell
AI Engineer session on Code Generation and Maintenance at Scale: Morgante Pell. It adds practical context for how teams are building and operating AI systems in production.
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Cohere for VPs of AI: Vivek Muppalla
AI Engineer session on Cohere for VPs of AI: Vivek Muppalla. It adds practical context for how teams are building and operating AI systems in production.
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Cohere: Building enterprise LLM agents that work (Shaan Desai)
AI Engineer session on Cohere: Building enterprise LLM agents that work (Shaan Desai). It adds practical context for how teams are building and operating AI systems in production.
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Cooking with fire without burning down the kitchen: Dominik Kundel
AI Engineer session on Cooking with fire without burning down the kitchen: Dominik Kundel. It adds practical context for how teams are building and operating AI systems in production.
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Copilots Everywhere: Thomas Dohmke and Eugene Yan
AI Engineer session on Copilots Everywhere: Thomas Dohmke and Eugene Yan. It adds practical context for how teams are building and operating AI systems in production.
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Creating and scaling your own custom copilots with Azure AI Studio: Hanchi Wang
AI Engineer session on Creating and scaling your own custom copilots with Azure AI Studio: Hanchi Wang. It adds practical context for how teams are building and operating AI systems in production.
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Customized, production ready inference with open source models: Dmytro (Dima) Dzhulgakov
AI Engineer session on Customized, production ready inference with open source models: Dmytro (Dima) Dzhulgakov. It adds practical context for how teams are building and operating AI systems in production.
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Decoding Mistral AI's Large Language Models: Devendra Chaplot
AI Engineer session on Decoding Mistral AI's Large Language Models: Devendra Chaplot. It adds practical context for how teams are building and operating AI systems in production.
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Decoding the Decoder LLM without de code: Ishan Anand
AI Engineer session on Decoding the Decoder LLM without de code: Ishan Anand. It adds practical context for how teams are building and operating AI systems in production.
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Disrupting the $15 Trillion Construction Industry with Autonomous Agents: Dr. Sarah Buchner
AI Engineer session on Disrupting the $15 Trillion Construction Industry with Autonomous Agents: Dr. Sarah Buchner. It adds practical context for how teams are building and operating AI systems in production.
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Don't just slap on a chatbot: building AI that works before you ask
AI Engineer session on Don't just slap on a chatbot: building AI that works before you ask. It adds practical context for how teams are building and operating AI systems in production.
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E-Values Evaluating the Values of AI: Sheila Gulati and Nischal Nadhamuni
AI Engineer session on E-Values Evaluating the Values of AI: Sheila Gulati and Nischal Nadhamuni. It adds practical context for how teams are building and operating AI systems in production.
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Emergence Launch: AI Agents and the future enterprise: Dr. Satya Nitta
AI Engineer session on Emergence Launch: AI Agents and the future enterprise: Dr. Satya Nitta. It adds practical context for how teams are building and operating AI systems in production.
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Enhancing Quality and Security in CI: Gunjan Patel
AI Engineer session on Enhancing Quality and Security in CI: Gunjan Patel. It adds practical context for how teams are building and operating AI systems in production.
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Ensure AI Agents Work: Evaluation Frameworks for Scaling Success — Aparna Dhinkaran, CEO Arize
AI Engineer session on Ensure AI Agents Work: Evaluation Frameworks for Scaling Success, presented by Aparna Dhinkaran, CEO Arize. It adds practical context for how teams are building and operating AI systems in production.
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Evaluating Domain Specific LLMs for Real World Finance — Waseem Alshikh, Writer
AI Engineer session on Evaluating Domain Specific LLMs for Real World Finance, presented by Waseem Alshikh, Writer. It adds practical context for how teams are building and operating AI systems in production.
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Everything you need to know about Fine-tuning and Merging LLMs: Maxime Labonne
AI Engineer session on Everything you need to know about Fine-tuning and Merging LLMs: Maxime Labonne. It adds practical context for how teams are building and operating AI systems in production.
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EyeLevel Launch: Your RAG is Tripping, Here's the Real Reason Why
AI Engineer session on EyeLevel Launch: Your RAG is Tripping, Here's the Real Reason Why. It adds practical context for how teams are building and operating AI systems in production.
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Fine tune 20 Llama Models in 5 Minutes: Santosh Radha
AI Engineer session on Fine tune 20 Llama Models in 5 Minutes: Santosh Radha. It adds practical context for how teams are building and operating AI systems in production.
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Finetuning: 500m AI agents in production with 2 engineers — Mustafa Ali & Kyle Corbitt
AI Engineer session on Finetuning: 500m AI agents in production with 2 engineers, presented by Mustafa Ali & Kyle Corbitt. It adds practical context for how teams are building and operating AI systems in production.
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Fixing bugs in Gemma, Llama, & Phi 3: Daniel Han
AI Engineer session on Fixing bugs in Gemma, Llama, & Phi 3: Daniel Han. It adds practical context for how teams are building and operating AI systems in production.
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From model weights to API endpoint with TensorRT LLM: Philip Kiely and Pankaj Gupta
AI Engineer session on From model weights to API endpoint with TensorRT LLM: Philip Kiely and Pankaj Gupta. It adds practical context for how teams are building and operating AI systems in production.
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From Software Developer to AI Engineer: Antje Barth
AI Engineer session on From Software Developer to AI Engineer: Antje Barth. It adds practical context for how teams are building and operating AI systems in production.
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From Text to Vision to Voice Exploring Multimodality with Open AI: Romain Huet
AI Engineer session on From Text to Vision to Voice Exploring Multimodality with Open AI: Romain Huet. It adds practical context for how teams are building and operating AI systems in production.
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Frontier Feud: Anthropic, Google DeepMind, Meta FAIR, Thinking Machines — Barr Yaron, Amplify
AI Engineer session on Frontier Feud: Anthropic, Google DeepMind, Meta FAIR, Thinking Machines, presented by Barr Yaron, Amplify. It adds practical context for how teams are building and operating AI systems in production.
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Function Calling is All You Need — Full Workshop, with Ilan Bigio of OpenAI
AI Engineer session on Function Calling is All You Need, presented by Full Workshop, with Ilan Bigio of OpenAI. It adds practical context for how teams are building and operating AI systems in production.
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Git push get an AI API: Ryan Fox-Tyler
AI Engineer session on Git push get an AI API: Ryan Fox-Tyler. It adds practical context for how teams are building and operating AI systems in production.
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GitHub Copilot: The World's Most Widely Adopted AI Developer Tool
AI Engineer session on GitHub Copilot: The World's Most Widely Adopted AI Developer Tool. It adds practical context for how teams are building and operating AI systems in production.
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GitHub Next Explorations: Rahul Pandita
AI Engineer session on GitHub Next Explorations: Rahul Pandita. It adds practical context for how teams are building and operating AI systems in production.
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GitHub's AI Powered Security Platform: Sarah Khalife
AI Engineer session on GitHub's AI Powered Security Platform: Sarah Khalife. It adds practical context for how teams are building and operating AI systems in production.
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Giving a Voice to AI Agents: Scott Stephenson, CEO, Deepgram
AI Engineer session on Giving a Voice to AI Agents: Scott Stephenson, CEO, Deepgram. It adds practical context for how teams are building and operating AI systems in production.
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Going beyond RAG: Extended Mind Transformers - Phoebe Klett
AI Engineer session on Going beyond RAG: Extended Mind Transformers - Phoebe Klett. It adds practical context for how teams are building and operating AI systems in production.
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GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem
AI Engineer session on GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem. It adds practical context for how teams are building and operating AI systems in production.
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Hiring & Building an AI Engineering Team: Dr. Bryan Bischof
AI Engineer session on Hiring & Building an AI Engineering Team: Dr. Bryan Bischof. It adds practical context for how teams are building and operating AI systems in production.
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How Codeium Breaks Through the Ceiling for Retrieval: Kevin Hou
AI Engineer session on How Codeium Breaks Through the Ceiling for Retrieval: Kevin Hou. It adds practical context for how teams are building and operating AI systems in production.
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How Coding Agents change Software Development Forever - Hailong Zhang
AI Engineer session on How Coding Agents change Software Development Forever - Hailong Zhang. It adds practical context for how teams are building and operating AI systems in production.
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How Deep Research Works - Mukund Sridhar & Aarush Selvan, Google DeepMind
AI Engineer session on How Deep Research Works - Mukund Sridhar & Aarush Selvan, Google DeepMind. It adds practical context for how teams are building and operating AI systems in production.
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How to build the world's fastest voice bot: Kwindla Hultman Kramer
AI Engineer session on How to build the world's fastest voice bot: Kwindla Hultman Kramer. It adds practical context for how teams are building and operating AI systems in production.
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How to Construct Domain Specific LLM Evaluation Systems: Hamel Husain and Emil Sedgh
AI Engineer session on How to Construct Domain Specific LLM Evaluation Systems: Hamel Husain and Emil Sedgh. It adds practical context for how teams are building and operating AI systems in production.
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How to evaluate a model for your use case: Emmanuel Turlay
AI Engineer session on How to evaluate a model for your use case: Emmanuel Turlay. It adds practical context for how teams are building and operating AI systems in production.
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How to Fail at AI Strategy: Hamel Husain & Greg Ceccarelli
AI Engineer session on How to Fail at AI Strategy: Hamel Husain & Greg Ceccarelli. It adds practical context for how teams are building and operating AI systems in production.
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How to Improve Your Agents: Academic Lit Review
AI Engineer session on How to Improve Your Agents: Academic Lit Review. It adds practical context for how teams are building and operating AI systems in production.
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How We Build Effective Agents: Barry Zhang, Anthropic
AI Engineer session on How We Build Effective Agents: Barry Zhang, Anthropic. It adds practical context for how teams are building and operating AI systems in production.
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How Windsurf writes 90% of your code with an Agentic IDE - Kevin Hou, Windsurf
AI Engineer session on How Windsurf writes 90% of your code with an Agentic IDE - Kevin Hou, Windsurf. It adds practical context for how teams are building and operating AI systems in production.
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How Zapier Builds AI Products and Features with the Help of Braintrust: Ankur Goyal & Olmo Maldonado
AI Engineer session on How Zapier Builds AI Products and Features with the Help of Braintrust: Ankur Goyal & Olmo Maldonado. It adds practical context for how teams are building and operating AI systems in production.
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Hypermode Launch: Kevin Van Gundy
AI Engineer session on Hypermode Launch: Kevin Van Gundy. It adds practical context for how teams are building and operating AI systems in production.
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Hyperspace More Nodes Is All You Need: Nicolas Schlaepfer
AI Engineer session on Hyperspace More Nodes Is All You Need: Nicolas Schlaepfer. It adds practical context for how teams are building and operating AI systems in production.
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Insights from Snorkel AI running Azure AI Infrastructure: Humza Iqbal and Lachlan Ainley
AI Engineer session on Insights from Snorkel AI running Azure AI Infrastructure: Humza Iqbal and Lachlan Ainley. It adds practical context for how teams are building and operating AI systems in production.
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Insights on Building AI Teams — Heath Black, SignalFire
AI Engineer session on Insights on Building AI Teams, presented by Heath Black, SignalFire. It adds practical context for how teams are building and operating AI systems in production.
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Ionic Launch: Opening the economy to AI agents
AI Engineer session on Ionic Launch: Opening the economy to AI agents. It adds practical context for how teams are building and operating AI systems in production.
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Iterating on LLM apps at scale Learnings from Discord: Ian Webster
AI Engineer session on Iterating on LLM apps at scale Learnings from Discord: Ian Webster. It adds practical context for how teams are building and operating AI systems in production.
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Judging LLMs: Alex Volkov
AI Engineer session on Judging LLMs: Alex Volkov. It adds practical context for how teams are building and operating AI systems in production.
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Keynote: The AI developer experience doesn't have to suck — why and how we built Modal
AI Engineer session on Keynote: The AI developer experience doesn't have to suck, presented by why and how we built Modal. It adds practical context for how teams are building and operating AI systems in production.
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Keynote: Why people think "agent" is a buzzword but it isn't
AI Engineer session on Keynote: Why people think "agent" is a buzzword but it isn't. It adds practical context for how teams are building and operating AI systems in production.
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Knowledge Graphs & GraphRAG: Techniques for Building Effective GenAI Applications: Zach Blumenthal
AI Engineer session on Knowledge Graphs & GraphRAG: Techniques for Building Effective GenAI Applications: Zach Blumenthal. It adds practical context for how teams are building and operating AI systems in production.
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Lessons From A Year Building With LLMs
AI Engineer session on Lessons From A Year Building With LLMs. It adds practical context for how teams are building and operating AI systems in production.
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Lessons from building GenAI based applications — Juan Peredo
AI Engineer session on Lessons from building GenAI based applications, presented by Juan Peredo. It adds practical context for how teams are building and operating AI systems in production.
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Lessons from the Trenches: Building LLM Evals That Work IRL: Aparna Dhinkaran
AI Engineer session on Lessons from the Trenches: Building LLM Evals That Work IRL: Aparna Dhinkaran. It adds practical context for how teams are building and operating AI systems in production.
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Lets Build An Agent from Scratch
AI Engineer session on Lets Build An Agent from Scratch. It adds practical context for how teams are building and operating AI systems in production.
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Llamafile: bringing AI to the masses with fast CPU inference: Stephen Hood and Justine Tunney
AI Engineer session on Llamafile: bringing AI to the masses with fast CPU inference: Stephen Hood and Justine Tunney. It adds practical context for how teams are building and operating AI systems in production.
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LLM Quality Optimization Bootcamp: Thierry Moreau and Pedro Torruella
AI Engineer session on LLM Quality Optimization Bootcamp: Thierry Moreau and Pedro Torruella. It adds practical context for how teams are building and operating AI systems in production.
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LLM Safeguards: Security Privacy Compliance Anti Hallucination: Daniel Whitenack
AI Engineer session on LLM Safeguards: Security Privacy Compliance Anti Hallucination: Daniel Whitenack. It adds practical context for how teams are building and operating AI systems in production.
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LLM Scientific Reasoning: How to Make AI Capable of Nobel Prize Discoveries: Hubert Misztela
AI Engineer session on LLM Scientific Reasoning: How to Make AI Capable of Nobel Prize Discoveries: Hubert Misztela. It adds practical context for how teams are building and operating AI systems in production.
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Low Level Technicals of LLMs: Daniel Han
AI Engineer session on Low Level Technicals of LLMs: Daniel Han. It adds practical context for how teams are building and operating AI systems in production.
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Making Open Models 10x faster and better for Modern Application Innovation: Dmytro (Dima) Dzhulgakov
AI Engineer session on Making Open Models 10x faster and better for Modern Application Innovation: Dmytro (Dima) Dzhulgakov. It adds practical context for how teams are building and operating AI systems in production.
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Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou
AI Engineer session on Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou. It adds practical context for how teams are building and operating AI systems in production.
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Mission-Critical Evals at Scale (Learnings from 100k medical decisions)
AI Engineer session on Mission-Critical Evals at Scale (Learnings from 100k medical decisions). It adds practical context for how teams are building and operating AI systems in production.
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Moondream: how does a tiny vision model slap so hard? — Vikhyat Korrapati
AI Engineer session on Moondream: how does a tiny vision model slap so hard?, presented by Vikhyat Korrapati. It adds practical context for how teams are building and operating AI systems in production.
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Multi model multimodal and multi agent innovations in Azure AI: Cedric Vidal
AI Engineer session on Multi model multimodal and multi agent innovations in Azure AI: Cedric Vidal. It adds practical context for how teams are building and operating AI systems in production.
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Navigating AI’s Frontier in 2025 - Grace Isford, Lux Capital
AI Engineer session on Navigating AI’s Frontier in 2025 - Grace Isford, Lux Capital. It adds practical context for how teams are building and operating AI systems in production.
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Navigating Challenges and Technical Debt in LLMs Deployment: Ahmed Menshawy
AI Engineer session on Navigating Challenges and Technical Debt in LLMs Deployment: Ahmed Menshawy. It adds practical context for how teams are building and operating AI systems in production.
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Navigating RAG Optimization with an Evaluation Driven Compass: Atita Arora and Deanna Emery
AI Engineer session on Navigating RAG Optimization with an Evaluation Driven Compass: Atita Arora and Deanna Emery. It adds practical context for how teams are building and operating AI systems in production.
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No more bad outputs with structured generation: Remi Louf
AI Engineer session on No more bad outputs with structured generation: Remi Louf. It adds practical context for how teams are building and operating AI systems in production.
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No-code fine-tuning: Mark Hennings
AI Engineer session on No-code fine-tuning: Mark Hennings. It adds practical context for how teams are building and operating AI systems in production.
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Open Challenges for AI Engineering: Simon Willison
AI Engineer session on Open Challenges for AI Engineering: Simon Willison. It adds practical context for how teams are building and operating AI systems in production.
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OpenAI for VP's of AI + Advice for Building Agents
AI Engineer session on OpenAI for VP's of AI + Advice for Building Agents. It adds practical context for how teams are building and operating AI systems in production.
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OpenLLMetry is all you need
AI Engineer session on OpenLLMetry is all you need. It adds practical context for how teams are building and operating AI systems in production.
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Optimizing LLMs in Insurance with DSPy: Jeronim Morina
AI Engineer session on Optimizing LLMs in Insurance with DSPy: Jeronim Morina. It adds practical context for how teams are building and operating AI systems in production.
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Patrick Dougherty: How to Build AI Agents that Actually Work
AI Engineer session on Patrick Dougherty: How to Build AI Agents that Actually Work. It adds practical context for how teams are building and operating AI systems in production.
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Personal, Local, Private AI Agents: Soumith Chintala
AI Engineer session on Personal, Local, Private AI Agents: Soumith Chintala. It adds practical context for how teams are building and operating AI systems in production.
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Personality Driven Development: Exploring the Frontier of Agents with Attitude
AI Engineer session on Personality Driven Development: Exploring the Frontier of Agents with Attitude. It adds practical context for how teams are building and operating AI systems in production.
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Privacy First Enterprise AI: Building AI Agents that Never Leave Your Security Boundary
AI Engineer session on Privacy First Enterprise AI: Building AI Agents that Never Leave Your Security Boundary. It adds practical context for how teams are building and operating AI systems in production.
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Productionizing GenAI Models — Lessons from the world's best AI teams: Lukas Biewald
AI Engineer session on Productionizing GenAI Models, presented by Lessons from the world's best AI teams: Lukas Biewald. It adds practical context for how teams are building and operating AI systems in production.
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Prompt Engineering Tactics: Dan Cleary
AI Engineer session on Prompt Engineering Tactics: Dan Cleary. It adds practical context for how teams are building and operating AI systems in production.
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Pydantic is STILL all you need: Jason Liu
AI Engineer session on Pydantic is STILL all you need: Jason Liu. It adds practical context for how teams are building and operating AI systems in production.
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RAG Agents in Prod: 10 Lessons We Learned — Douwe Kiela, creator of RAG
AI Engineer session on RAG Agents in Prod: 10 Lessons We Learned, presented by Douwe Kiela, creator of RAG. It adds practical context for how teams are building and operating AI systems in production.
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RAG and the MongoDB Document Model: Ben Flast
AI Engineer session on RAG and the MongoDB Document Model: Ben Flast. It adds practical context for how teams are building and operating AI systems in production.
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RAG at scale: production ready GenAI apps with Azure AI Search
AI Engineer session on RAG at scale: production ready GenAI apps with Azure AI Search. It adds practical context for how teams are building and operating AI systems in production.
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RAG for VPs of AI: Jerry Liu
AI Engineer session on RAG for VPs of AI: Jerry Liu. It adds practical context for how teams are building and operating AI systems in production.
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Real ROI: Lessons from Enterprises that have already succeeded with LLMs at Scale: Raza Habib
AI Engineer session on Real ROI: Lessons from Enterprises that have already succeeded with LLMs at Scale: Raza Habib. It adds practical context for how teams are building and operating AI systems in production.
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Realtime Data Connectivity for AI: Tanmai Gopal
AI Engineer session on Realtime Data Connectivity for AI: Tanmai Gopal. It adds practical context for how teams are building and operating AI systems in production.
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Reinforcement Learning for Agents - Will Brown, ML Researcher at Morgan Stanley
AI Engineer session on Reinforcement Learning for Agents - Will Brown, ML Researcher at Morgan Stanley. It adds practical context for how teams are building and operating AI systems in production.
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Rethinking how we Scaffold AI Agents - Rahul Sengottuvelu, Ramp
AI Engineer session on Rethinking how we Scaffold AI Agents - Rahul Sengottuvelu, Ramp. It adds practical context for how teams are building and operating AI systems in production.
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Reverse Conway's law and GenAI: How agents will take over the organisation - Patrick Debois
AI Engineer session on Reverse Conway's law and GenAI: How agents will take over the organisation - Patrick Debois. It adds practical context for how teams are building and operating AI systems in production.
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Running AI Application in Minutes w/ AI Templates: Gabriela de Queiroz, Pamela Fox, Harald Kirschner
AI Engineer session on Running AI Application in Minutes w/ AI Templates: Gabriela de Queiroz, Pamela Fox, Harald Kirschner. It adds practical context for how teams are building and operating AI systems in production.
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Scaling Agents for Gen AI Products - Anju Kambadur, Bloomberg Head of AI Engineering
AI Engineer session on Scaling Agents for Gen AI Products - Anju Kambadur, Bloomberg Head of AI Engineering. It adds practical context for how teams are building and operating AI systems in production.
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Scaling AI in Education: A Khanmigo case study: Shawn Jansepar
AI Engineer session on Scaling AI in Education: A Khanmigo case study: Shawn Jansepar. It adds practical context for how teams are building and operating AI systems in production.
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Second Order Effects of AI: Cheng Lou
AI Engineer session on Second Order Effects of AI: Cheng Lou. It adds practical context for how teams are building and operating AI systems in production.
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Self Coding Agents — Colin Flaherty, Augment Code
AI Engineer session on Self Coding Agents, presented by Colin Flaherty, Augment Code. It adds practical context for how teams are building and operating AI systems in production.
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State Space Models for Realtime Multimodal Intelligence: Karan Goel
AI Engineer session on State Space Models for Realtime Multimodal Intelligence: Karan Goel. It adds practical context for how teams are building and operating AI systems in production.
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Stateful Agents — Full Workshop with Charles Packer of Letta and MemGPT
AI Engineer session on Stateful Agents, presented by Full Workshop with Charles Packer of Letta and MemGPT. It adds practical context for how teams are building and operating AI systems in production.
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Stop Guessing: Build Robust AI with Layered CoT
AI Engineer session on Stop Guessing: Build Robust AI with Layered CoT. It adds practical context for how teams are building and operating AI systems in production.
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Substrate Launch: the API for modular AI
AI Engineer session on Substrate Launch: the API for modular AI. It adds practical context for how teams are building and operating AI systems in production.
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System Design for Next-Gen Frontier Models — Dylan Patel, SemiAnalysis
AI Engineer session on System Design for Next-Gen Frontier Models, presented by Dylan Patel, SemiAnalysis. It adds practical context for how teams are building and operating AI systems in production.
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The Adversarial Path to the Personal Assistant: Sumit Agarwal
AI Engineer session on The Adversarial Path to the Personal Assistant: Sumit Agarwal. It adds practical context for how teams are building and operating AI systems in production.
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The Agent Development Life Cycle — Zack Reneau-Wedeen, Sierra
AI Engineer session on The Agent Development Life Cycle, presented by Zack Reneau-Wedeen, Sierra. It adds practical context for how teams are building and operating AI systems in production.
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The AI emperor has no DAUs why most devs still don't use code AI: Quinn Slack
AI Engineer session on The AI emperor has no DAUs why most devs still don't use code AI: Quinn Slack. It adds practical context for how teams are building and operating AI systems in production.
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The Devops Engineer Who Never Sleeps — Diamond Bishop, Datadog
AI Engineer session on The Devops Engineer Who Never Sleeps, presented by Diamond Bishop, Datadog. It adds practical context for how teams are building and operating AI systems in production.
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The era of unbounded products: Designing for Multimodal IO: Ben Hylak
AI Engineer session on The era of unbounded products: Designing for Multimodal IO: Ben Hylak. It adds practical context for how teams are building and operating AI systems in production.
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The Future of Knowledge Assistants: Jerry Liu
AI Engineer session on The Future of Knowledge Assistants: Jerry Liu. It adds practical context for how teams are building and operating AI systems in production.
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The GenAI Maturity Curve or You Probably Don't Need Fine Tuning: Kyle Corbitt
AI Engineer session on The GenAI Maturity Curve or You Probably Don't Need Fine Tuning: Kyle Corbitt. It adds practical context for how teams are building and operating AI systems in production.
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The Hidden Costs of Building Your Own RAG Stack — Ofer Vectara
AI Engineer session on The Hidden Costs of Building Your Own RAG Stack, presented by Ofer Vectara. It adds practical context for how teams are building and operating AI systems in production.
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The Hierarchy of Needs for Training Dataset Development: Chang She and Noah Shpak
AI Engineer session on The Hierarchy of Needs for Training Dataset Development: Chang She and Noah Shpak. It adds practical context for how teams are building and operating AI systems in production.
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The LLM Triangle: Engineering Principles for Robust AI Applications - Almog Baku:
AI Engineer session on The LLM Triangle: Engineering Principles for Robust AI Applications - Almog Baku:. It adds practical context for how teams are building and operating AI systems in production.
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The Making of Devin by Cognition AI: Scott Wu
AI Engineer session on The Making of Devin by Cognition AI: Scott Wu. It adds practical context for how teams are building and operating AI systems in production.
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The missing pieces of workflow automation — Shirsha Chaudhuri, Thomson Reuters Labs
AI Engineer session on The missing pieces of workflow automation, presented by Shirsha Chaudhuri, Thomson Reuters Labs. It adds practical context for how teams are building and operating AI systems in production.
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The Model Isn’t Wrong — You’re Just Bad at Prompting
AI Engineer session on The Model Isn’t Wrong, presented by You’re Just Bad at Prompting. It adds practical context for how teams are building and operating AI systems in production.
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The Multimodal Future of Education: Stefania Druga
AI Engineer session on The Multimodal Future of Education: Stefania Druga. It adds practical context for how teams are building and operating AI systems in production.
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The Price of Intelligence - AI Agent Pricing in 2025
AI Engineer session on The Price of Intelligence - AI Agent Pricing in 2025. It adds practical context for how teams are building and operating AI systems in production.
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The Rise of the AI Software Engineer: Jesse Han
AI Engineer session on The Rise of the AI Software Engineer: Jesse Han. It adds practical context for how teams are building and operating AI systems in production.
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The ROI of AI: Why you need Eval Framework - Beyang Liu
AI Engineer session on The ROI of AI: Why you need Eval Framework - Beyang Liu. It adds practical context for how teams are building and operating AI systems in production.
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This video was edited with AI agent. But how?
AI Engineer session on This video was edited with AI agent. But how?. It adds practical context for how teams are building and operating AI systems in production.
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Tool Calling Is Not Just Plumbing for AI Agents — Roy Derks
AI Engineer session on Tool Calling Is Not Just Plumbing for AI Agents, presented by Roy Derks. It adds practical context for how teams are building and operating AI systems in production.
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Training Albatross An Expert Finance LLM: Leo Pekelis
AI Engineer session on Training Albatross An Expert Finance LLM: Leo Pekelis. It adds practical context for how teams are building and operating AI systems in production.
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Trust, but Verify: Knowledge Agents for Finance Workflows - Mike Conover
AI Engineer session on Trust, but Verify: Knowledge Agents for Finance Workflows - Mike Conover. It adds practical context for how teams are building and operating AI systems in production.
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Understanding AI Stakes to Break Production Code: Philip Rathle
AI Engineer session on Understanding AI Stakes to Break Production Code: Philip Rathle. It adds practical context for how teams are building and operating AI systems in production.
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Unlocking Developer Productivity across CPU and GPU with MAX: Chris Lattner
AI Engineer session on Unlocking Developer Productivity across CPU and GPU with MAX: Chris Lattner. It adds practical context for how teams are building and operating AI systems in production.
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Unveiling the latest Gemma model advancements: Kathleen Kenealy
AI Engineer session on Unveiling the latest Gemma model advancements: Kathleen Kenealy. It adds practical context for how teams are building and operating AI systems in production.
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Using agents to build an agent company: Joao Moura
AI Engineer session on Using agents to build an agent company: Joao Moura. It adds practical context for how teams are building and operating AI systems in production.
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Vercel AI SDK Masterclass: From Fundamentals to Deep Research
AI Engineer session on Vercel AI SDK Masterclass: From Fundamentals to Deep Research. It adds practical context for how teams are building and operating AI systems in production.
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Voice Agent Engineering — Nik Caryotakis, SuperDial
AI Engineer session on Voice Agent Engineering, presented by Nik Caryotakis, SuperDial. It adds practical context for how teams are building and operating AI systems in production.
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Voice Agents: the good, the bad, and the ugly
AI Engineer session on Voice Agents: the good, the bad, and the ugly. It adds practical context for how teams are building and operating AI systems in production.
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We accidentally made an AI platform: Jamie Turner
AI Engineer session on We accidentally made an AI platform: Jamie Turner. It adds practical context for how teams are building and operating AI systems in production.
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What It Actually Takes to Deploy GenAI Applications to Enterprises: Arjun Bansal and Trey Doig
AI Engineer session on What It Actually Takes to Deploy GenAI Applications to Enterprises: Arjun Bansal and Trey Doig. It adds practical context for how teams are building and operating AI systems in production.
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What's new from Anthropic and what's next: Alex Albert
AI Engineer session on What's new from Anthropic and what's next: Alex Albert. It adds practical context for how teams are building and operating AI systems in production.
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Where AI is superhuman: The right jobs to automate with LLMs
AI Engineer session on Where AI is superhuman: The right jobs to automate with LLMs. It adds practical context for how teams are building and operating AI systems in production.
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Which Jobs Can Be Replaced Today: Fryderyk Wiatrowski and Peter Albert
AI Engineer session on Which Jobs Can Be Replaced Today: Fryderyk Wiatrowski and Peter Albert. It adds practical context for how teams are building and operating AI systems in production.
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Why Agent Engineering — swyx
AI Engineer session on Why Agent Engineering, presented by swyx. It adds practical context for how teams are building and operating AI systems in production.
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WTF do people use Open Models for??
AI Engineer session on WTF do people use Open Models for??. It adds practical context for how teams are building and operating AI systems in production.
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Your AI Agent Isn't an Engineer: The Art of Thoughtful Anthropomorphism
AI Engineer session on Your AI Agent Isn't an Engineer: The Art of Thoughtful Anthropomorphism. It adds practical context for how teams are building and operating AI systems in production.
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Your Evals Are Meaningless (And Here’s How to Fix Them)
AI Engineer session on Your Evals Are Meaningless (And Here’s How to Fix Them). It adds practical context for how teams are building and operating AI systems in production.
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Your LLM Ran Out of Knowledge — Now What?
AI Engineer session on Your LLM Ran Out of Knowledge, presented by Now What?. It adds practical context for how teams are building and operating AI systems in production.
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‘Speaking Dolphin’ to AI Data Dominance, 4.1 + Kling 2.0: 7 Updates Critically Analysed
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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o3 and o4-mini - they’re great, but easy to over-hype
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI CEO: ‘Stock Crash Could Stop AI Progress’, Llama 4 Anti-climax + ‘Superintelligence in 2027’ ...
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Gemini 2.5 Pro - It’s a Darn Smart Chatbot … (New Simple High Score)
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Did AI Just Get Commoditized? Gemini 2.5, New DeepSeek V3, & Microsoft vs OpenAI
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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OpenAI’s New ImageGen is Unexpectedly Epic … (ft. Reve, Imagen 3, Midjourney etc)
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
Adversarial Machine Learning: A Taxonomy and Terminology of Attacks and Mitigations
NIST finalizes AI 100-2e2025, providing a terminology and taxonomy for adversarial machine learning across predictive and generative AI systems.
Progress from our Frontier Red Team
Anthropic shares lessons from frontier red teaming and discusses where models are showing early-warning signs of higher-risk cyber and biology capabilities.
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Manus AI - The Calm Before the Hypestorm … (vs Deep Research + Grok 3)
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Announcing AI Protection: Security for the AI era
Google introduced AI Protection and Model Armor to address prompt injection, jailbreaks, data loss, and multicloud AI workload security.
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GPT 4.5 - not so much wow
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Claude 3.7 is More Significant than its Name Implies (ft DeepSeek R2 + GPT 4.5 coming soon)
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Deep research System Card
OpenAI’s system card for deep research covers prompt injection, privacy, code execution, and external red teaming prior to release.
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AGI: (gets close), Humans: ‘Who Gets to Own it?’
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Deep Research by OpenAI - The Ups and Downs vs DeepSeek R1 Search + Gemini Deep Research
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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o3-mini and the “AI War”
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Nothing Much Happens in AI, Then Everything Does All At Once
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Operator System Card
The Operator system card documents red teaming and mitigation choices for a computer-using agent, with prompt injections listed as a central risk area.
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Altman Expects a ‘Fast Take-off’, ‘Super-Agent’ Debuting Soon and DeepSeek R1 Out
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Enhancing AI safety: Insights and lessons from red teaming
Microsoft summarizes lessons from red teaming more than one hundred generative AI products, emphasizing system-level testing, human expertise, and automation.
3 takeaways from red teaming 100 generative AI products
Microsoft Security distills lessons from red teaming more than 100 generative AI products, including multimodal prompt injection and core cyber hygiene.
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OpenAI Backtracks, Gunning for Superintelligence: Altman Brings His AGI Timeline Closer - '25 to '29
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
OWASP Top 10 for Large Language Model Applications
OWASP’s GenAI security project remains a practical baseline for teams building or assessing LLM applications and agentic systems.
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o3 - wow
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Never Browse Alone? Gemini 2 Live and ChatGPT Vision
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Sora is Out, But is it a Distraction?
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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o1 Pro Mode – ChatGPT Pro Full Analysis (plus o1 paper highlights)
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Breaks Its Silence: OpenAI’s ‘Next 12 Days’, Genie 2, and a Word of Caution
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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New Google Model Ranked ‘No. 1 LLM’, But There’s a Problem
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Leak: ‘GPT-5 exhibits diminishing returns’, Sam Altman: ‘lol’
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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ChatGPT with Search, Altman AMA
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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The New Claude 3.5 Sonnet: Better, Yes, But Not Just in the Way You Might Think
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI - 2024AD: 212-page Report (from this morning) Fully Read w/ Highlights
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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OpenAI: ‘We Just Reached Human-level Reasoning’.
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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‘Advanced Voice’ ChatGPT Just Happened … But There's 3 Other Stories You Probably Shouldn’t Ignore
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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o1 - What is Going On? Why o1 is a 3rd Paradigm of Model + 10 Things You Might Not Know
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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ChatGPT o1 - In-Depth Analysis and Reaction (o1-preview)
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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$125B for Superintelligence? 3 Models Coming, Sutskever's Secret SSI, & Data Centers (in space)...
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Grok-2 Actually Out, But What If It Were 10,000x the Size?
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Was GPT-5 Underwhelming, Or Not? OpenAI Co-founder Exits, Figure02 Arrives, Character.AI Gutted
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Llama 405b: Full 92 page Analysis, and Uncontaminated SIMPLE Benchmark Results
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT-4o Mini Arrives In Global IT Outage, But How ‘Mini’ Is Its Intelligence?
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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How Far Can We Scale AI? Gen 3, Claude 3.5 Sonnet and AI Hype
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Won't Be AGI, Until It Can At Least Do This (plus 6 key ways LLMs are being upgraded)
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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‘Everything is Going to Be Robotic’ Nvidia Promises, as AI Gets More Real
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Microsoft Promises a 'Whale' for GPT-5, Anthropic Delves Inside a Model’s Mind and Altman Stumbles
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT-4o - Full Breakdown + Bonus Details
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Conquers Gravity: Robo-dog, Trained by GPT-4, Stays Balanced on Rolling, Deflating Yoga Ball
This AI Explained video reviews a major AI development through the lens of robotics, world models, and embodied AI. It is useful context for AI engineering, evaluation, governance, and operational risk.
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New OpenAI Model 'Imminent' and AI Stakes Get Raised (plus Med Gemini, GPT 2 Chatbot and Scale AI)
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
![[Workshop] AI Engineering 101 video thumbnail](https://i.ytimg.com/vi/C0ZUdFg-iTo/hqdefault.jpg)
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[Workshop] AI Engineering 101
AI Engineer session on [Workshop] AI Engineering 101. It adds practical context for how teams are building and operating AI systems in production.
![[Workshop] AI Engineering 201: Inference video thumbnail](https://i.ytimg.com/vi/N7lJY5IKVLE/hqdefault.jpg)
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[Workshop] AI Engineering 201: Inference
AI Engineer session on [Workshop] AI Engineering 201: Inference. It adds practical context for how teams are building and operating AI systems in production.
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120k players in a week: Lessons from the first viral CLIP app: Joseph Nelson
AI Engineer session on 120k players in a week: Lessons from the first viral CLIP app: Joseph Nelson. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineering 201: The Rest of the Owl
AI Engineer session on AI Engineering 201: The Rest of the Owl. It adds practical context for how teams are building and operating AI systems in production.
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Announcing the AI Engineer Network: Benjamin Dunphy
AI Engineer session on Announcing the AI Engineer Network: Benjamin Dunphy. It adds practical context for how teams are building and operating AI systems in production.
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Building AI For All: Amjad Masad & Michele Catasta
AI Engineer session on Building AI For All: Amjad Masad & Michele Catasta. It adds practical context for how teams are building and operating AI systems in production.
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Building Blocks for LLM Systems & Products: Eugene Yan
AI Engineer session on Building Blocks for LLM Systems & Products: Eugene Yan. It adds practical context for how teams are building and operating AI systems in production.
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Building Context-Aware Reasoning Applications with LangChain and LangSmith: Harrison Chase
AI Engineer session on Building Context-Aware Reasoning Applications with LangChain and LangSmith: Harrison Chase. It adds practical context for how teams are building and operating AI systems in production.
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Building Production-Ready RAG Applications: Jerry Liu
AI Engineer session on Building Production-Ready RAG Applications: Jerry Liu. It adds practical context for how teams are building and operating AI systems in production.
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Building Reactive AI Apps: Matt Welsh
AI Engineer session on Building Reactive AI Apps: Matt Welsh. It adds practical context for how teams are building and operating AI systems in production.
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Climbing the Ladder of Abstraction: Amelia Wattenberger
AI Engineer session on Climbing the Ladder of Abstraction: Amelia Wattenberger. It adds practical context for how teams are building and operating AI systems in production.
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Domain adaptation and fine-tuning for domain-specific LLMs: Abi Aryan
AI Engineer session on Domain adaptation and fine-tuning for domain-specific LLMs: Abi Aryan. It adds practical context for how teams are building and operating AI systems in production.
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GPT Web App Generator - 10,000 apps created in a month: Matija Sosic
AI Engineer session on GPT Web App Generator - 10,000 apps created in a month: Matija Sosic. It adds practical context for how teams are building and operating AI systems in production.
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Harnessing the Power of LLMs Locally: Mithun Hunsur
AI Engineer session on Harnessing the Power of LLMs Locally: Mithun Hunsur. It adds practical context for how teams are building and operating AI systems in production.
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How to Become an AI Engineer from a Fullstack Background - Reid Mayo
AI Engineer session on How to Become an AI Engineer from a Fullstack Background - Reid Mayo. It adds practical context for how teams are building and operating AI systems in production.
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Move Fast Break Nothing: Dedy Kredo
AI Engineer session on Move Fast Break Nothing: Dedy Kredo. It adds practical context for how teams are building and operating AI systems in production.
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Open Questions for AI Engineering: Simon Willison
AI Engineer session on Open Questions for AI Engineering: Simon Willison. It adds practical context for how teams are building and operating AI systems in production.
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Pragmatic AI with TypeChat: Daniel Rosenwasser
AI Engineer session on Pragmatic AI with TypeChat: Daniel Rosenwasser. It adds practical context for how teams are building and operating AI systems in production.
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Principles for Prompt Engineering - Karina Nguyen (Claude Instant @ Anthropic)
AI Engineer session on Principles for Prompt Engineering - Karina Nguyen (Claude Instant @ Anthropic). It adds practical context for how teams are building and operating AI systems in production.
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Pydantic is all you need: Jason Liu
AI Engineer session on Pydantic is all you need: Jason Liu. It adds practical context for how teams are building and operating AI systems in production.
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Retrieval Augmented Generation in the Wild: Anton Troynikov
AI Engineer session on Retrieval Augmented Generation in the Wild: Anton Troynikov. It adds practical context for how teams are building and operating AI systems in production.
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See, Hear, Speak, Draw: Logan Kilpatrick & Simón Fishman
AI Engineer session on See, Hear, Speak, Draw: Logan Kilpatrick & Simón Fishman. It adds practical context for how teams are building and operating AI systems in production.
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Storyteller: Building Multi-modal Apps with TS & ModelFusion - Lars Grammel, PhD
AI Engineer session on Storyteller: Building Multi-modal Apps with TS & ModelFusion - Lars Grammel, PhD. It adds practical context for how teams are building and operating AI systems in production.
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Supabase Vector: The Postgres Vector database: Paul Copplestone
AI Engineer session on Supabase Vector: The Postgres Vector database: Paul Copplestone. It adds practical context for how teams are building and operating AI systems in production.
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The 1,000x AI Engineer: Swyx
AI Engineer session on The 1,000x AI Engineer: Swyx. It adds practical context for how teams are building and operating AI systems in production.
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The Age of the Agent: Flo Crivello
AI Engineer session on The Age of the Agent: Flo Crivello. It adds practical context for how teams are building and operating AI systems in production.
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The AI Evolution: Mario Rodriguez, GitHub
AI Engineer session on The AI Evolution: Mario Rodriguez, GitHub. It adds practical context for how teams are building and operating AI systems in production.
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The AI Pivot: With Chris White of Prefect & Bryan Bischof of Hex
AI Engineer session on The AI Pivot: With Chris White of Prefect & Bryan Bischof of Hex. It adds practical context for how teams are building and operating AI systems in production.
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The Code AI Maturity Model and What It Means For You: Ado Kukic
AI Engineer session on The Code AI Maturity Model and What It Means For You: Ado Kukic. It adds practical context for how teams are building and operating AI systems in production.
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The Future of Work: Toran Bruce Richards, Silen Naihin et al
AI Engineer session on The Future of Work: Toran Bruce Richards, Silen Naihin et al. It adds practical context for how teams are building and operating AI systems in production.
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The Hidden Life of Embeddings: Linus Lee
AI Engineer session on The Hidden Life of Embeddings: Linus Lee. It adds practical context for how teams are building and operating AI systems in production.
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The Intelligent Interface: Sam Whitmore & Jason Yuan of New Computer
AI Engineer session on The Intelligent Interface: Sam Whitmore & Jason Yuan of New Computer. It adds practical context for how teams are building and operating AI systems in production.
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The Weekend AI Engineer: Hassan El Mghari
AI Engineer session on The Weekend AI Engineer: Hassan El Mghari. It adds practical context for how teams are building and operating AI systems in production.
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Trust, but Verify: Shreya Rajpal
AI Engineer session on Trust, but Verify: Shreya Rajpal. It adds practical context for how teams are building and operating AI systems in production.
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Using AI to Build an Infinite Game: Jeff Schomay
AI Engineer session on Using AI to Build an Infinite Game: Jeff Schomay. It adds practical context for how teams are building and operating AI systems in production.
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‘Her’ AI, Almost Here? Llama 3, Vasa-1, and Altman ‘Plugging Into Everything You Want To Do’
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Udio, the Mysterious GPT Update, and Infinite Attention
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Why Does OpenAI Need a 'Stargate' Supercomputer? Ft. Perplexity CEO Aravind Srinivas
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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5 Key Quotes: Altman, Huang and 'The Most Interesting Year'
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Agents Take the Wheel: Devin, SIMA, Figure 01 and The Future of Jobs
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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The New, Smartest AI: Claude 3 – Tested vs Gemini 1.5 + GPT-4
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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The AI 'Genie' is Out + Humanoid Robotics Step Closer
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Sora - Full Analysis (with new details)
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Gemini 1.5 and The Biggest Night in AI
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Gemini Ultra - Full Review
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT-5: Everything You Need to Know So Far
This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Alpha Everywhere: AlphaGeometry, AlphaCodium and the Future of LLMs
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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OpenAI Flip-Flops and '10% Chance of Outperforming Humans in Every Task by 2027' - 3K AI Researchers
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI On An Exponential? Data, Mamba, and More
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Midjourney v6, Altman 'Age Reversal' and Gemini 2 - Christmas Edition
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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A 100T Transformer Model Coming? Plus ByteDance Saga and the Mixtral Price Drop
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Phi-2, Imagen-2, Optimus-Gen-2: Small New Models to Change the World?
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Gemini Full Breakdown + AlphaCode 2 Bombshell
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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OpenAI Insights and Training Data Shenanigans - 7 'Complicated' Developments + Guest Star
This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Q* - Clues to the Puzzle?
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Are We Back to Before? OpenAI 2.0, Inflection-2 and a Major AI Cancer Breakthrough
This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Altman@Microsoft, Shear@OpenAI, Chaos@Everywhere: Sutskever Regret and the Weekend That Changed AI
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Altman Out: Reasons, Reactions and the Repercussions for the Industry
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 4 Turbo-Charged? Plus Custom GPTS, Grok, AGI Tier List, Vision Demos, Whisper V3 and more
This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Declarations and AGI Timelines – Looking More Optimistic?
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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State of AI 2023: Highlights of 163 Page Report + Eureka Self-Improvement, MEG, Suno AI and GPT F
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Not Slowing Down: GAIA-1 to GPT Vision Tips, Nvidia B100 to Bard vs LLaVA
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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RT-X and the Dawn of Large Multimodal Models: Google Breakthrough and 160-page Report Highlights
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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An Actually Big Week in AI: AutoGen, The A-Phone, Mistral 7B, GPT-Fathom and Meta Hunts CharacterAI
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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ChatGPT Fails Basic Logic but Now Has Vision, Wins at Chess and Prompts a Masterpiece
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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The New Bard and AI Images, Videos, and Translations
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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9 AI Developments: HeyGen 2.0 to AjaxGPT, Open Interpreter to NExT-GPT and Roblox AI
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AGI Will Not Be A Chatbot - Autonomy, Acceleration, and Arguments Behind the Scenes
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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SmartGPT: Major Benchmark Broken - 89.0% on MMLU + Exam's Many Errors
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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9 New Gemini Leaks, Code Llama and A Major AI Consciousness Paper
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI Los Alamos? + New Realistic AI Avatars
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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11 Major AI Developments: RT-2 to '100X GPT-4'
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Llama 2: Full Breakdown
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Bad AI Predictions: Bard Upgrade, 2 Years to AI Auto-Money, OpenAI Investigation and more
This AI Explained video reviews a major AI development through the lens of robotics, world models, and embodied AI. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Time Until Superintelligence: 1-2 Years, or 20? Something Doesn't Add Up
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Phi-1: A 'Textbook' Model
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Google Gemini: AlphaGo-GPT?
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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ChatGPT's Achilles' Heel
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Sam Altman's World Tour, in 16 Moments
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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The AI News You Might Have Missed This Week - Zuckerberg to Falcon w/ SPQR
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Orca: The Model Few Saw Coming
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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The AI News You Might Have Missed This Week
This AI Explained video reviews a major AI development through the lens of robotics, world models, and embodied AI. It is useful context for AI engineering, evaluation, governance, and operational risk.
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'Show Your Working': ChatGPT Performance Doubled w/ Process Rewards (+Synthetic Data Event Horizon)
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
![Hassabis, Altman and AGI Labs Unite - AI Extinction Risk Statement [ft. Sutskever, Hinton + Voyager] video thumbnail](https://i.ytimg.com/vi/f20wXjWHh2o/hqdefault.jpg)
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Hassabis, Altman and AGI Labs Unite - AI Extinction Risk Statement [ft. Sutskever, Hinton + Voyager]
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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12 New Code Interpreter Uses (Image to 3D, Book Scans, Multiple Datasets, Error Analysis ... )
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 4 Got Upgraded - Code Interpreter (ft. Image Editing, MP4s, 3D Plots, Data Analytics and more!)
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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'This Could Go Quite Wrong' - Altman Testimony, GPT 5 Timeline, Self-Awareness, Drones and more
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Enter PaLM 2 (New Bard): Full Breakdown - 92 Pages Read and Gemini Before GPT 5? Google I/O
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 4 is Smarter than You Think: Introducing SmartGPT
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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What's Behind the ChatGPT History Change? How You Can Benefit + The 6 New Developments This Week
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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8 Signs It's The Future: Thought-to-Text, Nvidia Text-to-Video, Character AI, and P(Doom) @Ted
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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‘We Must Slow Down the Race’ – X AI, GPT 4 Can Now Do Science and Altman GPT 5 Statement
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
![GPT 5 Will be Released 'Incrementally' - 5 Points from Brockman Statement [plus Timelines & Safety] video thumbnail](https://i.ytimg.com/vi/1NAmLp5i4Ps/hqdefault.jpg)
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GPT 5 Will be Released 'Incrementally' - 5 Points from Brockman Statement [plus Timelines & Safety]
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
![Can GPT 4 Prompt Itself? MemoryGPT, AutoGPT, Jarvis, Claude-Next [10x GPT 4!] and more... video thumbnail](https://i.ytimg.com/vi/6NoTuqDAkfg/hqdefault.jpg)
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Can GPT 4 Prompt Itself? MemoryGPT, AutoGPT, Jarvis, Claude-Next [10x GPT 4!] and more...
This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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Do We Get the $100 Trillion AI Windfall? Sam Altman's Plans, Jobs & the Falling Cost of Intelligence
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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'Pause Giant AI Experiments' - Letter Breakdown w/ Research Papers, Altman, Sutskever and more
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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How Well Can GPT-4 See? And the 5 Upgrades That Are Next
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.
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'Sparks of AGI' - Bombshell GPT-4 Paper: Fully Read w/ 15 Revelations
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
![What's Up With Bard? 9 Examples + 6 Reasons Google Fell Behind [ft. Muse, Med-PaLM 2 and more] video thumbnail](https://i.ytimg.com/vi/XmnTd92NqFw/hqdefault.jpg)
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What's Up With Bard? 9 Examples + 6 Reasons Google Fell Behind [ft. Muse, Med-PaLM 2 and more]
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
![Google Bard - The Full Review. Bard vs Bing [LaMDA vs GPT 4] video thumbnail](https://i.ytimg.com/vi/9ll_pth4Sss/hqdefault.jpg)
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Google Bard - The Full Review. Bard vs Bing [LaMDA vs GPT 4]
This AI Explained video reviews a major AI development through the lens of multimodal generation and provenance. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 4: 9 Revelations (not covered elsewhere)
This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 4: Full Breakdown (14 Details You May Have Missed)
This AI Explained video reviews a major AI development through the lens of AI safety and model behavior. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 5 is All About Data
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
![8 New Ways to Use Bing's Upgraded 8 [now 20] Message Limit (ft. pdfs, quizzes, tables, scenarios...) video thumbnail](https://i.ytimg.com/vi/weH9LKYNGWg/hqdefault.jpg)
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8 New Ways to Use Bing's Upgraded 8 [now 20] Message Limit (ft. pdfs, quizzes, tables, scenarios...)
This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
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9 of the Best Bing (GPT 4) Prompts
This AI Explained video reviews a major AI development through the lens of model capability and AI systems in practice. It is useful context for AI engineering, evaluation, governance, and operational risk.
![8 Ways ChatGPT 4 [Is] Better Than ChatGPT video thumbnail](https://i.ytimg.com/vi/cgihbdO6bvw/hqdefault.jpg)
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8 Ways ChatGPT 4 [Is] Better Than ChatGPT
This AI Explained video reviews a major AI development through the lens of benchmarks and evaluation evidence. It is useful context for AI engineering, evaluation, governance, and operational risk.
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GPT 4 - hype vs reality
This AI Explained video reviews a major AI development through the lens of scaling and compute economics. It is useful context for AI engineering, evaluation, governance, and operational risk.