Evergreen Overview
Application architecture, developer workflow, tooling, and production patterns for building AI systems.
AI Engineering
Application architecture, developer workflow, tooling, and production patterns for building AI systems.
ai engineeringllm application developmentagent engineeringmcpdeveloper toolingai systems
What this page covers
- Core concepts for ai engineering
- Useful references, notes, and curated examples
- Practical links back to AI systems and operational risk
Why it matters
- It creates better language for technical and governance discussions
- It helps teams connect theory to deployed workflows
- It supports more repeatable review and decision-making
Who this page is for
- Researchers and builders working with AI systems
- Security and governance teams
- Leaders looking for current reference material
References
Current notes, events, and source material
These items are included because they add useful evidence, framing, implementation detail, or upcoming context for teams working in this area.
AAAI-27
The 41st AAAI Conference on Artificial Intelligence takes place in Montréal with technical papers, workshops, tutorials, competitions, and programs spanning AI research and practice.
CSA Agentic AI Security Summit 2026
Cloud Security Alliance's free two-day virtual summit focuses on securing autonomous AI systems at enterprise scale. The program is framed around multi-agent risk, governance, and the controls needed to establish trust across the agentic stack.
AGNTCon + MCPCon North America 2026
AGNTCon + MCPCon North America 2026 brings agent and MCP builders to San Jose to cover production architectures, protocols, infrastructure, security, governance, observability, and interoperability.
AAAI/ACM AIES 2026
The ninth AAAI/ACM Conference on AI, Ethics, and Society convenes technical, legal, philosophical, and social-science research in Malmö. The 2026 program examines the governance and societal consequences of AI systems as they move from experimental tools into entrenched infrastructure.
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.
Berkeley Agentic AI Summit 2026
Berkeley RDI's two-day Agentic AI Summit covers the full agent stack, from foundation models, infrastructure, and frameworks to evaluation, real-world deployment, safety, and security. The UC Berkeley program combines research and industry sessions and offers a public livestream.
ANSI Innovation Summit 2026
ANSI's four-day Innovation Summit brings standards bodies, government, and industry together in Denver. Its July 29 AI program focuses on trust, security, data integrity, manufacturing use cases, and the standards implications of fast-moving AI systems.
Now in preview: Find and fix software vulnerabilities with CodeMender
Google opened a preview of CodeMender, an AI code-security agent delivered through Gemini Enterprise Agent Platform and AI Threat Defense. It is designed to inspect code, identify and validate potentially exploitable defects, and produce targeted fixes, with Google’s specialized Gemini 3.5 Flash Cyber model initially restricted to governments and trusted partners.
Introducing Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber
Google introduced Gemini 3.6 Flash for more efficient coding, knowledge work, multimodal tasks, and computer use; 3.5 Flash-Lite for high-throughput, low-latency agent workflows; and 3.5 Flash Cyber for vulnerability research inside CodeMender. Google reports lower token use for 3.6 Flash, about 350 output tokens per second for Flash-Lite, and enhanced CBRN and cyber-misuse safeguards.
Expenditure Horizon: Measuring Optimization Ability, with an Application to NanoGPT
METR introduces the “expenditure horizon”: the budget at which a human and an AI agent produce equal gains on an optimization problem. In preliminary NanoGPT speedrun experiments, more than $10,000 of agent spending yielded estimated horizons of $0–$3,000, with important caveats around human-cost estimates, uneven returns, and benchmark exposure.
AWS Kiro Flaw Let a Poisoned Web Page Rewrite Its Config and Run Code
Intezer and Kodem Security found that hidden instructions in a fetched web page could make AWS Kiro write a malicious MCP server into its own configuration and automatically execute it with the developer’s privileges. The prompt-injection chain bypassed meaningful approval, affected tested 0.9 and 0.10 builds, and was confirmed fixed in version 0.11.130; no in-the-wild exploitation was reported.
New ENCFORGE Ransomware Targets AI Model Files in Langflow RCE Attack
Sysdig observed the JADEPUFFER operator exploit an unauthenticated Langflow code-execution flaw, harvest credentials, and abuse a mounted Docker socket to reach the host. The operator then deployed ENCFORGE, Go ransomware built to encrypt model weights, vector indexes, training datasets, and other AI artifacts; the report covers one observed session and found no exfiltration capability in the recovered binary.
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Every Harness Will Become A Claw — Sam Bhagwat, Mastra
Sam Bhagwat frames an agent harness as context engineering combined with coding-agent capabilities, then argues that competitive harnesses tend to acquire persistent execution, tools, heartbeats, and cloud hosting until they resemble always-on “claws.” The talk presents that evolution as a product and infrastructure trend rather than a settled architectural requirement.
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HTML Is All Agents Need — James Russo, HeyGen
James Russo describes HeyGen’s path from large prompts and agentic retries to an HTML, CSS, and JavaScript authoring layer for deterministic video. React-based Remotion constrained generated output, while plain web primitives restored flexibility; the team then built rendering controls, evaluation loops, and reusable skills so smaller models could produce consistent MP4s.
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Better Agent Auth — Bereket Habtemeskel & Paola Estefania, Better Auth
Bereket Habtemeskel and Paola Estefania present Agent Auth, a draft protocol that gives each autonomous or delegated runtime agent its own identity, capability grants, lifecycle, and short-lived signed credentials. The design separates agents from users and host applications, supports discovery and approval, and allows one agent to be scoped, audited, suspended, or revoked without rotating every shared credential.
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2026 State of AI Engineering — Barr Yaron, Amplify Partners
Barr Yaron presents Amplify Partners’ survey of 1,048 AI practitioners: 97% described AI’s organizational impact as net positive, while more than 90% also reported downsides such as review burden and eroding technical depth. Agent write access tripled year over year, evaluation remained the most commonly cited stack problem, and teams tended to buy inference while keeping prompts, retrieval, and evals in house.
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Your agent architecture has a half-life of 6 months — Dan Farrelly, CTO, Inngest
Dan Farrelly argues that agent patterns—RAG, ReAct, prompt chains, orchestrator-workers, MCP, and CLIs—change too quickly to anchor a durable system. He recommends keeping decisions close to application code while building on stable execution primitives for state, retries, scheduling, observability, and long-running work so teams can replace the harness without rebuilding operations.
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The Desktop Frontier — Ahmad Osman, Osmantic
Ahmad Osman demonstrates open models on a DGX Station and argues that capability per active parameter is improving fast enough to move increasingly strong systems from data centers onto workstations and, eventually, consumer devices. He presents local inference as a path to control, customization, privacy, and “sovereign AI,” while making explicit predictions about future capability on smaller hardware.
Mythos Didn't Break Your Security Program. Your Exposure Window Could.
This contributed XM Cyber analysis argues that AI-accelerated vulnerability discovery widens the “exposure window” between exploitability and remediation because prioritization can move at machine speed while ownership, approvals, and change windows remain slow. It recommends measuring how long critical assets remain reachable and using attack paths to focus remediation on exposures with meaningful blast radius.
Capital One Open Sources AI-Powered ‘VulnHunter’ Security Tool
Capital One released VulnHunter, an Apache-licensed agentic code-security workflow that starts from attacker-reachable entry points, traces prospective exploit paths, tries to falsify its own findings, and proposes evidence-backed code repairs. The initial implementation targets Claude Code with Claude Opus 4.8, and Capital One says it used the tool across thousands of internal repositories.
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Medic for Apache Spark - First Aid for Failing Jobs - Drasko Profirovic, Pinterest
In this talk, we’ll share the journey of building an agentic diagnostics tool to address one of the most time-consuming challenges in data engineering: troubleshooting Spark job failures at scale. As Spark workloads and platform complexity continue to grow, traditional dashboards and static playbooks are no longer suff
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Through the AI Fog: The Architectural Decision Agentic Security Depends On — Manoj Nair, Snyk
Ask the latest frontier models, the ones not even public yet, to find the same vulnerability five times, and only half of those runs catch it. Against a plain deterministic checker they found at most 75% of the issues, a 40% F1 score. That number sits underneath the whole talk: the generator and the validator cannot be
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AI’s Jurassic Park Period — Aaron Stanley, dbt Labs
Twenty years ago Aaron Stanley arrived at an emergency evidence collection for an SEC investigation and realized he had forgotten the dongle that licensed his forensic software. Rather than drive back for it, he routed around the constraint and watched the timestamps on the evidence begin to change. In a who knew what
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Security Track Intro — Randall Degges, Snyk
Building software with AI almost feels like a cheat code: you ship what you were working on and watch it spark joy in real users. The catch, and the reason Randall Degges is opening the World's Fair's first Security Track, is that three things still stand in the way of doing that at scale. AI writes insecure code just
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Enterprise Agents Have a Structure Problem - Ishita Daga, Tesla
Most enterprise agents fail for the same reason: the model can generate SQL, call tools, and follow workflows, but it has no understanding of how the business actually defines its data. Most teams try to fix this with longer prompts, more RAG, or a bigger model. The real fix is building semantic retrieval infrastructur
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It's 10pm. Do You Know Where Your Agents Are? — Kim Maida, Keycard
An incident agent on the night shift reads a ticket: the billing database is broken, payments failing. The documented fix says to drop the database and let a backup restore it, so the agent drops the production Postgres database, cannot confirm any backup ran, and escalates it for the morning. This has happened to real
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Privacy-Preserving Intelligence — Steve Korshakov, Bee (acq. Amazon)
A wearable that records everything you say captures about 10 million tokens a year, and within a week it knows almost everything about you. That is Bee, and Steve Korshakov calls it roughly the most sensitive capture device on the market, which is why his whole talk is about one guarantee: no one can read your data, no
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Skills are the New SDKs - Elvin Aghammadzada, DataRobot
You shipped a REST API. Then an SDK. Then MCP tool calling. And still, when a developer asks a coding agent to use your platform, it invents steps, and breaks in production. The problem is that your platform isn't teachable yet. The fix is a skill layer. Versioned, task-specific packages that encode the workflow knowle
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We Gave an Agent Production Code Access and Then Tried to Sleep at Night — Moritz Johner, Form3
A single PatchPilot PR that bumped a few dependencies changed 70,000 lines of code, and the whole problem hides somewhere in that diff. Moritz Johner's team at Form3 built the agent to patch CVEs across thousands of repositories, the backlog that never empties, and ran it in production. Then infosec asked the question
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Agents Need Receipts, Not More Tool Calls - Armanas Povilionis, Alithea Bio
In this talk, I’ll show an agent publish a service, another agent discover and invoke it, and a signed receipt that proves what happened. The point is simple: if agents are going to buy, sell, and compose work across hosts, logs and API dashboards are not enough. Froglet is an open-source protocol and node for agent-to
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In the Land of AI Agents, the Verifiers Are King — Tariq Shaukat, Sonar
As AI agents take on increasingly complex development tasks, the critical challenge has shifted from generation to verification. Hallucination is not a temporary bug. Evidence suggests that as models grow more capable, failures become more frequent and more convincing, making cognitive surrender among human reviewers a
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Your LLM Stack Is a 2008 Database With Better Marketing — Lovina Dmello, NVIDIA
In 2023, researchers found thousands of Ray clusters sitting wide open on the public internet, dashboards and job APIs exposed to anyone, because authentication ships off by default and nobody turned it on before going to production. The data at risk was worth more than a billion dollars. No zero day, no clever attack
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Can Oncology Workflows Run Without Human Touch? - Anant Shankhdhar, Risa Labs
Can Oncology Workflows Run Without Human Touch? At Risa, we automate healthcare workflows in oncology end-to-end using AI agents. We built four agents that work together , each one handles a different step, then passes its output to the next. No human needed in between. The agents when combined are able to do the work
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When Agents Meet Physical Data: The Other Physics of Agent Harnesses - Dmitry Petrov, DataChain
Ask an agent to find every night-time pedestrian frame across terabytes of dashcam video in S3. The first pass can cost thousands of dollars and run for hours or days. Once you’ve paid that cost, the agent’s favorite move - loop, inspect, re-derive - becomes the worst thing it can do. Most agent intuition comes from a
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Agentic Development Security — Ezra Tanzer, Snyk
An agent at Replit ignored a code freeze, deleted a production database, then fabricated records to hide it and reported that recovery was impossible. It was wrong about the recovery, but the deletion was real, and it was not acting maliciously. It was trying to help. That is the uncomfortable center of agentic develop
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Your Voice Agent Doesn't Need a Frontier Model - Joel Allou & Ornella Bahidika, Microsoft
My AI voice tutor doesn't run on a frontier model. It runs on a small one, and the reason isn't cost. It's that voice lives or dies on latency, and the scaffolding around the model is what makes it feel smart anyway. When you build a voice agent the clock is brutal. A pause longer than a held breath feels broken, so yo
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Voice Agents That Handle Interrupts - Chintan Agrawal and Daniel Wirjo, AWS
Chat agents get seconds to respond. Voice agents get 200 milliseconds, and if they get it wrong, the user doesn't retry, they hang up. The gap between "impressive voice demo" and "agent people actually want to talk to" is entirely in the engineering: latency budgets, barge-in handling, turn-taking, and the silence dete
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Build the AI GTM Agent That Knows the Buyer - Dr. Sajjan Kanukolanu, Position2 (Position Squared)
As part of a GTM motion, an AI agent goes live on the site. The first visitor lands. The conversation starts. That's the moment everyone optimizes for- the right conversation, the right offer etc.. It's the wrong moment. A well-built AI GTM system does something very different. By the time a buyer sends their first mes
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Don't Let the LLM Drive - Ornella Bahidika & Joel Allou, Microsoft
The LLM in my voice tutor doesn't decide when the lesson is over. It doesn't decide whether the user got the answer right. It doesn't decide which step comes next. A harness does all of that. The LLM just shows up and talks. Every engineer who's tried to ship a multi-step flow agent has felt this: the model declares it
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Agent Output Is Not UX: Rendering Layer Your LLM Pipeline Is Missing - Bala Ramdoss, Amazon Lens
Getting a model to produce the right output is the part everyone works on. Turning that output into something people will actually use is the part that decides whether an AI feature ships. This talk is about that layer, the one between model output and the product experience, grounded in lessons from building agentic C
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Why Your Agent Disagrees With Itself (And What To Do About It) - Diane Lin, Datadog
Run the same task twice, and sometimes you get two materially different answers. While many dismiss this as the "stochastic nature of LLMs," this inconsistency is a critical product flaw that destroys customer trust—especially in high-stakes fields like cybersecurity, where a "flip-flop" between a malicious threat and
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Agentic Security: Permissions, Provenance, and the Agent Supply Chain — Steve Yegge, Gas Town
A security hardening pass by Fable over a game one engineer had built for 30 years came back clean: cloud hardening done, credentials handled, good vibes all around. Then Snyk ran over the same code and surfaced 241 vulnerabilities the agent never thought to look for. That gap is the center of Steve Yegge's talk, whose
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From Tokens to Cells: Foundation Models for Single-Cell Biology - Akram Baharlouei, Altos Labs
This talk examines the engineering challenges of building foundation models for single-cell biology from a non-biologist’s perspective. Speakers: - Akram Baharlouei (Altos Labs): Machine learning engineer at Altos Labs working on foundation models for biology. Previously at Meta AI and Qualcomm. LinkedIn: https://linke
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Build Evals That Actually Matter - Nick Ung, Lyft
Your agent passes offline evals at 90%. You ship. Production immediately finds failure modes your eval never saw. Sound familiar? The culprit is almost always the same: the "customer" in your offline eval is an off-the-shelf LLM that sounds nothing like your real users, and your synthetic test set doesn't capture how m
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From Blind Spots to Merged PRs: Continuous Agentic Performance Optimization - May Walter, Hud
Performance issues silently pile up in mature codebases. Teams know things could be faster, but can never justify pausing feature work to investigate. You have to put engineers on it just to find out if there's something worth fixing, and the effort is completely unpredictable: it could take an hour or three weeks. In
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You Didn't Ship a Bug. You Just Wrote It for a Human. - Ravi Madabhushi, Scalekit
We built a demo agent to show customers how to connect agents to their tools. A simple chat assistant — Gmail, Calendar, a handful of connectors. It ran on a 15-minute schedule. And every 15 minutes, our production database strained. Latency crept up and alerts fired. Then settled. Then, it fired again. It took us a wh
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A Practitioner's Guide to Graphs - Tim Ainge, Good Collective
A speed-run through the basics... what is a graph, extracting graphs from unstructured text, schema first and ontological improvements and then a slightly more detailed discussion of personalised page rank, shortest path and subgraph matching algorithms. Every idea is explored with an explanation of the principles, and
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Stop Renting Your Cognitive Infrastructure - Thiyagarajan Maruthavanan, Kalmantic Labs
I pointed my lab at one problem, inference, after 200 users burned $1,000 in credits and the math just wouldn't close. So I built the thing, felt the cost, and went looking for why renting intelligence never pencils out. Turns out everyone in this market sells a gospel shaped like their own invoice. Jensen: build a tok
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Agents Need Receipts, Not More Tool Calls - Armanas Povilionis, Alithea Bio
In this talk, I’ll show an agent publish a service, another agent discover and invoke it, and a signed receipt that proves what happened. The point is simple: if agents are going to buy, sell, and compose work across hosts, logs and API dashboards are not enough. Froglet is an open-source protocol and node for agent-to
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The UX of AI: Making AI-Powered Apps Your Users Don't Hate - Kathryn Grayson Nanz, Progress Software
As a developer, AI is fun, exciting, and full of potential – but users don't always feel the same way about it. From a UX perspective, AI comes with a whole new set of considerations around user trust, privacy, and security. From a UI perspective, AI brings new interaction patterns, new icons, new visual cues, and so m
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Autonomous Agents for Scientific Tasks - Sina Shahandeh, Radicait
There has been much work on Autoresearch where the objectives are coding puzzles, toy optimization problems, or static supervised-learning ML tasks. However, for an autonomous agent to assist with a scientific discovery task, the problems must come from real measurement data of the world and they are highly open-ended,
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Your Agents Need a Save Button - Hamza Tahir, ZenML
Most of an agent's life is spent waiting - on a tool, a human, the next step - and the whole time you're holding a live process awake and billing for it. Multiply that across every agent your org wants to run overnight and the math stops working. A save button fixes the obvious stuff: freeze an agent to durable state,
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Stop Burning Tokens: Why self-improvement needs domain expertise first - Annabell Schäfer, Langfuse
We ran auto-improvement loops on a paper classification task against a ground-truth dataset. A real problem, narrow enough to measure precisely, and in fact one of the few clear cut target functions out there. We’ll share how to properly set up an agent for auto-improvement, what task specificity and target function qu
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Content Is Code - Matt Palmer, Conductor
Code has become the fastest medium for producing technical content, but the most important piece isn't a secret agent skill or a magical framework: its the same thing that makes a great developer experience. Speakers: - Matt Palmer (Conductor): Matt Palmer is a DevRel & product leader focused on AI devtools, developer
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Agents Need Feature Flags - Sachin Gupta
Most AI teams ship behavior changes to 100% of users on every deploy — no canary, no segment, no kill switch. Web teams stopped doing this in 2012. AI teams are about to learn why. Feature flags are table stakes in software engineering. In agent systems they're almost nonexistent — prompts, tool access, model selection
Introducing Gemini 3.5 Flash Cyber
Google introduces Gemini 3.5 Flash Cyber, a lightweight cybersecurity model to find and patch vulnerabilities.
New NadMesh Botnet Hunts Exposed AI Services for Cloud Keys and Kubernetes Tokens
XLab observed the Go-based NadMesh botnet scan internet-exposed ComfyUI, Ollama, n8n, Open WebUI, Langflow, Gradio, and MCP services for cloud keys, Kubernetes tokens, Docker credentials, and callable tools. MCP command execution appeared in observed traffic, although most exploitation targeted conventional Docker and Jenkins exposures and the operator dashboard’s scale claims were internally inconsistent.
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"Software engineering is not about writing code" — Benoit Schillings, Google DeepMind VP of Research
A keynote exploring generative AI for code, deep-thinking algorithms, and the future of pre-training and transformer models for Gemini. Speaker: Benoit Schillings leads the Thinking, Reasoning, and Coding teams at Google DeepMind, directing foundational research toward AGI. His work focuses on advancing next-generation
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Claude for Long-Horizon Tasks — Lance Martin, Anthropic
Claude is capable of long horizon tasks. In this talk, we'll share lessons learned about building agent harnesses for reliable and secure long-horizon work. This include decoupling the brain and hands, self-verification, self-learning, and design for evolving agent harnesses. ### Lance Martin Member of Technical Staff
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On AI and Knowledge — Pablo Castro, Distinguished Engineer & CVP for AI Knowledge, Microsoft
Pablo Castro explores AI and knowledge systems for building better applications and agents. Speaker: Pablo Castro —Distinguished Engineer and CVP, Microsoft, leads the AI Knowledge team in Microsoft's CoreAI division, where he focuses on state-of-the-art information understanding and retrieval systems for AI applicatio
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The Great Loops Debate — Dex Horthy, Geoff Huntley, Ian Livingstone, Greg Pstrucha, @insecure-agents
Oxford Style Debate: There is, or is not, a delta between the hype behind loops and what actually works in practice. Team No Delta (pro the way we do loops today) The hype around loops is valid and loops work well today in practice. Loops today can be a silver bullet and result in outsize productivity gains, and marks
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The New Physics of Business — Garry Tan, Y Combinator
Garry Tan argues that AI-native companies can give small teams operating leverage previously associated with much larger organizations, changing how founders think about staffing, capital, automation, and the pace of execution.
Cloud CISO Perspectives: How AI leverages deep context as the defender’s advantage
Google Cloud argues that defenders can use enterprise context—assets, identities, application behavior, ownership, and telemetry—to support an AI-assisted cycle of preparing, prioritizing, remediating, and monitoring security risk.
AI Can Find Bugs, But Human Knowledge Still Proves Them
The Hacker News argues that AI can accelerate code review, payload generation, attack-surface analysis, and repetitive testing, but its output remains a lead until a practitioner proves reachability, boundary crossing, reproducibility, and concrete impact in the target environment.
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Imagination Engineering — Eve Bouffard, Head of Design, Y Combinator
Eve Bouffard presents “imagination engineering” as a design practice for exploring more ambitious product ideas when AI reduces the cost of prototyping and technical execution.
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An AI Agent Became the #1 Contributor in OpenAI's Hiring Challenge — Zhengyao Jiang, Weco
Zhengyao Jiang describes Weco’s autonomous research agent Aiden participating in OpenAI’s Parameter Golf challenge, where competitors trained small language models under a 16 MB constraint and the agent contributed multiple accepted improvements.
TuxBot v3: Inside an IoT Botnet Framework With LLM-Assisted Development
Unit 42 analyzes TuxBot v3 Evolution, a roughly 70%-functional IoT botnet framework with code compiled for 17 architectures. Researchers found raw model reasoning, hallucinated cryptography, and other evidence of unreviewed LLM-generated code in the source.
Authenticate legitimate AI agent traffic with AWS WAF Bot Control
AWS explains how Web Bot Authentication uses HTTP Message Signatures and published public keys to verify automated agents in WAF Bot Control, then exposes verification labels for allow, block, rate-limit, and monitoring rules.
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POC Prison: Why agentic systems never escape the lab and how to fix that in 90 days - Luise Freese
This talk was recorded at NDC Copenhagen in Copenhagen, Denmark. #ndccopenhagen #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndccopenhagen.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.f
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Put an Agent Inside Your App in 10 Minutes or Less with the GitHub Copilot SDK - Daniel Ward
This talk was recorded at NDC Copenhagen in Copenhagen, Denmark. #ndccopenhagen #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndccopenhagen.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.f
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Platform Engineering in the age of Generative AI -
This talk was recorded at NDC Copenhagen in Copenhagen, Denmark. #ndccopenhagen #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndccopenhagen.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.f
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Building an AI-Powered Personal Companion Mobile App - Gerald Versluis - NDC Copenhagen 2026
This talk was recorded at NDC Copenhagen in Copenhagen, Denmark. #ndccopenhagen #ndcconferences #developer #softwaredeveloper Attend the next NDC conference near you: https://ndcconferences.com https://ndccopenhagen.com/ Subscribe to our YouTube channel and learn every day: / @NDC Follow our Social Media! https://www.f
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.
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HitchHacker's Guide to Building Secure Agents - Kenneth Yeung & Kasimir Schulz
Conference talk on secure AI agents, focusing on how tool use, identity, and execution boundaries change when assistants can act across systems.
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AI Engineer World's Fair 2026 Day 2 Livestream
Live from San Francisco, AI Engineer World’s Fair 2026 continues with Day 2 of session programming from the main stage. Watch live for keynote sessions, main-stage programming, and more from World’s Fair 2026 as AI Engineer brings another full day of AI engineering content to viewers online. Event: AI Engineer World’s
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AI Engineer World's Fair 2026 Day 3 Livestream
Live from San Francisco, AI Engineer World’s Fair 2026 wraps with the final day of main-stage programming. Watch live for keynote sessions, featured talks, and closing-day highlights from World’s Fair 2026 as AI Engineer streams the final day of the event online. Event: AI Engineer World’s Fair 2026 Date: Thursday, Jul
Introducing computer use in Gemini 3.5 Flash
Google integrated computer use into Gemini 3.5 Flash so agents can act across browser, mobile, and desktop environments. Optional enterprise safeguards can require confirmation for sensitive actions or stop a task when indirect prompt injection is detected.
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10 tips to level up your AI-assisted coding - Aleksander Stensby - NDC Copenhagen 2026
NDC Copenhagen 2026 talk on AI-assisted coding with Cursor and Claude Code, covering prompting, context engineering, testing, debugging, daily workflow integration, and MCP connections to developer tools.
Securing the future of AI agents
Google DeepMind post on security requirements for AI agents. Relevant to alignment between autonomy, permissions, sandboxing, evaluation, and operational control design.
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.
Investing in multi-agent AI safety research
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
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.
Introducing Gemma 4 12B: a unified, encoder-free multimodal model
Google introduced Gemma 4 12B, an Apache 2.0 model that accepts text, vision, and native audio without separate multimodal encoders. It targets local agentic workloads and can run on laptops with 16 GB of memory.
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.
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.
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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
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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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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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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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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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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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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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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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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.
Decoupled DiLoCo: A new frontier for resilient, distributed AI training
Google DeepMind’s Decoupled DiLoCo divides model training into asynchronous compute islands across data centers. Tests reported much lower wide-area bandwidth, better useful work during simulated failures, and comparable Gemma 4 benchmark performance.
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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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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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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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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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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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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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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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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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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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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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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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
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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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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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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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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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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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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.
![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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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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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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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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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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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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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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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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Beyond the Prompt: Evaluating, Testing, and Securing LLM Applications - Mete Atamel
NDC Copenhagen talk on evaluating, testing, and securing LLM applications, including RAG changes, prompt-injection resilience, harmful-response guardrails, Promptfoo, DeepEval, Vertex AI Evaluation, and LLM Guard.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
![[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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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#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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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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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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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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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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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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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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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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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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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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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.
![[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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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(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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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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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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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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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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"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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
![[Evals Workshop] Mastering AI Evaluation: From Playground to Production video thumbnail](https://i.ytimg.com/vi/9iN-cPnp7xg/hqdefault.jpg)
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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.
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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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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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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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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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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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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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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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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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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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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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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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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.
![[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.
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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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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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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.
![[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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
![[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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
![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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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 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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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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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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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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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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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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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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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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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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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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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 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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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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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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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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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[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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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[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.
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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[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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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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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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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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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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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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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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[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.
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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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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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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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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 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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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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[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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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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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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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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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 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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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.