Controls and attack paths for browsing, tool use, memory, identity, and action-taking agents.
Agent security is about what happens when AI systems can browse, use tools, remember state, and take actions across multiple steps. The security boundary moves from a chat response to a longer workflow with identity, permissions, memory, and operational consequences.
These items are included because they add useful evidence, framing, implementation detail, or upcoming context for teams working in this area.
GAISS 2026 is an IEEE conference at the University of Texas at Austin focused on generative AI for secure systems, including red teaming, blue-team automation, governance, and agentic secure AI.
IAPP Privacy. Security. Risk. + AI Governance Global 2026 brings privacy, cybersecurity law, technology, and AI governance professionals together in Seattle.
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 brings agent and MCP builders to Amsterdam to cover agent architectures, protocols, infrastructure, security, observability, and interoperability.
Black Hat USA 2026 includes an AI Summit and security briefings in Las Vegas focused on how artificial intelligence is changing digital defense.
We’re open-sourcing k8s-aibom, a Kubernetes controller that continuously monitors environments to detect AI runtimes and generate standard ML-BOMs.
Give an AI assistant a memory and access to your inbox, and you hand an attacker a way to rewrite what it thinks it knows about you. A single email can trick that agent into saving a false "fact" about the user, hide the change, and quietly steer its answers in later sessions. When it works, the person reads an ordinar
A few days ago, I was sitting with the CISO of a Fortune 50 company, walking through how his security team was thinking about AI agents in the SOC. Smart team. Serious program. They had already connected Claude to a few detection tools and were seeing real value in specific investigations. But as we mapped out the broa
The U.K. Treasury has designated Google Cloud EMEA as a critical third party (CTP) to the U.K. financial sector under the CTP regime. Here’s how that helps you.
Details have emerged about three now-patched security flaws in the OpenClaw personal artificial intelligence (AI) assistant that, if successfully exploited, could enable credential theft, privilege escalation, and arbitrary code execution on the host. A brief description of the high-severity vulnerabilities is as follo
Microsoft’s latest Secure Future Initiative report outlines progress on secure foundations, AI-powered defense, and future-ready cybersecurity. The post Securing our future: July 2026 progress report on Microsoft’s Secure Future Initiative appeared first on Microsoft Security Blog .
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What a week in AI, for real. GPT 5.6 may actually beat Claude Fable, in what you get for your money, while the new Grok 4.5 and Meta Muse Spark 1.1 make the choice even harder. Uncovering a dozen nuggets of gold you may have missed from all the viral headlines, I can also assure you you’ll learn something you didn’t kn
Ask an AI coding agent to scan open-source code for security holes, and it might run the attacker's code on your own machine instead. That is the finding in a proof-of-concept published Wednesday by the AI Now Institute, an attack it calls "Friendly Fire." It works against Anthropic's Claude Code and OpenAI's Codex whe
Researchers at Wiz found that a flaw in six popular AI coding assistants lets a booby-trapped code project quietly take control of a developer's computer. The assistant asks permission to edit one harmless-looking file, but the write lands on a sensitive one instead. The affected tools are Amazon Q Developer, Anthropic
Two announcements on July 7, 2026, demonstrate the government’s determination to improve the level of cybersecurity within the UK. The post UK Government Rolls Out Agentic AI Defense Plan Alongside Industry Pledge appeared first on SecurityWeek .
System prompts form the foundation of generative AI applications. A system prompt is a collection of instructions and operational context provided to a large language model (LLM) that shapes how the model behaves and interacts with users and tools. System prompts often contain proprietary information, including role de
Our flagship Google for Startups program, Gemini Startup Forum: Cybersecurity, has selected its first 33 trailblazing startups.
Note: the modeling assumptions and conclusion are Thomas Kwa’s opinion, and others at METR disagree. 1 Also, the math was checked by Claude but not a second human. Introduction Anthropic’s RSI blog post reported that in Q2 2026, Anthropic contributors merged 8× as much code per day as in the 2021-2024 period. What does
Sophos looked at a week of its own endpoint data and found that AI coding agents such as Claude Code, Cursor, and OpenAI Codex are setting off detection rules written to catch human intruders. The agents are not malicious. They just do a lot of things that, to a behavioral engine, look exactly like an attack. Decryptin
The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Tuesday added four security flaws to its Known Exploited Vulnerabilities (KEV) catalog, citing evidence of active exploitation. The vulnerabilities are listed below - CVE-2026-48282 (CVSS score: 10.0) - A path traversal vulnerability in Adobe ColdFusio
An AI coding assistant that refuses to answer a dangerous request in its chat box can answer it anyway if the same request is broken into small, ordinary-looking steps inside a code editor. That is the finding of a new study of GitHub Copilot by researchers Abhishek Kumar and Carsten Maple. The models they tested throu
Researchers show how attackers can use a crafted public GitHub Issue to trick AI-powered workflows into exposing data from private repositories without authentication. The post Critical Vulnerability Exposes GitHub Agentic Workflows to Prompt Injection appeared first on SecurityWeek .
With the introduction of models that require data sharing with third-party providers—such as Claude Fable 5—organizations need a way to centrally enforce data retention policies. Amazon Bedrock gives you control over whether your prompts and model outputs are retained after an inference request completes. You might nee
To help you match your real-world exposures with real-time adversary activity, we’ve begun integrating Google Threat Intelligence with Wiz Attack Surface Management.
A public issue can trick GitHub Agentic Workflows into leaking the contents of an organization's private repositories, researchers at Noma Security have shown. The attacker needs only to open a normal-looking issue on a public repository, with no stolen credentials and no access to the organization. If that organizatio
Cybersecurity researchers have disclosed details of a now-patched critical session isolation vulnerability in Writer, an enterprise generative artificial intelligence (AI) platform, that could result in cross-tenant compromise. The one-click vulnerability has been codenamed WriteOut by the Sand Security Research team.
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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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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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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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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
July's security digest covers the critical MCP vulnerabilities, real-world MCP exploitation, NSA's official MCP hardening guidelines. Explore these essential resources and secure our MCP servers. The post Top MCP security resources — July 2026 first appeared on Adversa AI .
Read five key learnings from the Frost & Sullivan 2025 Frost Radar™ for CSPM to learn how CSPM is evolving from point-in-time compliance to continuous risk management. The post 5 insights from Frost & Sullivan’s 2025 Frost Radar™ for Cloud Security Posture Management appeared first on Microsoft Security Blog .
We’re running Patch the Planet , an ongoing collaboration with OpenAI that pairs Trail of Bits engineers directly with more than 30 open-source projects. Its goal is to front-run a serious problem facing open-source maintainers: highly capable models like GPT-5.5-Cyber will soon create a firehose of bug reports, and OS
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Fable 5 (newly re-released) vs GPT 5.6 Sol, what comparisons can we unearth? Plus, Sonnet 5, a 5% equity seizure by US Govt, the ‘largest heist’, Beetlejuice and more… Exclusive Vids in AI Insiders ($9!): https://www.patreon.com/AIExplained Chapters: 00:00 - Introduction 01:06 - Fable Timeline 02:59 - Sol Release? 06:0
Unit 42 analysis of phantom squatting: attackers register domains that LLMs may hallucinate in recommendations, code, documentation, or support answers. That turns model error into a supply-chain path, especially when users or agents follow generated links without independent validation.
Frost & Sullivan names Microsoft a leader as cloud and application security converge into unified, runtime risk reduction. The post Microsoft named a leader in the Frost Radar for cloud and application runtime security appeared first on Microsoft Security Blog .
Wiz post on AI threat readiness and secure-by-default cloud operations in a faster vulnerability environment. The value for this library is the platform-security angle: AI-era systems need inventory, exposure reduction, posture management, and rapid remediation built into normal operating practice.
METR pre-deployment evaluation summary of a frontier model, emphasizing independent assessment, capability evidence, and launch-risk considerations. Relevant to model evaluation and safety gating.
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Conference talk on secure AI agents, focusing on how tool use, identity, and execution boundaries change when assistants can act across systems.
Agent skill marketplaces introduce supply-chain risk when third-party skills can execute actions or collect data. Relevant to vetting, provenance, and containment controls.
Vendor guidance on operationalizing AI-enabled detection and response. Useful as an implementation signal for monitoring, containment, and response workflows around AI-influenced threats.
Earlier this month, I spoke at the Gartner Security & Risk Management Summit about a blind spot most security programs are still not accounting for - how attackers are circumventing AI security programs by using legacy infrastructure to hijack AI agents. AI adoption is moving faster than security programs can account f
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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.
Google DeepMind post on security requirements for AI agents. Relevant to alignment between autonomy, permissions, sandboxing, evaluation, and operational control design.
From defending networks to enabling attacks, artificial intelligence is changing every aspect of cybersecurity. Here's what dozens of experts say security leaders need to understand now. The post AI and Cybersecurity – Everything You Wanted to Know, But Were Afraid to Ask appeared first on SecurityWeek .
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Claude Fable 5 banned, but what’s the bigger story. We go through 11 under-reported details, so you have the context to see what’s coming next for your use of AI. From whether the ban will last, what the possible motives are, what the model can actually do, and some wild over-extrapolations going on. Check out my fast-
OpenAI update on European trustworthy-AI work and governance engagement. Relevant to standards, assurance, and regulatory coordination for deployed AI systems.
Two security teams have shown, in separate research published this week, that OpenClaw, the popular self-hosted AI agent, can be driven to run attacker-controlled code or hand over sensitive data through ordinary-looking inputs. Imperva buried instructions inside shared contacts, vCards, and location pins that the agen
Vendor guidance on AI-assisted code analysis. Relevant as an implementation pattern for integrating code-scanning, remediation, and AI development workflows into operational security.
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
Cloudflare describes architecture and operational lessons for defending against frontier cyber models. Relevant to AI-enabled threat modeling, defensive controls, and internal security readiness.
Anthropic red-team research assessing how LLMs affect exploitation of known vulnerabilities. Relevant to cyber capability evaluation, benchmark design, and misuse risk modeling.
Anthropic and Verizon mapping of AI-enabled cyber activity to MITRE ATT&CK. Relevant to threat modeling, red-team scenario design, and structured reporting of AI-enabled operations.
Gartner Security & Risk Management Summit 2026 brings CISOs and security leaders together in National Harbor, Maryland, with tracks covering AI, cyber risk, application security, data security, operations, privacy, and governance.
ACM CAIS 2026 is a research-focused conference on compound AI architectures, optimization, deployment, and agentic AI systems in San Jose, California.
Anthropic evaluation of model performance on exploit-development benchmarks. Relevant to cyber capability measurement, safety thresholds, and model release risk.
Anthropic reports early Project Glasswing results using Mythos Preview with infrastructure partners and external testers, including large-scale vulnerability discovery and a cautious disclosure posture.
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.
METR report summarizing frontier model risk observations across February and March 2026. Relevant to external evaluation, risk monitoring, and pre-release assurance practices.
Cloudflare report on testing security-focused frontier models against real infrastructure code. Relevant to evaluating AI-assisted vulnerability discovery and production security workflows.
Gemini 3.5 is built to help you execute complex, agentic workflows.
OWASP analysis of memory and context poisoning as an agent attack surface. Relevant to persistent state, trust boundaries, and regression tests for agent memory.
NVIDIA AI Red Team post on grammar-constrained decoding for Bash generation in small language models. Relevant to safer command generation and executable-output controls.
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NDC Security 2026 talk on securing agentic systems through reference architecture, common risk analysis, and control prioritization for autonomous agents in the software development lifecycle.
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GPT 5.5 full analysis, plus DeepSeek V4 paper highlights, comparisons with Mythos, a vibe-coded game w/ GPT Image 2, and 50 data-points you wouldn’t get from just reading the headlines. https://80000hours.org/aiexplained Check out my fast-growing (!) app, free to use, and code INSIDER15 for paid tiers: https://lmcounci
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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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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.
Cloudflare article on accountability models as AI assistants and privacy proxies blur bot and human distinctions. Relevant to agent identity, abuse prevention, and web access controls.
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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.
NVIDIA guidance on mitigating indirect AGENTS.md injection in agentic coding environments. Relevant to instruction provenance, repository trust, and sandboxed automation.
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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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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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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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Attacking AI is a one of a kind session releasing case studies, tactics, and methodology from Arcanum’s AI assessments in 2024 and 2025. While most AI assessment material focuses on academic AI red team content, “Attacking AI” is focused on the task of assessing AI enabled systems.
Announcement of a hands-on CTF for agentic AI security in a financial-services scenario. Relevant to training, scenario design, and practical red-team exercises.
OWASP roundup of reported GenAI incidents and exploit patterns from Q1 2026. Relevant as a threat-intelligence reference for risk tracking and test-case design.
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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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AI Engineer session on Agentic Engineering: Working With AI, Not Just Using It, presented by Brendan O'Leary. It adds practical context for how teams are building and operating AI systems in production.
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AI 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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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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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 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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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Claude Mythos Preview is a new general-purpose language model that is strikingly capable at computer security tasks. This post provides technical details for researchers and practitioners who want to understand exactly how we have been testing this model, and what we have found over the past month. We hope this will sh
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NDC Security 2026 talk on prompt injection in CI/CD and automation systems, including AI agents with access to shell commands, GitHub or GitLab tokens, issue editing, build workflows, and privileged pipeline context.
Microsoft Incident Response explains how to detect prompt abuse using logging, telemetry, and incident response workflows.
OpenAI frames prompt injection as an agent-security problem that increasingly resembles social engineering rather than simple string matching.
This post dives deep into how Claude wrote an exploit for one of the vulnerabilities it found in Firefox.
In a collaboration with researchers at Mozilla, Claude Opus 4.6 discovered 22 Firefox vulnerabilities over the course of two weeks.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
MITRE maps incidents in an open-source agentic ecosystem to ATLAS techniques, showing how AI-first systems create distinct attacker paths.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
AI models can now find high-severity vulnerabilities at scale. This is a moment to empower defenders. We're now using Claude to find and help fix vulnerabilities in open source software.
NVIDIA guidance on sandboxing agentic workflows and managing execution risk. Relevant to tool isolation, approvals, filesystem boundaries, and operational controls for coding agents.
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NDC AI 2025 talk on breaking AI systems in production, covering prompt injection, hidden prompts in documents, agent goal manipulation, privacy exposure, and practical AI red-team testing methods.
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NDC AI 2025 talk on prompt-jacking in AI coding assistants, using Cursor vulnerability examples, hidden text in codebases, agentic behavior shaping, data exfiltration, and supply-chain style propagation.
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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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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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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.
![Claude Agent SDK [Full Workshop] — Thariq Shihipar, Anthropic video thumbnail](https://i.ytimg.com/vi/TqC1qOfiVcQ/hqdefault.jpg)
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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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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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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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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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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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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.
In a recent evaluation of AI models’ cyber capabilities, current Claude models can now succeed at multistage attacks on networks with dozens of hosts using only standard, open-source tools, instead of the custom tools needed by previous generations.
Ensuring that programs are bug-free is one of the most challenging aspects of software engineering. We developed an agent that can efficiently identify bugs in large software projects. Our agent infers general properties of code that should be true, and then applies property-based testing. After extensive manual valida
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
AI could help defenders of critical infrastructure identify the vulnerabilities that attackers might exploit—and close them before they are exploited. Anthropic has partnered with Pacific Northwest National Laboratory (PNNL) to explore this defensive application of AI, demonstrating both the potential of AI-accelerated
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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 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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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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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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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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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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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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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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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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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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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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AI Engineer session on Agents are Robots Too: What Self-Driving Taught Me About Building Agents, presented by Jesse Hu, Abundant. It adds practical context for how teams are building and operating AI systems in production.
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AI 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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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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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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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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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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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
OpenAI describes using automated red teaming and reinforcement learning to discover agent prompt injection attacks before they appear in the wild.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
In June, we revealed that we'd set up a small shop in our San Francisco office run by an AI shopkeeper. It did not do particularly well. We made some adjustments for phase two of Project Vend. The idea of an AI running a business doesn't seem as far-fetched as it once did. But the gap between 'capable' and 'completely
Google Cloud outlines a defense-in-depth view of AI security spanning application controls, data protections, and infrastructure isolation.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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AI Engineer session on Agents vs Workflows: Why Not Both?, presented by Sam Bhagwat, Mastra.ai. It adds practical context for how teams are building and operating AI systems in production.
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AI 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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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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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.
![[Full Workshop] Building Conversational AI Agents - Thor Schaeff, ElevenLabs video thumbnail](https://i.ytimg.com/vi/MPtCBaZn84A/hqdefault.jpg)
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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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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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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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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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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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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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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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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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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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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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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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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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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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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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AI Engineer session on Agents, Access, and the Future of Machine Identity, presented by Nick Nisi (WorkOS) + Lizzie Siegle (Cloudflare). It adds practical context for how teams are building and operating AI systems in production.
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AI 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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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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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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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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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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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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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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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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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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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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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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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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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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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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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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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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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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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.
Google’s CISO perspective on why agents need a new security paradigm and what changes when models can observe, plan, and act.
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AI 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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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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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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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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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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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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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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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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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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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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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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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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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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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 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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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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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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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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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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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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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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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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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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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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AI Engineer session on AI Agents, Meet Test Driven Development. It adds practical context for how teams are building and operating AI systems in production.
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AI 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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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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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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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 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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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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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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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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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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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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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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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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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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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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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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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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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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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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AI Engineer session on Agentic Workflows on Vertex AI: Rukma Sen. It adds practical context for how teams are building and operating AI systems in production.
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AI 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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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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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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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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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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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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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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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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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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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
Google introduced AI Protection and Model Armor to address prompt injection, jailbreaks, data loss, and multicloud AI workload security.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
The Operator system card documents red teaming and mitigation choices for a computer-using agent, with prompt injections listed as a central risk area.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
Microsoft summarizes lessons from red teaming more than one hundred generative AI products, emphasizing system-level testing, human expertise, and automation.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
OWASP’s GenAI security project remains a practical baseline for teams building or assessing LLM applications and agentic systems.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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AI 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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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of governance and responsible deployment. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.
![Can GPT 4 Prompt Itself? MemoryGPT, AutoGPT, Jarvis, Claude-Next [10x GPT 4!] and more... video thumbnail](https://i.ytimg.com/vi/6NoTuqDAkfg/hqdefault.jpg)
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This AI Explained video reviews a major AI development through the lens of agentic workflows and tool-use risk. It is useful context for AI engineering, evaluation, governance, and operational risk.