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.
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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-
We are thrilled to collaborate with Apple on its expanded Private Cloud Compute (PCC) systems announced this week at WWDC 2026.
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
Adaptive Spec-driven Scoring for Evaluation and Regression Testing (ASSERT) is an open-source framework for converting natural language behavior requirements into executable evaluations of AI models and agents. The post Turn specs into evals for any agent with ASSERT appeared first on Microsoft Security Blog .
Google DeepMind and partners announce a $10M funding call for multi-agent safety research.
On June 9, Anthropic released Claude Fable 5, the most capable model it has ever made, generally available. It also did something unusual: it shipped one model as two products, split not by capability but by a layer of safety classifiers. Fable 5 goes to the public. Its twin, Claude Mythos 5, the same underlying model
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Fable 5 is out - and it’s good, very good. But beyond the splashy demos, I want to bring you the 20+ nuggets from the 319 page system card, which I read in full, all day, plus benchmarks you may not have noticed. https://assemblyai.com/aiexplained Plus two worrying trends inside the ‘mind’ of Claude, how OpenAI counter
Learn how Google Security Operations works in concert with AI Threat Defense to monitor, detect, and respond to threats, particularly from code you do not own or can not patch.
Learn how to investigate AI activity in Microsoft 365 Copilot and Azure AI services using a structured, telemetry-driven approach. This playbook helps security teams reconstruct events, assess data exposure, and detect potential threats faster. The post Reconstructing AI activity in investigations appeared first on Mic
As threat actors operationalize AI to accelerate attacks, they are also leveraging the wider global interest around AI itself as a social engineering lure. The post AI brands as bait: How threat actors are using the AI hype in social engineering appeared first on Microsoft Security Blog .
Microsoft Threat Intelligence identified a prompt injection pathway in Claude Code GitHub Action that allowed access to workflow secrets under specific conditions. This research examines the attack chain, responsible disclosure process, Anthropic's mitigation, and guidance for securing AI-powered CI/CD workflows. The p
A surge in real-world attacks against agentic AI systems is reshaping how we think about risk. Based on 12 months of red teaming, this update introduces seven new failure modes, from supply chain compromise to goal hijacking, and the practical mitigations teams need now. The post Updating the taxonomy of failure modes
A large-scale npm supply chain attack compromised over 90 versions of @redhat-cloud-services packages, silently infecting CI/CD environments and developer systems. The malicious code steals credentials from GitHub, cloud platforms, and local machines, then spreads like a worm by republishing trusted packages. Discover
Discover how Microsoft enables fast, secure AI development with MDASH and new security capabilities. The post Microsoft Build 2026: Securing code, agents, and models across the development lifecycle appeared first on Microsoft Security Blog .
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.
From industrial control systems to decades-old municipal databases, here’s our CISO guidance to prep AI-ready security programs for the public sector.
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The ‘best’ generally available AI model just dropped, but there is plenty I bet you missed about what it is, how it performs, and what the release tells us. 15 highlights from the 244 page system card, plus private testing, leader interview and more. AI Insiders ($9!): https://www.patreon.com/AIExplained Chapters: 00:0
ACM CAIS 2026 is a research-focused conference on compound AI architectures, optimization, deployment, and agentic AI systems in San Jose, California.
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.
Gemini 3.5 is built to help you execute complex, agentic workflows.
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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.
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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.
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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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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
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.
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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.
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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.
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.
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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.