Explore advanced techniques for building long-running AI agents, moving beyond simple loops. Learn why self-evaluation fails and adversarial evaluators succeed, how to manage context with structured handoffs instead of just compaction, and how to use negotiated 'sprint contracts' and detailed rubrics to build and test complex, full-stack applications autonomously.
Danilo Campos of PostHog details the common failure modes of LLM-based code generation—from model rot to security risks—and shares the practical, prose-driven strategies his team uses to make their autonomous coding agent reliable for thousands of users.
Eric Zakariasson from Cursor explains the shift from single-agent pair programming to managing a multi-agent "software factory". He outlines the practical steps required, from establishing a well-structured codebase with guardrails to adopting a managerial mindset that focuses on automation, asynchronous work, and scaling agent fleets to increase software development throughput and consistency.
![[FULL WORKSHOP] AI Coding For Real Engineers - Matt Pocock, AI Hero (@mattpocockuk )](https://img.youtube.com/vi/-QFHIoCo-Ko/maxresdefault.jpg)
A workshop on building a complete AI-assisted development workflow, covering how to translate ambiguous requirements into agent-ready plans and run autonomous coding agents to ship production-ready features.
Henrik Kniberg shares practical experiences from over two years of AI agent development, defining agents as autonomous entities with missions, tools, and an LLM brain. He covers effective design patterns, architectural insights, and safety considerations, emphasizing the importance of human-in-the-loop collaboration and iterative development to build agents that are not just powerful, but genuinely useful in real-world scenarios.
Jason Martin of HiddenLayer discusses the significant security vulnerabilities of OpenClaw, a viral open-source AI personal assistant. The analysis covers critical flaws like prompt injection, insecure defaults, and the potential for creating sophisticated botnets, offering key lessons for securing the next generation of autonomous AI agents.