Anthropic's Boris Cherny, creator of Claude Code, discusses the paradigm shift from traditional coding to agentic workflows. He covers the co-evolution of models and their "harnesses," the importance of "hackability" via features like slash commands, and provides practical tips for leveraging coding agents for tasks of varying complexity.
Daniel Terhorst-North explores the learnable traits of great programmers, challenging the notion of innate talent. He outlines a three-part framework focusing on effective execution, selecting appropriate tools, and fostering a psychologically safe team environment, emphasizing that greatness is achieved through deliberate practice and a focus on product and people over code.
Dexter Horthy of Human Layer explains why naive AI coding agents fail in complex software projects and introduces 'Advanced Context Engineering.' He details a spec-first, three-phase workflow (Research, Plan, Implement) designed to manage context intentionally, keeping utilization below 40% to maximize model performance. This approach uses subagents and frequent compaction to turn AI from a prototyping tool into a production-ready system for large, brownfield codebases.
David Edoh-Bedi, a Developer Advocate at Stripe, shares his journey from growing up in Togo to working on large-scale systems like Windows at Microsoft and eventually transitioning into developer relations. The conversation covers the essential skills for DevRel, the hidden complexities of global payment systems, and the evolution of software development from libraries to API-centric architectures.
Drawing from conversations with top AI builders, Dex argues that production-grade AI agents are not magical loops but well-architected software. This talk introduces "12-Factor Agents," a methodology centered on "Context Engineering" to build reliable, high-performance LLM-powered applications by applying rigorous software engineering principles.
Greg Brockman discusses his journey from a math enthusiast to a programmer, his early days scaling Stripe, and the core philosophies that drive OpenAI. He covers the critical partnership between research and engineering, the future of coding with agentic systems, and the immense infrastructure and algorithmic challenges on the path to AGI.