Prompt engineering

[404] – Developer Not Found: The Continuing Developer Evolution • Derek Bingham • YOW! 2025

[404] – Developer Not Found: The Continuing Developer Evolution • Derek Bingham • YOW! 2025

Derek Bingham explores the rapid evolution of developer tools with AI, from coding assistants to autonomous agents. He emphasizes the shift from prompt engineering to context engineering, introduces Spec-Driven Development (SDD) as a framework for quality AI-generated code, and dispels fears about AI replacing developers, arguing instead for increased demand and the necessity of new skills like ethical and systems thinking.

Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google

Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google

Michael Hablich from the Chrome DevTools team shares hard-won engineering lessons on building effective and secure interfaces for AI agents. The talk covers moving from raw data to semantic summaries, measuring interface efficiency with 'tokens per successful outcome', designing for error recovery, and the critical importance of trust boundaries and deliberate friction in UI design for agents.

AI at college graduations and why Claude blackmails

AI at college graduations and why Claude blackmails

The Mixture of Experts team discusses the growing skepticism towards AI among younger generations, a Microsoft study revealing how LLMs can corrupt data in complex workflows, Anthropic's data-centric fix for Claude's "blackmailing" issue, and the cultural debate over an AI-generated story potentially winning a literary prize, all circling the central themes of human ownership, trust, and the need for better processes in the age of AI.

Build Agents That Run for Hours (Without Losing the Plot) — Ash Prabaker & Andrew Wilson, Anthropic

Build Agents That Run for Hours (Without Losing the Plot) — Ash Prabaker & Andrew Wilson, Anthropic

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.

Fighting AI with AI — Lawrence Jones, Incident

Fighting AI with AI — Lawrence Jones, Incident

Lawrence Jones from Incident.io explains why their team needed AI to debug their complex AI SRE product. He details three powerful patterns: a CLI for agents to manage large evaluation files, serializing debug UIs into downloadable file systems for agent-based tracing, and multi-agent pipelines for fleet-scale failure analysis.

Inside image generation’s Renaissance moment — the OpenAI Podcast Ep. 19

Inside image generation’s Renaissance moment — the OpenAI Podcast Ep. 19

Product lead Adele Li and researcher Kenji Hata from OpenAI discuss the significant advancements in Images 2.0, covering breakthroughs in photorealism, text rendering, and multilingual support. They explore new productivity and creative use cases, the evaluation process, and the future of image generation as a creative assistant.