Rethinking the Agent Harness

This week, host Eric Freeman and John Berryman, founder of Arcturus Labs, coauthor of Prompt Engineering for LLMs and an early production engineer on GitHub Copilot, cover the week's biggest AI developments: Anthropic's decision to restrict its Mythos model after it identified critical security flaws, the White House's possible pivot to FDA-style AI review, and the staggering compute deals reshaping the industry, including a 40,000-acre Utah data center planned for nine gigawatts of power.

Berryman then takes you through four years of AI product development, from tiny 2,048-token context windows to today's agent harnesses, and shows why the gap between a bare model and a well-designed harness now drives more performance than any model benchmark. He also demos a personal agent that carries context from an Obsidian notebook into Wikipedia, giving a glimpse of how a future open agent protocol might work, and explains how he helped a client replace an entire bespoke application with a skills-driven agent that domain experts can read and fix themselves, in plain English, no developer required.

If you build with AI or make decisions about AI tooling, this episode covers the infrastructure, policy, and architectural shifts you need to understand right now.