Progressive disclosure

Oct 07, 2026

From 36% to 100%: How Self-Improving Agents Write Their Own Skills — Rafal Wilinski, Runlayer

Rafal Wilinski of Runlayer argues that when one agent solves a hard problem, that knowledge should become a skill shared across the whole company. He covers why skills matter more as agents run longer, three problems with current skills, using MCP as a governed distribution layer, distilling skills from successful and failed agent traces inspired by the Voyager paper, and the organizational flywheel as a durable competitive advantage.

Aug 11, 2026

Agents, codebases, and teams — Aditya Khandelwal, Amazon AGI Lab

Aditya Khandelwal argues that scaling AI agent adoption within engineering teams is a leadership challenge, not an individual contributor problem. He highlights common pitfalls like agent "babysitting" and "slop," and provides a playbook emphasizing progressive disclosure, high-value automation, robust feedback loops, and a critical mindset shift to successfully integrate agents into team workflows.