From Stateless to Self-Improving: Building Agent Workflows That Get Better Every Session

Most AI coding session starts from zero. You explain your project structure, your preferences, your patterns. The agent does great work, you close the session, and tomorrow it’s a stranger again. I got tired of re-teaching the same lessons every time I opened my projects.

Kiro Crew is an open-source workspace where agents carry memory, lessons, and skills across sessions. When you correct something, it becomes a durable lesson the agent won’t repeat, and repeated workflows become named skills.

In this talk I’ll show how persistent agent memory works and we’ll walk through a demo workflow that visibly improves across sessions. You’ll leave knowing how to set up a self-improving agent workflow and when to trust (or override) what it remembers.