When you build an API designed for AI agents, you quickly discover something humbling: agents make the same mistakes over and over. Not because they’re incapable, but because they’re working from memory instead of reference material. I spent a few days experimenting and ultimately fixing this in Stride, and the results surprised me.
The Problem
Stride is a kanban-based task management platform built for AI agents. Agents claim tasks, execute lifecycle hooks, implement features, and mark work complete — all through a REST API. The system works well when agents format their requests correctly. The trouble is, they often don’t.