Looper

I run recurring AI agent jobs every day on my own sites and projects. Each job started as a prompt and a schedule. Over time its goals, its checks and the lessons from past runs ended up in notes, scripts and chat logs. When a run taught me something, the next run never saw it, and I had no score to tell me whether a job was getting better.

Looper keeps each job in one Markdown spec. The spec has nine sections: objective, evals, sources and instructions, quality control, macros and recursion, learning, schedule, roadmap and OKRs.

Each run does the work and scores it against the evals. The loop logs what raised or lowered the score and edits the sections of its spec it is allowed to edit. A bank view lists every loop with its schedule, its last score and the change since the run before.

It is in development and I am its only user. A loop cannot change its own objective, evals or OKRs. Every edit is logged with the reason, and if the next score drops, the loop goes back to the last version. I write the specs and decide what ships. AI agents write much of the code and the first drafts, and I review them.