A software factory builder cut cost by capping retries and replacing one worker with a script

Scarlett built a factory with five workers: a planner, a builder, a tutorial writer, a reviewer and a previewer. It runs on a persistent remote machine (a Sprite) and, in her words, it is a "transparent, well-lit factory" set against Steve Yegge's dark one. She reports two problems. A factory is new territory for coding agents, so it "took me hours to get it right." And failed runs still burn tokens: the factory kept pausing, she kept rerunning it, and she had hit her Codex usage limit while an automatic top-up kept the spend going.

Her fixes are specific. Every coding role moved to a cheaper model (gpt-5.6-luna) at low reasoning. She turned off automatic retries and gave each worker five minutes, so a failure stops the factory and leaves the retry decision to her. The preview worker became a plain script because it needs no model. For traceability she used the open-source Entire CLI, which links a recorded session to each Git commit, and added an AGENTS.md instruction to commit and push after every single file change. She ran two projects through it in parallel and calls it a success. The post gives no cost figures and no measured comparison, so the savings are her account, not a result.

Why it matters: The cost controls here are the portable part: a retry cap, a per-worker time limit and a script in place of a model call each turn an open-ended spend into a bounded one. The per-file commit rule is a cheap way to make a session reconstructable after the fact.