We have seen what happens when teams bolt AI onto their workflows without guardrails. You get a firehose of speculative issues, vague suggestions, and noisy PR comments that train developers to ignore everything the bot says. The Elastic AI Software Factory is built on the opposite philosophy: an agent that has nothing useful to say should say nothing at all.
What does it look like when a repo runs the full Elastic AI Software Factory? We deployed the framework on our playground repository -- combining the named workflows that ship with ai-github-actions and a set of custom Scheduled Audit configurations (Ideas Man agents, Playwright smoke testers, and domain-specific analyzers). The result is over 30 agents running on a daily schedule, and from the outside it can look like chaos. But there is a rhythm to it.