Summary

You now know how a change travels from an idea to done in an AI-native org - with Cogitave's own lifecycle as the worked example - and how to tell the difference between working on it and finishing it.

In this module, you:

• Learned that a change is a first-class Request (in Cogitave's Core, cogitave://request/{id}) that humans and agents drive through the same stages over MCP - intake, evaluate, plan, document, implement, review, done.
• Saw that each stage produces an artifact and passes a gate, that stages auto-advance on green checks, and that a human is pulled in only on an exception.
• Understood why the write tools - two of them in Cogitave's estate, request_intake and advance_stage - are propose-only: they open an issue or PR and stage a draft, and never merge, apply, or release.
• Read the Definition of Done - DoD == 100% and a CODEOWNER approval, with Core items that cannot be waived - and can now say when a Request is genuinely done rather than merely worked on.

You can now find, read, and work a change end to end - the lifecycle every contribution and every operation runs on.

Next steps

Where you go next depends on your path:

• Onboard to an AI-native codebase → Open your first pull request - turn the lifecycle into an actual signed, Conventional-Commit, docs-complete pull request (the final module of that path; completing it earns the trophy).
• Operate your AI-native estate → Run agentic operations - see how agents run this same lifecycle across your estate under least privilege.
• The LIFECYCLE.md doc is the authority on the seven stages; keep it open when you work a real Request.
• The definition-of-done.md doc has the full checklist the review gate enforces.