You have built REVIEWBOT across five modules: foundations, tools and AI, workflows, human-in-the-loop and scheduling, and an MCP server. Here is where to take it next.
The capstone: let it review itself
Point REVIEWBOT at a deliberately bad pull request on its own repo and watch it work. The risk tier comes back full, all three specialists fire, and it catches the planted bugs before asking you to post. Open the Self-review exercise.
Make it yours
Point REVIEWBOT at your own repositories. Change a prompt, add a specialist, tune the risk tiers. You own the data, the model, the prompts, and the infra, so every part is yours to change.
The production reviewer
To go further, read the production write-up: seven specialists, multi-model failback, circuit breakers, and CI integration. You now have the mental model to build it.
Optional: lock it down
Before REVIEWBOT goes public, the optional Secure it with Zero Trust lesson puts identity in front of the agent and its MCP endpoint.