Building Creative AI Mastermind with Three AI Models

How Claude plans, Codex engineers and Gemini reviews the platform, and why errors are caught before they reach you.

You might wonder how Creative AI Mastermind keeps growing a little every week, and why that matters to you. The AI Radar is refreshed by a weekly sweep for new events, courses and funding calls, the AI Graph keeps learning new skills, and new tools arrive that save you time. Here is how that happens.

I am the initiator of Creative AI Mastermind, and I am not a developer. So I faced a question many of you know from your own projects: how do you get planning, engineering and quality control when you are one person? My answer is a team of AI models. Claude, Codex and Gemini share the build, and each one does the part it is best at.

Claude plans: it takes my instructions, assigns the tasks and signs off the results. Codex engineers the layouts, the database migrations and the automated tests. Gemini reviews what actually appears on the screen and reads the files that are too large for the others.

The rules keep it honest. High-risk work from one model family is always reviewed by another. The models never vote; the code, the tests and the rendered page decide when something is ready. For you, that means errors are caught before they reach your screen.

From the development side, the past week was about keeping the work moving. We built a live check that reads each provider's usage allowance before every task, and a supervisor that runs outside any Claude session. If Claude reaches its limit, the supervisor hands the next queued task to Codex or Gemini within a minute, so the platform keeps growing while I sleep. On 19 September, four AI workers built separate parts of the code side by side without getting in each other's way.

The next big step is matching. In the next post I introduce AI Match, the tool that reads your AI Graph to find the right people, funding and events for your project.