Ship with AI: Review, Secure, and Deploy with Confidence
AI writes more code, faster than ever. That's the easy part. The hard part — the part that decides whether shipping with AI is safe — is what happens next: who reviews it, who secures it, and how it gets from a pull request to production without anyone's attention slipping.
This site is both things at once. It's the companion material for AI Genius Season 5, Episode 3, and it's also the exact repository that was reviewed, secured, and deployed live on stream, using the pipeline described on the next few pages.
The trust gap. The more code an AI assistant produces, the more your review, security, and release process has to carry. Speed without those guardrails just moves risk downstream — into your dependencies, your CI/CD pipeline, and your production environment.
Where to start
- The pipeline — how an idea becomes a deployed change
- Secure your supply chain — the security spine of this demo
- Follow the demonstration — six stages from issue to deployment
Questions & feedback
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