AI app launch risk review process

How it works

1. Share repository access and any specific concerns you already have.
2. I review architecture, risky implementation choices, and operational blind spots.
3. You get prioritized findings with practical next steps ranked by impact and effort.

What I look for

• Backend authorization and data-boundary risks
• Secrets, payments, webhooks, and private data paths
• AI-assisted code paths that are brittle or hard to maintain
• Deployment assumptions and observability gaps around sensitive paths

What the report covers

• Highest-risk decisions to fix before launch
• Whether the codebase is ready to ship, needs targeted fixes, or needs deeper work
• Recommendations ranked by impact and effort
• Context on where a future developer is likely to get stuck

Best timing

The review is most useful before production launch, before a handoff to another developer, after an AI-assisted build sprint, or before committing to a major refactor.