Stabilization Sprint

Who this is for

The app works. That was never the problem. The problem is what shipping feels like now.

• The AI breaks something every time you ship, and you’ve stopped being surprised.
• Nobody has ever actually checked who can call your API, or what it returns to them.
• Authorization lives in the client, so anyone curious enough owns your data model.
• There are no tests, which means every change is a bet with your users’ trust as the stake.
• You asked the AI to fix something and it made it worse. Twice.

None of this means you built it wrong. You built it fast, it worked, and now the codebase needs to be built to last. That is a different job, and it’s the one this engagement does.

What happens

Week one: map, then close the worst gaps. I read the code the way an attacker and a maintainer both would, rank what I find by real exposure, and fix the highest-risk items first: missing authentication, missing row-level security, keys in the wrong places, endpoints that trust the client. You see the ranked list, and nothing happens to your codebase without you knowing why.

Weeks two to three: make it hold. Authorization moves server-side where it belongs. The API surface gets hardened, so every endpoint has an answer to “who can call this, and what does it hand back?” Tests go around the paths your revenue depends on, so the AI can’t silently break them again.

Then: make shipping fast again. Stability is what lets you move quickly, not what stops you. You get CI/CD with automated deployments, health checks, and stood-up dev and QA environments, plus processes catered to your team and your app: properly configured git hooks, DevSecOps gates, and industry standards codified into the repo itself, so Cursor and Claude Code follow the same rules your engineers do. Shipping gets faster because you stop hand-checking everything first.

Final week: make it repeatable, then hand it back. Secrets come out of the code, environments get separated, deploys become boring. You get a written handoff report covering everything that changed and why, plus a walkthrough call, so the knowledge lands with you and not only in the commits.

What you walk away with

A codebase that you and your AI tools can keep building on, with tests that catch regressions before your users do and deploys that no longer take nerve. The handoff report makes the whole sprint legible to a future hire, a partner, or an investor running technical diligence.

If you’d rather not be the only senior set of eyes on it going forward, the Aftercare Retainer picks up exactly where the sprint ends.