Typical problems
- Many fast changes without clear architecture
- Build and runtime errors after AI-generated additions
- Unclear data flows between UI, API, and database
Cursor project stabilization
Cursor is strong for speed. The bill often arrives later: scattered changes, inconsistent patterns, and features without robust failure cases. I stabilize the most important technical paths.
Process
I check build, routing, data flows, and configuration.
The most important flows are stabilized before side issues.
Errors are fixed deliberately and documented.
Matching packages
When the project starts, but nobody knows why it keeps breaking.
Code review, build/import check, and rescue plan within two business days.
For prototypes that almost work but are not reliable yet.
Triage plus up to ten hours of targeted repair and stabilization.
Ongoing senior control while you continue developing with AI.
Monthly allowance for reviews, small fixes, and technical guardrails.
FAQ
No. The same problems also happen with ChatGPT, Claude, Lovable, and other AI tools.
Yes, where it is necessary for stability and maintainability. Large refactors are prioritized instead of started blindly.
Yes, ideally with clearer guardrails so new AI changes cause less damage.
a Jurono service