AI App Rescue
You built something with AI. Now it needs to become real software.
AI coding tools can get a product surprisingly far. Once real users, payments, customer data, integrations, and production traffic enter the picture, the technical requirements change.
I help founders audit, repair, stabilize, and prepare applications built with Lovable, Bolt, Replit, Cursor, Claude Code, Codex, and other AI development tools for their next stage.
AI can write the code. Someone still needs to know whether the code is good.
For non-technical founders, solo builders, startups, and small businesses, a working prototype is a real achievement. This service helps you understand what can support real customers, what needs attention, and what is already working well.
AI Prototype → Review → Stabilization → Production
When the prototype starts acting like a production system
Not every AI-built application has these problems. A review becomes useful when progress slows down or the consequences of a mistake become more serious.
Changes have become unpredictable
A generated change breaks unrelated features. Login behaves differently in production. Deployments fail, environment settings drift, or preview and production disagree.
Duplicated implementations make it unclear which code is safe to change. The AI keeps patching symptoms while the underlying problem remains.
Data and integrations need attention
Supabase permissions or row-level security policies are hard to follow. Database queries are getting slow or expensive.
Stripe webhooks, background jobs, or API integrations are unreliable. You need someone to check whether secrets or API keys are exposed.
Customers depend on the app now
People rely on the application, but monitoring, backups, recovery, and safe deployment practices have not caught up.
You need a clearer view of production risks before adding customers, collecting more data, or expanding the product.
Three ways to move forward
Start with the problem you have today. The scope follows the evidence and your priorities.
AI App Health Check
A structured review of the codebase, infrastructure, and production readiness. Get clear findings and a prioritized next step before investing in more changes.
Vibe Coding Triage
Urgent care for AI-built software. For broken login, failed deployments, migration problems, missing data, payment failures, slow APIs, and regressions that repeated generated fixes have not resolved.
Diagnosis comes first. Timing and repair options depend on what the investigation finds and current availability.
Prototype to Production
A larger engagement to make a validated prototype maintainable and dependable. Keep useful work and strengthen the parts that need to support real customers.
What an App Health Check covers
Architecture, API design, authentication, authorization, database structure, indexes, and Supabase configuration.
Secrets management, dependencies, obvious security concerns, logging, error handling, tests, and deployment configuration.
Duplicated or dead code, vendor lock-in, scalability bottlenecks, backups, recovery, and infrastructure costs. Review depth is agreed around the size and needs of your application.
A useful review includes what to leave alone
The goal is a practical set of decisions, not a long list of changes for its own sake. Findings explain their impact and recommended next steps.
Critical
Problems that should be addressed before adding more users.
Important
Issues likely to cause trouble as the application grows.
Technical Debt
Cleanup that will help maintainability but is not urgent.
Looks Good
Working areas that should be left alone.
Keep what works. Replace what does not.
An AI-built application does not automatically need a rewrite. Your UI, React components, user flows, validated product decisions, and working business logic may already be valuable foundations.
Where needed, I can improve authentication and authorization, database design, backend APIs, background jobs, file storage, payment infrastructure, and secrets management.
Production readiness also means useful logs and monitoring, reliable deployment infrastructure, CI/CD, automated tests, and a recovery plan. The aim is software you can safely maintain and operate.
Keep using AI. Add experienced technical oversight.
You do not need to abandon Lovable, Cursor, Claude Code, Codex, or the tools that help you build. Add a technical reviewer at the points where a mistake would be expensive.
Ongoing support can include architecture decisions, code reviews, agent-generated pull requests, production changes, database migrations, security-sensitive work, deployment strategy, infrastructure choices, and recurring health checks.
You keep the speed of AI-assisted development without giving up technical judgment. Scope and frequency depend on the product and the support you need.
AI can generate a lot of code. Production software still requires judgment.
Software engineering includes architecture, reliability, security, maintainability, debugging, operations, infrastructure, scaling, and the tradeoffs between them. Generating code is one useful part of that work.
AI-assisted development is powerful and has a lasting place in how software is built. Experienced engineering helps make that speed safer and more sustainable as a product grows.
From the first look to a clear next step
Start with a short description. Repository and environment access are arranged securely after initial contact.
1. Show me the application
Share what the app does, where it is deployed, and the problem or goal. Then arrange access to the relevant repository and environment.
2. Technical review
Inspect the relevant code, infrastructure, database, logs, and deployment configuration.
3. Findings and priorities
Identify what is actually wrong, what is risky, and what should be left alone.
4. Fix, stabilize, or plan
Implement agreed repairs or create a prioritized path toward a production-ready system.
Your prototype already proved something. Now make sure the software can support it.
Tell me what you built and what you need help with. Include a public app URL if useful, the tools you used, and whether customers are affected. Please do not send passwords, API keys, or repository credentials through the contact form.