The Demo Worked. Production Is a Different Story.
AI coding tools like Lovable, Cursor, Replit, Claude Code, and v0 have made it possible to build a working prototype in a weekend. That speed is real and useful. The problem is what comes after: real users, real load, real security requirements, and a codebase that was never built to handle any of it.
Lightning Workgroup specializes in vibe code cleanup and production readiness: taking over AI-generated code and making it work in the real world. Not reviewing it and handing you a list of problems to figure out on your own. Actually fixing it. We have 15 or more years of experience inheriting, modernizing, and stabilizing complex systems. AI-built apps are the newest version of a problem we have been solving for a long time.
US-based senior engineers. Not a solo developer. Not an offshore shop. A team that knows what matters, what can wait, and how to get an AI-built app ready for the real world.
Signs Your AI-Built App Is Not Production-Ready
✅ It works in demos but breaks or slows down when real customers use it
✅ Every update to the app carries real risk because there is nothing in place to catch problems before users do
✅ Sensitive credentials like passwords and API keys are stored directly in the code where anyone with file access can see them
✅ There is no reliable process for releasing updates, so each one requires manual steps and hope
✅ You are not confident about who can access your customer data or whether it is properly protected
✅ A developer told you the code needs to be rewritten but you do not want to throw away what you built
You do not have to address everything at once. Most clients start with a Code Health Check, get a clear picture of what they are dealing with, and decide from there. There is no obligation to go further until you are ready.
If any of these sound familiar, you are not the only one. Most apps built with AI tools share these issues by default. The question is whether to address them now or after they cost you a customer, a deal, or a data incident.
Vibe Code Cleanup Services
Three ways to take your AI-built app to production. Start wherever makes sense.
Code Health Check
A structured audit of your AI-generated codebase. Your code gets reviewed systematically and we surface security gaps, architectural problems, performance issues, and missing infrastructure. You walk away with a prioritized findings report and a clear picture of what needs to be addressed and in what order.
Full Cleanup Sprint
Hands-on remediation by our engineering team. The Cleanup Sprint takes the Code Health Check findings and fixes them: credentials secured, vulnerable endpoints closed, test coverage added so future changes do not break what works, and a real release process set up so updates go out without stress. You end up with a codebase your team can actually maintain and build on confidently.
MVP to Production
Full takeover of an AI-built prototype and delivery of a system ready for real customers and real scale. Everything that exists gets assessed, the business logic and functionality that works stays intact, and the structure it was missing gets built. At the end you have a stable, secure application with documentation, a clear architecture, and 30 days of post-engagement support included as standard.
Looking for continued coverage as you keep building? Our AI engineering partnership is structured for teams that want a senior team alongside them as they keep shipping with AI tools.
Common Problems with AI-Generated Code
AI-generated code tends to have a predictable set of structural problems. These are not edge cases. They are the default state of most codebases built this way.
- Unsecured customer data: Access controls misconfigured or missing entirely, meaning customer records may be reachable in ways they should not be.
- No safety net for changes: No automated tests means every code change is a risk. There is no way to know if an update broke something until a customer tells you.
- Performance that does not hold: Works fine with a handful of test users. Falls apart under real load because the underlying queries and architecture were never optimized.
- App failures with no graceful recovery: When something goes wrong, the whole app stops instead of handling the error and staying available.
- No controlled release process: Changes go live manually with no staging environment and no way to roll back quickly if something breaks.
- Exposed credentials: Passwords, API keys, and service tokens stored in the code or committed to version control where they should never be.
How We Clean Up AI-Built Code
Why Choose Lightning Workgroup?
We take over hard codebases. It is what we have always done.
Every engagement includes 30 days of post-work support as standard. For teams that want continued coverage, we offer ongoing support plans that keep us involved as your application and team grow. If you have questions about what cleanup or ongoing partnership would look like for your codebase, start with a 15-minute conversation. You will get an honest read on what you are dealing with and what it would take to address it.
We make digital solutions simple, effective, and stress-free.
Vibe Code Cleanup: Common Questions
A: Vibe code cleanup, also called vibe coding cleanup, is the process of taking an AI-generated codebase built with tools like Lovable, Cursor, Replit, Claude Code, Base44, or v0 and making it secure, stable, and production-ready. That includes closing security gaps, adding test coverage, fixing the architecture, and setting up a proper deployment pipeline.
A: Before, if the timeline allows. Catching security and architecture issues before launch is significantly less expensive than catching them after, and it avoids a launch that creates problems for early customers. A Code Health Check typically takes 3 to 5 business days, so even a tight launch timeline can usually accommodate one. If launching is non-negotiable, we can prioritize critical security fixes pre-launch and address the rest in the weeks after.
A: Probably not by default. Lovable generates a real Supabase backend, which is a good foundation, but the security configuration is almost always incomplete. Common issues we see: row-level security misconfigured so users can see data they should not, authentication flows missing rate limiting and session protections, API keys committed to the codebase, and environment variables exposed in the frontend bundle. The fix is straightforward but it has to actually be done. A Code Health Check identifies which of these are present in your specific app and exactly what needs to change.
A: Because AI tools optimize for getting something working, not for getting something working under load. The most common causes: database queries that run fine for one user but multiply badly for many, no caching layer so every request hits the database, blocking operations that lock up the app while one user waits, and missing error handling that turns small problems into full crashes. None of these are hard to fix, but all of them have to be identified and addressed individually. A Code Health Check finds them, a Cleanup Sprint resolves them.
A: You do not have to rebuild your app to move off Base44. Your frontend is standard React and exports cleanly. What you do not own is the backend: the database, authentication, API layer, and file storage all live on Base44 infrastructure. We rebuild that backend on standard services you actually control, then point your existing frontend at it. Your business logic, your data, and the work you have already done all stay intact. You can also keep using Base44 for prototyping new features after migration and integrate them into the production system as they prove out.
A: Yes, for teams that are actively building. A one-time cleanup fixes what exists today. If you keep generating new code without a review process, the same problems come back and you are paying to fix them again. Ongoing support keeps the codebase from accumulating new issues in the first place, which is almost always less expensive than periodic cleanups after the damage is done. We offer this as an AI engineering partnership for teams that want continued coverage.
A: Most standard engagements begin within 1 to 2 weeks of scoping. If you are dealing with something more time-sensitive, like a launch in days or an active issue affecting users, we can typically accommodate accelerated timelines on a case-by-case basis. Reach out and tell us the situation honestly. We will be straight with you about what is realistic and what trade-offs an expedited engagement involves.