Codersarts Blog.

You built something real. Maybe it took a weekend with Lovable, a few evenings with Cursor or an afternoon of prompting Claude Code. In the preview window everything works: the login, the dashboard, the button that calls an AI model and writes the perfect paragraph. Then you deploy it, and nothing works. The page loads but the data does not. Login spins forever. The AI feature returns an error you have never seen. Or, more confusingly, it works for a day and then quietly br

It usually starts quietly. A message goes unanswered for a few days. A small bug fix that used to take an afternoon now takes two weeks. Then the email arrives, or worse, it never does: your developer has taken a full-time job, moved on to another client, or simply stopped replying. If you are a founder or business owner, this moment can feel like losing the keys to your own building. The app still runs, customers still use it, but the one person who knew how it all fits to

Vibe coding gets you a working app in days. Here's what it actually is, where it breaks once real users arrive, what's already gone wrong in public, and how to fix each problem without starting over. Key takeaways Vibe coding is building software by describing what you want to an AI tool in plain language and accepting the code it writes without reviewing it. It's genuinely good for prototypes, idea validation and internal tools. It struggles with what nobody prompts for: sec

A self-scoring audit for apps built with Lovable, Bolt, Replit, Base44 or Cursor. No developer required. Budget an afternoon. This is the checklist we run internally before we quote on any AI app rescue job. It's been trimmed to the things a non-technical founder can verify without reading code, and ordered so the highest-consequence items come first. Key takeaways 25 yes/no checks across 7 areas: data access, secrets, authorization, money, scale, abuse limits and operations.

If you stopped working on your app tomorrow, how long would it take someone else to change one thing safely? AI-built apps carry code but almost none of the context that explains it. Why that costs you at hiring and at valuation, and the under-two-days fix.

Most comparisons rank these three on how fast they build. Once real money is involved, the axis that decides it is exit cost — how much of your app is code and how much is platform. How Lovable, Bolt and Replit compare on that, and the one-paragraph decision.

AI gets you four-fifths of a working product in weeks. The last fifth takes longer, because it's a different kind of work entirely — unhappy paths, adversarial thinking, real data volume and operations. What's actually in it, why it's the expensive part, and who should build it.

A client portal, an intermittent bug, and forty confident fixes — each one landing in the file where the symptom appeared, none reaching the cause spread across three others. A composite account of the debugging spiral, and why three returns is the signal to stop.

Finishing an AI-built app runs anywhere from four days to five weeks. Almost all of that spread comes from three things you already know the answer to: how long you kept prompting, whether money is involved, and how much live data exists. The breakdown, item by item.

Lovable produces a specific stack, and that stack has specific weak points. Five failures consistent enough to check before reading anything else — open Supabase policies, shared-client caching, unvalidated edge functions, full-table loads and a frozen schema — plus what's genuinely fine.

A marketplace and a clinic portal don't fail the same way. Twenty-five app types across marketplaces, SaaS, regulated domains, content platforms and internal tools — the failure each one produces most, why it's characteristic of that category, and how to check yours.

A definition of AI app rescue, the five types of work it covers — audit, security hardening, stabilization, productionization and rebuild assessment — and the examples that show where each one applies. Plus what the category isn't: not maintenance, not a rewrite, not staff augmentation.

Production readiness isn't a measure of how complete your features are. It's a measure of what happens when you aren't watching. The working definition, the five conditions underneath it, what the phrase doesn't mean, and four questions that place your own app.

Different tools, different founders, different industries, same six problems. A year of auditing AI-built apps turned up a consistent list of security holes — each one explained, and each with a check you can run on your own app in under ten minutes.

AI app builders are good at writing code. That part is settled. What they're still bad at is everything between "it works on my screen" and "strangers are paying for it." Six places where that gap opens — and which ones will close as the tools mature.