When Vibecoding Works — and When It Doesn't

A realistic map of where vibecoding produces good results fast and where it quietly leads you into trouble. Knowing the difference up front saves you from betting a serious project on an approach that fits a weekend prototype.

AI is strongest on code that is common, self-contained, and easy to check by looking at the result. It gets weaker as the task becomes novel, spans many interacting parts, or has correctness you can't eyeball — because then a fluent, confident answer can be wrong in ways you won't notice. Matching your ambition to that reality is what keeps vibecoding from turning into a debugging nightmare.

Vibecoding works well for: prototypes and MVPs, internal tools, personal projects, standard CRUD web apps, landing pages, scripts and automations, and the first version of an idea you want to test. It also works as a learning accelerator — building something real is a fast way to understand how the pieces fit.

Be cautious — or bring in review — when the app handles payments, health or legal data, or the private data of many users; when it must integrate deeply with fragile existing systems; when correctness is subtle and can't be verified by clicking around; or when it must scale to heavy load. None of these are impossible to vibecode, but none are safe to vibecode without reading the code and checking the security.

Here's what I want to build: <description>. Before we start, tell me honestly: is this a good fit for building mostly by AI, or are there parts (security, data, integrations, scale) where I'll need to slow down and review carefully? List those parts specifically.

A founder vibecodes a polished marketing site and a waitlist form in a day — a great fit. When the same founder tries to vibecode the payment and subscription logic the same way without reading any of it, they ship a billing bug that double-charges users. Same technique, wrong risk level.

Split any ambitious project into a 'safe to vibe' zone (UI, layout, standard flows) and a 'read every line' zone (auth, payments, data access, anything a malicious user touches). Vibecode the first freely; treat the second as AI-assisted but human-verified.

• Assuming that because the easy 80% vibecoded smoothly, the risky 20% is equally safe to accept unread.
• Picking a genuinely novel or complex problem for your first project and concluding vibecoding 'doesn't work' when it stalls.
• Ignoring the security-sensitive zone because the app appears to work perfectly in your own testing.