Vibe Coding Is Not a Shortcut — It's a Minefield. Here Are the Mistakes That Will Actually Cost You

Vibe coding started as a joke. You describe what you want in plain English, an LLM spits out code, and you ship it without reading a single line. It felt like magic.

Six months in, the magic is wearing off. Developers are shipping apps that break in production, leak API keys, and run up cloud bills for features nobody asked for. The problem isn't the AI — it's the vibe.

I've been building Android apps for years, shipping to Google Play with a tiny team and an even tinier budget. When vibe coding tools showed up, I tried them. I broke things. I learned. Here are the mistakes that actually matter — and what to do instead.

1. You Trust the First Output

The biggest lie in vibe coding: "It just works." It doesn't. The first output from any LLM is a starting point — not a finished product. It will compile. It might even look correct. But it rarely handles edge cases, and it never understands your specific constraints.

I've seen generated code that works perfectly for API version 3 and silently corrupts data on version 4. I've seen "null checks" that check the wrong variable. The AI doesn't know your backend, your users, or your deployment pipeline. It guesses.

Fix: Treat every generation as a draft. Run it. Break it. Ask "what happens if the network is slow?" and "what happens if this value is empty?" The AI will answer confidently — you need to verify.

2. You Ship Code You Don't Understand

This one is seductive. The AI generates 200 lines of Kotlin. It compiles. The feature works. You merge it. Three weeks later, a crash report points to a function you've never read.

If you can't explain every line of code you ship, you're not developing — you're gambling. The AI might generate a regex that's 99.9% correct but fails on one specific character. It might use a deprecated API that works today and breaks tomorrow.

Fix: Read every line. If something looks clever, it's probably wrong. Rewrite it until you could explain it to a junior developer. If you can't, you shouldn't ship it.

3. You Let the AI Make Architecture Decisions

Vibe coding tools are great at generating functions. They are terrible at deciding how those functions should be organized. Ask an LLM to build a "scalable architecture" and you'll get a beautiful diagram with arrows going everywhere and a codebase that collapses under its own weight in two sprints.

Architecture decisions — dependency direction, module boundaries, data flow — require context the AI doesn't have. It doesn't know your team size, your release cadence, or which components change most often.

As the developer behind Pin Up Retro Manner, I've learned that architectural choices compound. A bad decision on day one costs ten times more to fix on day one hundred. The AI will happily make that bad decision for you if you let it.

Fix: Design the architecture yourself. Use the AI to fill in implementation details within boundaries you've already set. Never ask "how should I structure this project?" — ask "given this structure, implement this module."

4. You Skip Testing Because "The AI Got It Right"

LLMs generate plausible-looking code. Plausible is not correct. I've seen generated sorting algorithms that work for 10 items and shuffle everything above 100. I've seen database queries that return the right result in development and time out catastrophically in production with real data volumes.

Without tests, you're betting your users will find the bugs before you do.

Fix: Write tests before you trust the code. Not after. If the AI can generate the implementation, it can generate the tests too — but you need to verify both. A test the AI wrote that passes doesn't prove anything. Read the test. Break the code on purpose and confirm the test catches it.

5. You Burn Your Context Window

Every LLM has a context window. When you vibe-code a feature, you burn tokens on back-and-forth corrections, retries, and "no, what I meant was..." by the time you reach the important part, the AI has forgotten your project structure, your naming conventions, and that critical constraint you mentioned 20 messages ago.

The result: code that doesn't match the rest of your codebase. Inconsistent patterns. Duplicated logic. Bugs introduced by context amnesia.

Fix: Start fresh conversations for distinct features. Keep a project context document you paste at the start of each session. Be specific in the first message. The more focused your prompts, the less context you waste.

6. You Don't Version the Prompt History

Your code is in git. Your prompts? Probably lost in a chat history you'll never revisit. When a bug surfaces six months later and you need to understand why a particular implementation decision was made, the prompt that generated it is gone.

Fix: Save prompts alongside code changes. A one-line comment in the commit message or a prompts/ directory in the repo. It takes ten seconds and saves hours of forensic debugging later.

The Bottom Line

Vibe coding is a tool, not a replacement for engineering judgment. Use it to accelerate the boring parts — boilerplate, test stubs, documentation drafts. But when it comes to architecture, security, and correctness, the vibe stops. You make the call.

The developers who will thrive with AI are not the ones who type the fastest prompts. They're the ones who know when to trust the output and when to tear it apart and start over.

This article was written by Artem Garazha, an independent Android developer exploring the intersection of AI tools and mobile development. Follow the journey at Pin Up Retro Manner on YouTube.