Illustration highlighting common vibecoding mistakes

The Biggest Mistakes New Vibecoders Make (and How to Dodge Them)

Vibecoding is a superpower, until it isn’t. If you treat the AI like an all-knowing senior engineer, you’ll burn hours, tokens, and motivation. Over time, a pattern of common vibecoding mistakes has emerged among new AI programmers. The good news? Once you know them, you can avoid them and improve your developer workflow.

1. Assuming the AI “has it handled” (Common Vibecoding Mistake)

Mistake: Expecting the model to always pick the right patterns, keep security in mind, stay on task, and not break adjacent code.
Fix: You’re the technical strategist. Keep a checklist: security, scalability, framework choice, test impact, regression scan. Require the AI to explain the plan before it edits, then review diffs with your own eyes.

2. Using AI for the tiniest pixel nits (AI Coding Tips)

Mistake: Asking the model to nudge a margin or fix a misaligned button and getting a layout blender in return.
Fix: Reserve AI for net-new features or structural refactors. For finicky UI polish, prototype adjustments in browser dev tools first, then let AI refactor once you’ve proven the fix.

3. Skipping “skeleton code” (AI Programming Mistake)

Mistake: Dropping the AI into a blank repo and hoping it “figures out the architecture.”
Fix: Provide a thin scaffold: folders, interfaces, a README map, and a couple of example components or services. This anchors the AI to your intended structure instead of letting it improvise.

4. Vibing without fundamentals (Developer Workflow Pitfall)

Mistake: Never learning version control, secret management, deployment basics, or how HTTP/state actually work.
Fix: Build a few things without an LLM, even tiny utilities. Know when a completion smells wrong. Always commit before every prompt, keep secrets out of code, and wire a minimal CI.

5. Big prompts, vague goals (Vibecoding Mistake)

Mistake: “Build the whole feature” in one shot, with fuzzy requirements.
Fix: Co-design first. Ask the model for a proposal, refine it, lock the interfaces, then execute in small steps (one class or method per prompt) with diffs reviewed each time.

6. Shipping features no one asked for (AI Programming Trap)

Mistake: Overbuilding because vibecoding makes new features too easy.
Fix: Validate with smoke tests: put a button behind a feature flag, add minimal analytics/logging, and see if anyone uses it before you invest more.

7. Vendor lock-in creep (Developer Workflow & Portability)

Mistake: Parking your entire project on a platform that hides or owns your files.
Fix: Prefer tools that work in your repo or terminal. Keep everything exportable. Decide early which hosted bits you can swap (storage, email, auth) and document escape hatches.

8. Token burn as a substitute for skill (AI Coding Tips)

Mistake: Paying for the shiniest model and lots of retries instead of sharpening prompts and system design.
Fix: Treat spend like unit tests, only pay for experiments that improve your prompt kit or architecture. Start cheap or free where possible and upgrade for measurable gains.

9. Thinking you’re just “the ideas person” (Vibecoding Mistake)

Mistake: Acting like the PM only and hoping AI is the engineer.
Fix: You are the PM and the integrator. Do the planning: write specs with the AI, decide patterns, call out constraints, and babysit integrations.

10. Ignoring privacy and leaks (AI Programming & Security)

Mistake: Letting the assistant commit real names, keys, or sensitive files into your repo.
Fix: Gate commits with a pre-commit hook that redacts secrets and PII. Keep a “redaction dictionary” for proper nouns you never want stored.

A Minimal Vibecoder Checklist for Developer Workflow

Final Thought

Vibecoding shines when you stay the adult in the room: you set the architecture, define constraints, and move in tight loops. Let the AI generate, you orchestrate. That’s when the vibe turns into real progress and your developer workflow thrives.

See also