2025-02-14

Vibe Coding Needs a Reality Check: Why AI-Generated Code Still Requires Engineering Discipline

Vibe Coding

The term “vibe coding” has been making the rounds, painting a picture of a laid-back, intuitive way to write software with AI. The idea? You describe what you want, accept the AI-generated code, and move on. No stress, no deep dives, just code that vibes.

Except… the way that they make vibe coding sound is a setup for future problems.

Vibe Coding Isn’t New, Just Newly Branded

You, and many others, may have been working this way before the term “vibe coding” was popularized. AI-assisted development has been evolving for years, and developers have been using tools like Copilot, ChatGPT, and Claude to accelerate their work long before “vibe coding” became a buzzword.

The difference now? Marketing.

But just because AI can generate code faster doesn’t mean it’s automatically better. The reality is that AI-generated code needs oversight, structure, and engineering discipline, just like human-written code.

The Problem: Vibe Coding Sounds Too Passive

The phrase makes it sound like coding without guardrails, as if the AI is doing all the heavy lifting while developers sit back and let it happen. In reality, blindly accepting AI-generated code introduces major risks:

  • Maintainability Issues → AI doesn’t always optimize for long-term readability.
  • Performance Pitfalls → Code may work, but is it efficient at scale?
  • Security Vulnerabilities → AI doesn’t inherently understand security best practices.
  • Compounding Mistakes → Without oversight, one bad AI-generated decision can snowball into a bigger problem.

A Better Approach: Vibe Coding with Structure

If you’re going to use AI as part of your development process, you need a structured workflow that ensures quality and prevents long-term headaches.

Here’s what that should include:

✅ Code review checkpoints, with human-assisted review, at least for now.
✅ Testing and validation at every step, not just assuming AI-generated code is correct.
✅ Security checks built into the workflow to catch vulnerabilities early.
✅ **AI feedback loops to refine and improve suggestions over time.

AI is a tool, not a replacement for engineering judgment.

AI Coders Need Guardrails, or They Might Cause Damage

One of the biggest pitfalls of unrestricted vibe coding is that AI models degrade when built on top of previous AI-generated code.

If you accept AI-generated solutions blindly, without enforcing best practices, your assistant will accumulate hack upon hack. Eventually, the model performance will degrade, quality will drop, and it could start to reinforce its own mistakes.

A Slippery Analogy: Driving a Car vs. Fixing a Car

It’s true, you don’t need to be a mechanic to drive a car, but you need to know that you should not slam on the brakes when you hit ice.

You need to get to know the rules of the road for what you are vibing on.

Final Thoughts: Vibe Coding Isn’t Bad, But It Needs Discipline

AI-assisted development is here to stay, and vibe coding isn’t inherently a bad idea. But for it to work in the real world, it needs to be structured, tested, and reviewed.

✅ Use AI as a collaborator, not a crutch.
✅ Build processes to review, refine, and validate AI-generated code.
✅ Don’t let AI-generated shortcuts turn into long-term tech debt.

AI makes coding faster—but engineering discipline makes it sustainable.

What do you think? I know some people hate code generation, others love it.