Vibe Coding vs Engineering Judgment: Where Speed Ends and Responsibility Begins

Source: Dev.to

Introduction

Vibe coding is everywhere: you prompt an AI, stay in flow, generate code quickly, and ship something that looks correct. Demos work, tests pass, and it feels productive. After handling real‑world incidents and reviewing production code, one thing becomes clear: vibe coding accelerates output, while engineering judgment protects systems. Both are needed, but they solve very different problems.

What Vibe Coding Looks Like

• Rapid AI‑assisted code generation
• Minimal planning
• Trusting the output because “it works”
• Prioritizing momentum over structure

It removes friction: no blank page, no syntax struggles, no context switching. For small scopes, this is a genuine productivity boost.

When Vibe Coding Shines

• Throw‑away code – proofs of concept, demos, experiments where longevity doesn’t matter.
• Learning or validation – the goal is to explore ideas, not to guarantee production stability.
• Simple tasks – CRUD APIs, basic UI layouts, configuration setup.

In these cases the cost of mistakes is low, and the speed advantage outweighs the risk.

Where Vibe Coding Falls Short

Code that must survive multiple teams, refactors, scaling, and years of maintenance often suffers:

• AI‑generated structure may look clean initially but becomes painful to maintain.
• Complex business rules (auth, permissions, payments, secrets) are messy; AI tends to oversimplify and encode incorrect assumptions.

A Real‑World Example

I used AI to implement a background job flow that worked perfectly in staging, with clean retries and nice abstractions. What I missed:

• Retries weren’t idempotent.
• Partial failures caused duplicate writes.
• Logs hid the real issue.

A production incident exposed the problem. The AI didn’t make the mistake; the missing engineering judgment did.

Guiding Principle

If you can’t explain why the code is safe, you shouldn’t ship it.

AI can help write code, but it should be used as:

• An assistant
• A drafting tool
• A productivity multiplier

—not as the architect or decision‑maker.

Common Pitfalls of Unchecked Vibe Coding

• Hard‑coded secrets left “temporarily” in place
• Overly permissive access checks
• Unsafe dependency choices
• Missing validation paths

Everything looks fine until it isn’t. Security, in particular, requires skepticism that AI lacks.

Practices That Work

• Slow down at boundaries (authentication, data writes, integrations).
• Review AI‑generated code as if someone else wrote it.
• Ask how it fails, not just how it works.
• Never skip human code review; treat AI output as untrusted by default.

Speed without discipline merely moves problems downstream.

Balancing Speed and Responsibility

Use Vibe Coding To

• Explore ideas
• Reduce friction
• Move fast where risk is low

Rely on Engineering Judgment To

• Protect users
• Secure systems
• Design for failure
• Own production outcomes

Speed ships features. Judgment keeps systems alive. That’s the difference experience teaches.