Vibe Coding Is Not Engineering

4 hours ago

The gap between vibe coding (producing code quickly via AI) and engineering (designing coherent systems) is where production failures occur.
Vibe coding provides momentum and code but lacks coherence and critical engineering decisions made before coding.
Engineering involves problem framing, requirements, system modeling, architecture, non-functional needs, risks, interfaces, and planning.
LLMs skip crucial engineering decisions like invariants, uniqueness constraints, failure modes, coupling, state transitions, and boundaries.
AI-generated code often stalls or becomes fragile because missing decisions lead to system breakdowns under real-world conditions.
For example, a login system generated by AI might not enforce unique emails, causing identity confusion and security issues.
The misconception behind vibe coding is assuming AI reasons like an engineer, but it only produces text without deep reasoning.
Before using AI for code, define invariants, identity rules, constraints, and failure modes to ensure system safety and coherence.
Vibe coding is suitable for demos, but engineering is essential for systems that survive in production environments.

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