The concept of Vibe Coding is appealing: go with the flow and let AI write code for you. But in real projects, I've found that "going with the flow" is not actually low-cost.
Real costs include:
- Verification cost
AI-generated code requires human review. Not all code reveals problems at a glance — some bugs require running tests or even manual testing to discover.
- Context cost
AI doesn't understand your full project context. It might use wrong library versions, ignore existing conventions, or reimplement existing functionality.
- Boundary cost
AI might modify files it shouldn't or introduce unnecessary dependencies. Without clear workspace scope limits, risks multiply.
- Audit cost
When AI output has problems, you need to trace back: who generated this code? Based on what context? Which files were modified?
My solution is to establish a verification workflow:
- After each AI code generation, review the diff first
- Run existing tests to confirm no existing functionality is broken
- Manual testing on critical paths
- Retain task trail evidence
The "vibe" in Vibe Coding should not replace rigorous engineering practices. AI makes coding faster, but the verification stage cannot be skipped.
This is exactly the core philosophy of PatchWarden: making AI agent output auditable, verifiable, and reversible.