AI-generated code — why a human audit still matters
Vibe coding speeds up development but leaves blind spots. What an expert audit catches that your tooling does not.
A large share of the code shipped today is AI-generated. That is a huge speed gain — and a new kind of technical debt.
What LLMs silently produce
- API hallucinations: calls to methods that do not exist — or no longer exist — in the library version you use.
- Dead code: "just in case" functions that are never called and inflate your attack surface.
- Patterns copied without context: generic error handling, hardcoded secrets, overly broad permissions.
Why continuous SaaS tools are not enough
A linter or a continuous analysis SaaS works rule by rule. It does not perform a cross-cutting architectural review and does not recognize LLM generation signatures.
That is exactly the scope of an expert audit: crossing architecture, security and performance over the whole repository, then delivering a signed report you can hand to an investor or a buyer.
The more AI-generated code in your codebase, the more useful the audit.
This post is an example — replace it with your LinkedIn content.