AI Code Guard

What problem are we solving?

AI tools can write software very quickly. In minutes, they can produce a "proof of concept" — a rough working version of an application that demonstrates the idea works. But rough working versions are not the same as production-quality software. Production software needs to be reliable, secure, maintainable, and testable.

What does the orchestrator do about this?

It forces the AI to follow a strict, step-by-step process where the "homework" is written separately from the "answer key" — and the answer key is locked before the homework is attempted. A human expert reviews the answer key for quality, and multiple automated checks verify the homework from different angles. The process has five main stages:

Where do humans fit in?

The system is designed so humans review where it matters most, and automation handles the rest.

What does the output look like?

At the end of the process, you have: Before (POC) One large file or a few tangled files. No tests. No type safety. Hardcoded configuration. No error handling. No logging. Works on the developer's machine; may not work anywhere else. After (Production) Modular codebase with clean separation of concerns. Comprehensive test suite (424 tests in the latest validation project, 169 in the first). Strict type checking.

What does the current version cover?

The current version validates both the individual pieces and the assembled whole. It covers all four levels of the VP-model — implementation, design, architecture, and user — with the User level's content determined by the project's scope profile. The pre-clinical baseline (demonstrated on the confluency and tacit knowledge apps) provides full lifecycle coverage for commercial software.