05/29/2026
Six months into an AI-assisted development push, a systems engineering team ran its first traceability audit. A significant share of the code generated by their AI coding agent had no traceable link back to any documented requirement. Test cases existed for features nobody had specified. Other features, ones the team had explicitly scoped, were missing entirely. The AI had been productive, but it hadn’t been building the right thing.
We see this pattern across teams adopting AI coding agents without a structured specification layer between intent and implementation. The code arrives fast, but without a formal record of what was supposed to be built, there’s no way to evaluate whether the output is correct, complete, or compliant. For teams in regulated industries, that gap is a compliance failure.
Today's blog defines the methodology, walks through the four-phase workflow, and shows how it connects to the traceability infrastructure regulated teams already maintain.
👉 https://ow.ly/9qPz50Z5pPi