When your developers use AI coding assistants to integrate your APIs, the quality of that integration depends entirely on the quality of the context the AI is working from. Bad context produces code that compiles but fails in production: wrong authentication flows, outdated SDK methods, silent security vulnerabilities.
That is not a developer problem. It is an infrastructure problem. Engineering teams are currently absorbing this as review overhead, support tickets, and delayed release cycles.
Fixing it requires changing what the agent works from, not how it thinks. We ran a controlled experiment to measure exactly that. Here are the results.
