Why your Codebase is Forcing your AI to Underperform

Modern AI coding assistants are significantly hampered by bloated codebases — every unused, abandoned, or “dead” method that gets loaded into an AI’s context window burns tokens and shrinks the reasoning headroom available for the work that actually matters. When an AI must process code nobody runs, it produces weaker suggestions, more hallucinated API calls, and longer, less precise prompts. The challenge is that much of this problematic code isn’t technically “dead” in the traditional static-analysis sense — it simply never executes in production, making it invisible to conventional tools. In this webinar, we’ll show how runtime evidence can identify which code is truly unused, and how to leverage AI itself to safely remove that dead weight — restoring the context headroom your AI needs to perform at its best.