You're six hours into debugging a production issue. The trace points to line 847 in order_processor.rs, but you need to see how the state flowed from the original request through three service hops. You drop the relevant files into Codex, paste the error, and ask for the root cause. It gives you a confident answer that references a function that doesn't exist anymore — it was refactored six months ago.
This isn't a hallucination in the traditional sense. It's Context Blindness — the silent failure mode of AI coding tools that compress your codebase context so aggressively that the output looks correct but assumes a world that no longer exists.
I spent a week reverse-engineering Codex's context compression from the open-source tooling ecosystem and developer reports. Here's what the architecture actually does, and why it breaks your mental model exactly when you need it most.
How Context Compression Actually Works
Codex doesn't treat your codebase as a flat document. It uses a hierarchical chunking strategy that prioritizes files by:
