77.1% on ARC-AGI-2 and still can't stop adding drive-by refactors. ARC-AGI-2 tests novel pattern induction, it's genuinely hard to fake and the improvement is real. But it doesn't measure task scoping, instruction adherence, or knowing when to stop. Those are the capabilities practitioners actually need from a coding agent. We have excellent benchmarks for reasoning. We have almost nothing that measures reliability in agentic loops. That gap explains this thread.