Meta researchers created a mandatory checklist that forces AI to trace code line by line instead of blindly guessing. This structured approach boosted the accuracy of checking real-world code updates to an impressive 93%. Usually, when we ask an AI to check if a software update works, it just looks at the names of the functions and makes a very confident guess. If we want to be absolutely sure the code works, human developers normally have to run the code in expensive and slow testing servers. This paper changes that dynamic entirely by introducing a strict template that forces the AI to write down the exact path the code takes and provide hard evidence for every single claim it makes. Because the AI is forced to slow down and show its work step by step, it catches deeply hidden bugs and proves that patches work with 93% accuracy. The big deal here is that tech companies can now use AI to automatically and reliably verify millions of lines of code without ever paying for the massive computing costs required to actually execute that software. ---- Paper Link – arxiv. org/abs/2603.01896 Paper Title: "Agentic Code Reasoning"