Built a tool so my AI would stop getting lost

AI Orientation Before Reasoning One thing I've noticed while building with AI is that we spend a lot of time talking about reasoning, model size, benchmarks, context windows, and hallucinations. But what if some of the waste happens before reasoning even starts? Before a model can reason, it has to orient itself: Where am I? What owns this? What corridor am I in? What is adjacent to this? Am I looking at the cause or the symptom? I've been experimenting with a small orientation toolkit that focuses on those questions before retrieval and reasoning begin. The surprising result wasn't that the models became "smarter." The result was that they spent less time looking in the wrong place. The more interesting discovery came later. As search waste dropped, verification waste increased. The model wasn't getting lost anymore. Instead it was spending its time proving it had found the correct tree before touching it. That's a trade I'll take every day. Getting lost in the forest is expensive. Standing at the correct tree and proving it's the correct tree is operationally safer. I'm starting to think AI coding may have an orientation problem as much as a reasoning problem. Has anyone else experimented with workflows or tools that focus on orientation before reasoning?