Everyone wants an AI that picks winners. Almost nobody builds the boring part that makes one useful: a narrow job and a clean feed of inputs.
Think of it like hiring. A new employee fails less from lack of brains than from vague instructions and messy information. Same with any tool you wire up. Give it one specific job — "flag companies that break my screening rules" — not "make me money."
Then mind the plumbing. However you pull your data, the tool can only reason on what actually reaches it. A broken connection or a stale number produces confident nonsense. Garbage in, confident garbage out.
So before you chase a smarter model, sharpen two things: the exact question you're assigning, and the accuracy of what feeds it. The edge was never the intelligence. It was the clarity and the clean input.
What's the first job you'd hand a research helper?