Everything, Everywhere, All at Once: A Better Job for the Robot
Most of the energy going into AI and analytics right now is aimed at getting it to produce numbers you can trust. I think that's the wrong job. In our monthly executive report, the figures always come from code. That single rule changes what AI is actually useful for. Because when a number moves, the hard question was never what changed - it was why. And the answer is scattered across releases, related metrics, past investigations and half-remembered caveats in corners of the business no one person can hold in their head. So I built an agent that reads and connects all of that context, all at once. In five minutes I'll take one real example, walk through the exact chain the agent followed to explain it, and make the case that AI's real job was never the number. It's the why.
