Starting at the wrong end.
The instinct is to start with the model, because the model is the exciting part. But a model dropped into an organization that cannot see itself is a fast answer to a question nobody has framed. It optimizes a metric that may not matter, against a baseline nobody measured, in a process nobody instrumented.
Signal first inverts the order. Before you automate a decision, you make the decision visible: what triggers it, what feeds it, what it costs to get it wrong. Only then does intelligence have something true to stand on.
See clearly, then act.
Observability is not dashboards for their own sake. It is decision-grade telemetry: the specific signals a specific decision depends on, captured continuously, in context. Get that right and the model almost designs itself, because you finally know what you are optimizing and why.
The compounding effect
Signal compounds. Every decision you make visible makes the next one easier to govern, because the data fabric you built for one carries the next. Organizations that invest in signal early move faster later — not despite the discipline, but because of it.
You cannot automate a decision you cannot see. Observability is the cost of admission, not an upgrade.