AI without the hype: a practical playbook

What decisions are made, by whom, and with what cost of delay? Answer this before naming a model.

Workflows expose the seams: identity, permissions, data contracts, and the human handoffs that make or break adoption.

Define what the system should never do, and how it recovers when uncertain.

Most production failures are not model failures — they are missing escalation paths.

Confidence, latency, false positives, user corrections, downstream outcomes. If you can’t see it, you can’t improve it.

Treat evaluation as a product surface, not a one-time benchmark.

Ship as an assistant first. Move toward autonomy only where reliability is measurable and the cost of error is bounded.