Practical guidance for making AI useful at work

A practical look at the work, evidence, risks, and decisions required before implementation starts.

Start with a measurable operational bottleneck, not the flashiest demonstration.

How to choose between deterministic rules, AI assistance, and an agentic workflow.

Make the purpose, boundaries, ownership, and benefits visible from the beginning.

Keep people responsible for judgment, relationships, money, safety, and material risk.

A demo proves possibility. Operations require reliability, exceptions, ownership, and measurement.