Workflow first. AI second.
The method is built for teams that need a useful system, not a long transformation program.
A practical loop for AI work.
We keep the method simple because the hard part is adoption, not vocabulary.
Observe
Map the workflow, tools, data, decisions, exceptions, and people involved. We look for the real operating pattern, not the version on paper.
Choose
Pick one useful wedge: a repeated workflow, clear owner, available context, and an improvement the team can recognize.
Build
Ship a focused system with the right mix of automation, AI, human review, data, and interface. Small enough to use, solid enough to learn from.
Improve
Measure what happens in real use, then tighten prompts, process, data, permissions, and handoffs until the system earns its place.
A good AI project starts small enough to ship and specific enough to measure.
If the team does not use it, the work is not done. If the numbers or operating rhythm do not improve, we keep adjusting.