A practical operating model for founders and operators who need decisions, builds, and handovers—not infinite research or vanity AI demos.
Step 1
We start with the revenue, cost, or risk thesis—so scope debates tie back to something measurable.
Step 2
MVPs and AI workflows fail when everything is P0. We document trade-offs explicitly for stakeholders.
Step 3
Human-in-the-loop paths, approvals, logging, and rollback matter as much as model choice.
Step 4
Demos, reviews, and instrumentation land on a cadence you can sustain—not theatre for stakeholders.
Step 5
Ownership, access, docs, and runbooks are part of done—especially when you plan to hire in-house next.