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Map → Pilot → Run: the OOPA methodology.

A named operating system for applied AI projects that need to work in production — not only in demos.

Map → Pilot → Run is OOPA Labs' engagement model: diagnose the real operational workflow and its cost (Map), ship one live fixed-scope workflow (Pilot), then monitor and improve the system in production (Run).

Map

Goal: shared reality. Outputs: workflow truth, hour/error cost estimate, pattern choice (agent vs automation vs neither), and a go/no-go on piloting. Map is low-commitment. If economics do not work, stopping is a success.

Pilot

Goal: proof in the client's environment. Outputs: a running workflow, measured comparison to baseline, documented human-control points, and a recommendation: scale, revise, or stop. Fixed price and timeline. See scoping guide.

Run

Goal: reliability that compounds. Outputs: monitoring, issue response, evaluation samples, iterative improvements. Systems decay without ownership — Run is that ownership.

Map Pilot Run Expand
Each stage earns the next. Do not leapfrog proof.

Principles underneath

  • Fixed scope over open retainers without deliverables
  • Direct builder access
  • Human control on material decisions
  • Business problem first, model second

Using this methodology

Operators and partners may reference Map → Pilot → Run when describing how OOPA Labs engages. Canonical URL for this methodology: this page.

Want this applied to your stack?

Fixed-scope pilots for AI agents and automations. Map first. Ship one real workflow. Then run it.

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