In 30 seconds

The first useful version should be smaller than the first exciting version. Pick the narrowest slice that delivers real value, build that, and learn from real cases before expanding.

Why this comes up

Ambitious first builds try to handle every case, every exception and every integration at once. They take long to build, are hard to test, and often fail in ways nobody can untangle. A small pilot gives you something working quickly, on real cases, that you can actually judge.

Narrow the scope deliberately

Take your designed workflow and cut it down to the smallest version that is still genuinely useful:

  • Handle the most common case, not every case. Route the rest to a person.
  • Cover one team, one region or one document type first.
  • Keep the AI at a safe autonomy level: draft or suggest before execute.
  • Include the exception path, even a simple one. A pilot without a way to handle the unusual case is not testing the real workflow.

The aim is a slice thin enough to build and evaluate quickly, but real enough that its result means something.

Decide what success looks like first

Before building, write down how you will know the pilot worked. What would good results look like on real cases? What error rate is acceptable given the cost of errors? Deciding this in advance stops a pilot being judged by whether the demo felt impressive.

Keep the reviewer close

Choose a pilot narrow enough that a domain expert can review every result, at least at first. That review is where you learn how the AI actually behaves, which cases it gets wrong, and what the real edge cases are. You cannot get that from a demo.

A small example

Instead of an assistant for all customer email, a team piloted one thing: drafting replies to password-reset requests, for one support agent to approve. It was live in days, the agent reviewed every draft, and within two weeks they knew the real error cases. That evidence, not a demo, decided what to build next.

What this does not solve

A small pilot proves the workflow on a narrow slice; it does not prove it will scale or hold across every case. Expansion has to be earned with evidence, one step at a time. The pilot's job is to teach you, cheaply, whether you are on the right track.

Good enough to move on when

  • The pilot handles one common case end to end, including a simple exception path.
  • Success was defined before building.
  • A domain expert can review every result.
  • The AI's autonomy is kept safe for a first version.