01

Give AI a verb

“AI-powered” is not a responsibility. Draft, classify, extract, compare, explain, generate, route, and recommend are useful starting verbs. Add the object, the user, and the decision that follows.

02

Match freedom to consequence

A playful design exploration can tolerate variety. A payment action or policy answer cannot. As consequence rises, narrow the output, require stronger evidence, and add human approval or deterministic checks.

03

Design the context before the prompt

Decide which records, documents, policies, conversation history, and tool results the model can use. Define who may see each source and how stale or missing information appears. Better context usually matters more than a clever instruction.

04

Make uncertainty usable

The interface can show sources, ask a clarifying question, present alternatives, mark an assumption, or route the task to a person. Hiding uncertainty makes a smooth demo and a dangerous product.

05

Evaluate complete tasks

A response can look good and still fail the job. Test representative inputs, edge cases, prohibited behavior, latency, cost, tool actions, and whether a user can recognize and recover from a mistake.

06

Keep an exit from automation

People need a visible way to edit, undo, pause, retry, or take over. Operators need a record of what the system saw and did. Those controls are part of the product, not evidence that the AI failed.