Embedding AI in Product Processes

Choose one product ritual

Start with a recurring activity: research synthesis, weekly planning, release preparation or feedback triage. Describe the existing output and who depends on it.

Identify the bottleneck before choosing a tool. The best first experiment has a narrow scope, accessible evidence and a reviewer who can tell whether the output is useful.

Ritual:
Frequency:
Current output:
Bottleneck:
People affected:
AI assistance proposed:
Human review owner:

Make evidence and judgment separate

Ask the system to organise evidence before asking it to recommend action. Keep source references, conflicting signals and missing information visible. Avoid uploading material you are not authorised to share.

Use AI drafts to accelerate preparation; have a person decide priorities, tradeoffs and commitments. Keep your original source of truth intact until the proposed changes are reviewed.

• Define approved inputs and access boundaries.
• Retain links to original evidence.
• Check representative and exceptional cases.
• Name the reviewer for every new output.
• Agree on a fallback when the output is unusable.

Review whether the ritual improved

Measure the time saved after review, the quality of decisions and the work introduced elsewhere. If the team spends longer checking the output than it previously spent doing the task, narrow the scope.

Write down the repeatable pattern: input, prompt or configuration, output, review and storage. Share it with a second team member to test whether the benefit depends on one expert operator.

Baseline effort:
Pilot effort including review:
Quality observations:
Unexpected work:
Reusable pattern:
Keep, change or stop:
Next review: