Many useful agents never act on their own. They prepare work, and a person decides what happens next. Teams sometimes see this pattern as a stepping stone, but it is often the right long-term design.
Design the review step deliberately. The reviewer should see:
- the original request;
- the agent's draft;
- the sources it used.
They should be able to edit the draft as easily as approve it, so that reviewing is quicker than writing from scratch.
Record every action. The audit trail should show:
- what the agent drafted;
- what the reviewer changed;
- who approved the result, and when.
This helps with quality, training and compliance.
Explain how roles change. When an agent takes on preparation, the role moves towards review, judgement and improvement. Be open about which tasks are moving and what each role gains in return.
Teach supervision as a skill. Reviewing AI output well is a learnable skill. It covers:
- spotting unsupported statements;
- checking tone;
- knowing when to escalate.
It is worth training for.
Keep judgement where it belongs. Decisions that affect customers, colleagues or money stay with a named person, even when an agent does the preparation.
A short checklist:
- Can a reviewer see the agent's sources alongside its draft?
- Does your audit trail separate what the agent wrote from what a person changed?
- Have the people affected been told how their role will change?
From the 2SD Technologies team (2sdtechnologies.com). Part 5 of "Don't just build agents".
