AI experiments multiply quickly. Useful systems are rarer.
The weekly review is a small operating ritual that distinguishes temporary excitement from repeatable value.
Gather the evidence
Before the review, collect every experiment from the previous week:
- what task it attempted;
- who used it;
- time saved or quality improved;
- failures and edge cases;
- whether someone would use it again.
A simple record is enough. The goal is comparison, not bureaucracy.
Score the experiment
Evaluate each experiment on four dimensions:
- Value: did it improve an important outcome?
- Reliability: did it work consistently enough?
- Effort: can it be maintained without special attention?
- Risk: what happens if it is wrong?
An impressive demo with low reliability is still a demo.
Decide its status
Every experiment should receive one status:
- stop;
- keep testing;
- document and repeat;
- automate carefully;
- make it part of the standard process.
This is the moment where experimentation becomes operations.
Keep the decision log
Write down why you chose the status. In three months, this record becomes a practical map of where AI creates genuine leverage for the business.
Start small.
Make it repeatable.
- Input: Define the job, audience, constraints and source material.
- Draft: Use AI for structure and options, not the final unchecked answer.
- Review: Check facts, judgment, tone and the consequence of a mistake.
- Deliver: Put the useful output where work actually happens.
- Learn: Record what improved, failed or should change next time.
Make the workflow yours.
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