# A convincing answer still needs a proper check. · Requirements are clear, but errors appear unpredictably

All stories are fictional. They do not describe specific people, companies or projects. Any resemblance is coincidental.

A tool produces documents quickly and the leader likes the first examples. A closer review reveals missing conditions and incorrect conclusions. Participants disagree about quality because they assess different aspects of the text and have not agreed a shared evaluation method.

## Where we could start

Gather permitted examples and organise a repeatable evaluation against agreed requirements. Separate significant errors from acceptable limitations, pass observations to technical specialists and prepare a decision about the next stage.

## What you would have

Evaluation findings with examples of errors, limits on use and questions requiring technical investigation.

## Participants

The task owner, specialists reviewing the content and the technical team or solution supplier.

## Roles and decisions

I manage the evaluation and preparation of the decision. The technical team investigates causes and possible corrections; a few examples cannot establish guaranteed reliability.

## Factual experience, separate from the fictional story

MVP Lab / Pivot: Client requirements, approvals, demonstrations and release review.
https://apiperson.com/experience/#work-pivot

Keiss Media: Managing digital campaigns: client requests, estimates, budgets, suppliers and delivery.
https://apiperson.com/experience/#work-keiss

[People disagree about acceptable quality](https://apiperson.com/ai/ai-evaluation/criteria/)

[Requirements are clear, but errors appear unpredictably](https://apiperson.com/ai/ai-evaluation/errors/)

[The output looks suitable, but reviewing it takes too much work](https://apiperson.com/ai/ai-evaluation/review-effort/)

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