When AI produces vague, inaccurate or generic work, improving the prompt may help. The team also needs to examine the route around it. Was the brief clear? Were the right sources available? Did anyone agree what excellent looked like? Who was meant to check the result?
An agency can generate a finished-looking document before it has answered any of those questions. The cost then lands with the person who has to unpick it under pressure.
Make quality visible before production
Experienced people can recognise good work without finding it easy to explain. AI makes that gap harder to ignore. If the standard only exists in a senior person's head, every draft can become another lesson delivered through corrections.
The Vital Few give the team five observable characteristics of excellence for the work. For a client article, those might be a clear answer to the reader's question, supported claims, a recognisable brand voice, useful original detail and a conclusion the evidence earns. The exact five should come from that team's work and strong examples.
These characteristics should inform the brief, the sources selected, the Agent's job and the review. They should not appear for the first time after the draft has been made.
Correct the cause of repeated mistakes
Suppose a draft keeps inventing a customer result. The countermeasure may be an approved evidence document and a clear rule that missing results stay missing. If the copy always sounds generic, the team may need stronger voice examples and a more specific argument. If the reviewer is overwhelmed, earlier checks or fewer proposed routes may help.
AI can assist with comparison and checking, but it can also miss an error or make one of its own. The person responsible for release still needs to judge claims, context and consequences.
When someone corrects the work, put the useful learning back into the knowledge, examples or method used on the next attempt. Otherwise the same expensive correction becomes part of every project.
Give people better work to do
People should have more time for judgement, ideas and work they are proud of. Spending the day cleaning up avoidable output is a poor return on AI investment, even if the generation count is impressive.
Hollee combines shared knowledge, Agents and editable outputs with coaching in real work. The quality standard belongs to the team, and the system should help them apply and improve it.