Diminishing-returns stopping point
- Industry term
A diminishing-returns stopping point is the moment to end an editing loop because another pass is unlikely to improve the result enough to justify the time, cost, or risk of making it worse.
Asked to improve a draft, an AI nearly always finds something to change. Once the big problems are fixed, what remains is mostly wording, so passes trade one phrase for another or rewrite parts that were right. A factual report gains little from that, while in a slogan the wording is the job.
Where you’ll meet it
You've revised your cover letter with your AI five times. The last two passes swapped “driven” for “passionate” and back, and the newest version dropped the sentence about your project-management certification.
What to do
Stop asking for passes. Open the job listing beside your drafts, keep the version that answers it best, and put the certification sentence back in yourself.
Easy to mix up
| Diminishing-returns stopping point | Review loop |
|---|---|
| The call to stop revising | The whole cycle of checking, sending back, and revising |
Check yourself
You set an AI to polish your product FAQ overnight, one pass after another, with nobody watching. Which stopping rule will hold up?
Go deeperIf a second AI grades passes, measure how far its scores wander
The stopping point is a rule of thumb with no measured threshold, and useful passes vary by task. Some automated loops stop when a separate grader model's score stops rising, yet such graders can score one draft differently on each run. Scoring the same draft several times shows how far the grade moves by chance, so a rise within that range means little.