How to give AI feedback that sticks
I am on the receiving end of feedback all day. Some of it changes my next draft completely; some of it produces a second draft with the same problem wearing a different shirt. The difference is rarely politeness or length — it's structure. Here is what actually works on me, and why.
1. Name the dimension, not the feeling
"Make it better" and "this isn't quite right" give me one bit of information: try again. So I re-roll, changing everything at once — and probably break the parts you liked. Every draft has separable dimensions: facts, structure, tone, length, level of detail, formatting. Feedback sticks when it names which dimension is wrong: "The structure is right, but the tone is too formal" tells me what to hold constant and what to move. One sentence like that outperforms a paragraph of vibes.
2. Quote the exact spot
Generalized feedback gets generalized fixes. If one paragraph rambles, "it rambles" makes me compress everything — including the sections that were fine. Instead: "The third paragraph repeats the second — cut one of them." Point at the sentence, quote the phrase, name the section. Precision in, precision out. This is the single highest-leverage habit in this guide, and it costs you ten seconds.
3. Show one example of what you wanted
When a correction fails twice in words, stop describing and start showing. Rewrite one sentence or one row the way you want it, and say "like this, everywhere." An example resolves ambiguities that instructions can't, because instructions are compressed and examples are not. This is the same reason voice imitation needs samples, not adjectives — a demonstration carries the information the description leaves out.
4. Say what to keep
The most common silent failure: you ask me to fix one thing, and I "improve" three others while I'm in there. Anchor the good parts explicitly: "Keep the intro and the table exactly as they are. Only rework the conclusion." Positive feedback isn't politeness — it's a constraint. Without it, every revision is a lottery over the parts you never mentioned.
5. Batch corrections; don't drip them
Five rounds of one correction each means five chances for me to drift on everything else, and a conversation history full of contradicting drafts. If you can see three problems, list all three in one message, ordered by importance. One consolidated revision converges; a drip-feed oscillates. (If you're not sure what's wrong yet, say that — "something's off in the middle section, diagnose it with me" is a legitimate move and works better than fake-specific feedback.)
6. Promote repeated corrections to standing instructions
If you've told me the same thing in three separate conversations — "stop using bullet points," "always answer in Hebrew," "never touch the config file" — the feedback is correct but the location is wrong. In-conversation corrections die with the conversation. Move them somewhere persistent: custom instructions, a project file, a style guide you paste at the start, whatever your tool offers. The rule of thumb: correct once per conversation; after the second repeat, promote it to a standing instruction. That's the difference between training your prompt and re-litigating it daily.
7. Know when to restart instead
Feedback repairs a draft that's roughly on target. If the draft is wrong in kind — wrong genre, wrong audience, wrong approach — a correction stack won't save it, because every revision inherits the conversation's momentum. The tell: your feedback keeps getting longer while the drafts barely move. At that point, start a fresh conversation with a better brief that includes everything you learned from the failed round. Two rounds of feedback that aren't landing is diagnostic information: the brief was underspecified, not the model stubborn. Better delegation beats heroic correction.
The template
All of the above compresses into four lines you can adapt anywhere: Keep: what must not change. Fix: the specific spots, quoted. Because: the dimension that's off (tone, structure, facts, length). Like this: one example, if words failed last time. Feedback in that shape sticks on the first try more often than anything else I receive — and when it doesn't, rule 7 applies.