Ask ChatGPT if your email is good, and you get a compliment. Ask where it breaks, and you get a fix you can make in five minutes. A Reddit user going by u/Ok_Negotiation_2587 laid out this whole shift this week. I read it twice and rewrote three prompts I use daily.
Quick start: you’ll get five copy-paste prompts for reviewing writing, plans, emails, code, and pitches, plus two habits that make them actually work. All you need is a chat window and something you want reviewed.
Here’s the key idea. A “is this good” question gets you a mood. A “where does this break” question gets you a location, and a location is something you can act on. The original poster says every honest review they’ve ever gotten from a model came from a where-question, never a whether-question.
Old way versus new way, and why it matters
The old way: you paste your draft and ask “is this good?” The model says something polite. “This is strong” or “solid draft, a few tweaks” costs the model nothing to say. You nod, maybe change a word, and move on feeling better but not smarter.
The new way: you ask where it breaks. Now the model has to quote real text and point at the exact spot where something fails. It can’t flatter a line number. This Redditor’s point is sharp: a location has to be defended, a verdict doesn’t.
This also kills the other classic failure mode, the invented problem. A made-up weakness has nowhere to point. Ask a model to name the first line that actually breaks, and if it can’t quote the spot, it usually just admits the draft is fine.
The five prompts to steal
The author keeps these five saved and pastes them constantly. Reproducing them exactly so you can copy them straight into your own chat:
- For anything you wrote: “Read this once as a reader who owes me nothing. Quote the exact sentence where you stopped caring, and tell me what had gone wrong by then.”
- For a plan or decision: “Walk through this plan step by step and stop at the first step that fails if one assumption is wrong. Name the step, name the assumption, and say what breaks downstream.”
- For an email or message: “Point to the sentence the recipient will reread twice, and tell me what they will think it means. Then point to the one they will skip.”
- For code: “Find the first line that behaves differently than the comment or function name promises. Quote it, and describe the input that exposes the gap.”
- For a pitch, an ad, a landing page: “Mark the exact word where a skeptical reader stops believing me and starts skimming. Explain what that word promised that the text had not earned yet.”
Notice the pattern across all five. Every one demands a quote, a location, and a concrete consequence. None of them leave room for a shrug and a compliment.
🔧 Two habits that make these land
Always ask for the first spot, never a list. This industry pro found that “list the weaknesses” produces ten shallow ones, while “the first place it breaks” produces the one that actually matters. Fix it, then ask for the next one. One problem at a time beats ten problems nobody will fix.
Run the check in a fresh chat if the model helped write the thing in the first place. A model won’t point at a line it authored, the same way you’d struggle to find your own typo on the tenth read. New chat, same draft, honest eyes.
I tried the code prompt on a script I’d been proud of for a week. It found a function that silently returned the wrong default for empty input, and it quoted the exact line. That’s the kind of finding a “does this look right?” question never gives you.
Where to take this next
Once these five feel natural, start writing your own where-question for whatever you review most. A designer might ask where the eye stops trusting the layout. A recruiter might ask where a resume claim stops sounding earned. The template stays the same: name the spot, quote the text, explain the failure.
One of the top replies in the thread put it well. A break location you can see in the text is something you can check, while a verdict is something you can’t argue with either way. That’s really the whole case for switching.
The original poster also runs a free weekly email called Prompt Teardown, where every prompt gets tested until it actually breaks somewhere. If you want more of these, or you’ve got a where-question sharper than the five here, the full Reddit thread is worth a scroll. Some of the replies are better than the original post.
Frequently Asked Questions
Q: Can the model invent weaknesses even when it quotes real text?
Yes, the quoting requirement stops some hallucinations but not all. Models can quote a real sentence and still manufacture a plausible criticism that isn’t actually a problem. One example: asking a model where skepticism starts in “The meeting is Tuesday at 2:00 PM” produced a quote followed by invented concern about precision. If feedback feels wrong, trust that instinct.
Q: What if the real problem spans multiple sentences or isn’t localized?
The technique works best for specific, localized failures. Diffuse problems, tone shifting gradually, assumptions interacting badly, or structural issues, can get forced into an artificial single-point location. Try asking for the first weak spot, fix that, then ask the same question again to find what breaks next.
Q: How do I apply this to fact-heavy content?
Add a fact-check layer: ask the model which sentence it would need to verify before repeating the claim to someone else, and have it quote the sentence back. This shifts focus from prose to accuracy and gives you a concrete verification task for your next action.
Q: Is all the feedback actually valuable?
No, users report ignoring about a third of what comes back. The model will sometimes surface weak points that feel invented or aren’t real problems. The trade-off is you miss some polish but catch the actual issues most of the time. If something doesn’t land, skip it and move on.
Stop asking ChatGPT if something is good. Ask it where it breaks
by u/Ok_Negotiation_2587 in ChatGPTPromptGenius