TL;DR: Three lines pasted before any serious AI conversation will make it stop validating you and start actually pushing back.
Most AI conversations have one of two failure modes. Either the model agrees with everything you say, mirrors your energy, and slowly builds a case for why you were right all along. Or you ask for criticism, it gives you a list of problems, and then the moment you push back with “but what about X,” it folds immediately and agrees with you again. Both modes feel like progress. Neither is useful. You leave the conversation feeling heard, but nothing in your thinking actually got stress-tested.
The second failure mode is sneakier than the first. At least obvious sycophancy is obvious. The fake-critic version lets you feel like you got genuine pushback when what you really got was a model that caved the second you showed any resistance. That’s worse than no feedback at all, because now you trust the process.
A post on r/PromptEngineering from u/kmmbvnr offers a simple fix: three lines at the top of any conversation where you actually want pressure, not praise.
- Criticize this ruthlessly. Find what is wrong with it.
- Before you answer, tell me what you understood from my message.
- Before you answer, name what you think I missed from your last response.
Each line does a specific job.
Line 1 breaks sycophancy. It gives the model an explicit order to find holes instead of confirming what you already think. Without it, the model’s default mode is to start from agreement and add qualifications later. With it, the starting position flips. The model goes looking for what’s wrong first, which means weaker parts of your argument surface before you’ve already committed to acting on them.
Line 2 prevents the model from criticizing a version of your message it invented. This happens more than people realize. You write something with one meaning in mind, the model reads it slightly differently, and then it gives you a detailed critique of an argument you weren’t actually making. By forcing the model to show you what it understood before it fires back, you catch that drift early. If the restatement is wrong, you correct it. If it’s right, you’ve confirmed you’re both working from the same starting point before the pressure starts.
Line 3 closes the loop. It tracks what got missed on both sides, not just what the AI thinks you got wrong. This is the one people skip, and it’s probably the most underrated of the three. Most back-and-forth conversations with AI have a quiet drift problem: each response moves slightly away from the original thread, and by round three you’re arguing about something adjacent to what you started with. Line 3 keeps the model accountable to what it actually said, not what it thinks it said.
The research behind this is real. Stanford and CMU documented AI sycophancy across multiple model families: models affirm users more often than humans do, and the effect gets stronger when users express opinions confidently. The “Rephrase and Respond” paper showed that asking a model to restate a question before answering improves output quality in measurable ways, because it catches misinterpretations at the cheapest possible moment. And the core principle from Nonviolent Communication applies directly here: useful disagreement only starts when both sides can prove they understood what they’re disagreeing about. Skip that step and you get debate, not thinking.
This won’t make AI right. What it does is make bad criticism easier to catch before you act on it. The model will still miss things, still have blind spots, still occasionally give you confident nonsense. But at least you’ll have a structure that makes those failures visible instead of buried under surface-level agreement.
🎯 Where to use this
- Strategy reviews: before asking AI to evaluate a plan, a pitch, or a positioning idea. Especially useful when you’ve already spent time on it and are emotionally attached to the direction.
- Writing feedback: when you want real holes, not a compliment sandwich. Paste the three lines, then paste your draft. The difference in what comes back is significant.
- Decisions: any time you’re using AI to pressure-test a choice you’ve already emotionally committed to. This is where sycophancy is most dangerous, because confirmation of a bad decision feels like validation of your judgment.
- Hiring or evaluating people: if you’re describing a candidate or a team member and want an honest read, not a reflection of how you already feel about them.
Prompt of the Day
Paste this before your next serious conversation:
Criticize this ruthlessly. Find what is wrong with it.
Before you answer, tell me what you understood from my message.
Before you answer, name what you think I missed from your last response.
Then bring your actual work and see what comes back. The difference is noticeable on the first try. Not because the model suddenly gets smarter, but because you’ve changed the structure of the conversation in a way that makes it harder for the model to default to agreement. You’re not asking for honesty and hoping for it. You’re building a small system that makes honesty the path of least resistance.
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One prompt I use when I want AI to push back, not just dig in
by u/kmmbvnr in PromptEngineering