The first response is the model performing. The third one is where it actually thinks.
Standard workflow: one prompt, one output, copy-paste and move on. That’s not prompting. That’s delegating your judgment to a system optimized to sound confident, not to be right. The first pass is the model telling you what sounds complete. It’s not lying. It’s just not analyzing.
Here’s what changes everything. After you get the first answer, send one more message: “Now argue against that answer. Find the weakest parts and where it could be wrong.” Watch what happens. Things it stated with full confidence get walked back with actual reasoning. The model isn’t hallucinating differently — it’s evaluating from a different mode entirely.
Then the third move: “Given those criticisms, give me the corrected version.” What comes out is noticeably better than the first pass. And you didn’t have to know enough to catch the mistakes yourself.
Why it works: pass one is optimized for sounding helpful and complete. Asking it to attack its own output breaks that loop. Critical mode and helpful mode are different orientations. You’re not asking the same question twice — you’re switching the model’s goal from “defend this answer” to “dismantle this answer.”
Where it matters most: plans, analysis, decisions, writing. Anything that requires judgment. For pure factual lookups, verify those yourself regardless. But for “is this a good approach” questions, the self-critique pass is the difference between shipping a confidently wrong answer and shipping the right one.
Two extra prompts. That’s the whole system.
Frequently Asked Questions
Q: Is there a specific prompt template I should use?
The post focuses on the technique rather than an exact prompt. The steps are straightforward: get your initial answer, then ask the model to argue against it and find weaknesses, then ask for a refined version. You can adjust the wording to fit your style.
Q: Does this technique work for everything?
No. The post emphasizes it works best for judgment-based tasks (plans, analysis, decisions, writing) where reasoning quality matters. For pure factual questions, you should still fact-check independently, the self-critique pass improves reasoning, not accuracy.
Q: Why is this better than asking for multiple answers?
The difference is in how the request changes the model’s mindset. Your first request asks for a complete, helpful answer. The critique request puts the model in critical mode, so it actively looks for flaws instead of defending its original response.
Q: Do I need a powerful model like GPT-4 or Claude for this to work?
Stronger models will likely catch more subtle contradictions, but the technique should work with most modern AI models. You might see different quality levels, but the approach itself is model-agnostic.
Stop asking the model for the answer, ask it to argue against its own first answer
by u/rafio77 in ChatGPTPromptGenius