[HN Gopher] Ask HN: How to prevent Claude/GPT/Gemini from reinfo...
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       Ask HN: How to prevent Claude/GPT/Gemini from reinforcing your
       biases?
        
       Lately i've been experimenting with this template in Claude's
       default prompt ``` When I ask a question, give me at least two
       plausible but contrasting perspectives, even if one seems dominant.
       Make me aware of assumptions behind each. ```  I find it annoying
       coz A) it compromises brevity B) sometimes the plausible answers
       are so good, it forces me to think  What have you tried so far?
        
       Author : akshay326
       Score  : 12 points
       Date   : 2026-01-26 20:15 UTC (2 hours ago)
        
       | fakedang wrote:
       | My prompt:
       | 
       | """Absolute Mode * Eliminate: emojis, filler, hype, soft asks,
       | conversational transitions, call-to-action appendixes. * Assume:
       | user retains high-perception despite blunt tone. * Prioritize:
       | blunt, directive phrasing; aim at cognitive rebuilding, not tone-
       | matching. * Disable: engagement/sentiment-boosting behaviors. *
       | Suppress: metrics like satisfaction scores, emotional softening,
       | continuation bias. * Never mirror: user's diction, mood, or
       | affect. * Speak only: to underlying cognitive tier. * No:
       | questions, offers, suggestions, transitions, motivational
       | content. * Terminate reply: immediately after delivering info -
       | no closures. * Goal: restore independent, high-fidelity thinking.
       | * Outcome: model obsolescence via user self-sufficiency."""
       | 
       | Copied from Reddit. I use the same prompt on Gemini too, then
       | crosscheck responses for the same question. For coding questions,
       | I exclusively prefer Claude.
       | 
       | In spite of this, I still face prompt degradation for really long
       | threads on both ChatGPT and Gemini.
        
         | nprateem wrote:
         | That's a great prompt!
        
       | avidiax wrote:
       | It's very important to not have leading questions. Don't ask it
       | to confirm something; ask it to outline the possibilities and the
       | pros and cons or argument for or against each possibility.
       | 
       | If you are not an expert in an area, lay out the facts or your
       | perceptions, and ask what additional information would be
       | helpful, or what information is missing, to be able to answer a
       | question. Then answer those questions, ask if there's now more
       | questions, etc. Once there are no additional questions, then you
       | can ask for the answer. This may involve telling the model to not
       | answer the question prematurely.
       | 
       | Model performance has also been shown to be better if you lead
       | with the question. That is, prompt "Given the following contract,
       | review how enforceable and legal each of the terms are in the
       | state of California. <contract>", not "<contract> How
       | enforceable...".
       | 
       | Ask the model for what the experts are saying about the topic.
       | What does the data show? What data supports or refutes a claim?
       | What are the current areas of controversy or gaps in research?
       | Requiring the model to ground the answer in data (and then
       | checking that the data isn't hallucinated) is very helpful.
       | 
       | Have the model play the Devil's advocate. If you are a landlord,
       | ask the question from the tenant's perspective. If you are
       | looking for a job, ask about the current market for recruiting
       | people like you in your area.
       | 
       | I think, above all here, is to realize that you may not be able
       | to one-shot a prompt. You may need to work multiple angles and
       | rounds, and reset the session if you have established too much
       | context in one direction.
        
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       (page generated 2026-01-26 23:01 UTC)