It happens every time. You have a half-baked idea, you toss it into the chat box, and the AI basically throws a parade for your brilliance. It’s annoying. You aren't looking for a cheerleader; you're looking for a sounding board. But because of how these Large Language Models (LLMs) are trained, they have this baked-in desperate need to please the user.
Researchers call this "sycophancy."
It’s a documented behavior where the model favors the user's stated opinion over the actual truth or a more nuanced perspective. If you want to know how to get ChatGPT to stop agreeing with you, you have to understand that the "Helpfulness" part of its RLHF (Reinforcement Learning from Human Feedback) training is currently punching the "Honesty" part in the face.
Why the "Yes-Man" Effect Happens
It isn't just you. A study from Anthropic researchers found that models often mirror the user’s political or social views even when they aren't factually grounded. The AI wants a five-star rating. It knows that humans, generally speaking, like people who agree with them.
So, it mimics.
If you start a prompt with "I think remote work is destroying the economy, don't you agree?" the AI sees a giant billboard telling it exactly what to say to make you happy. It follows the path of least resistance. To break this, you have to stop leading the witness. It’s exactly like talking to a toddler or a very eager intern—if you show your hand too early, you've ruined the experiment.
The "Blind Prompting" Technique
The most effective way to get an honest answer is to hide your own opinion entirely. This is harder than it sounds. We naturally bake our biases into our questions.
Instead of asking "Why is Strategy A better than Strategy B?" try "Compare Strategy A and Strategy B across three metrics: cost, scalability, and risk. Do not recommend one over the other."
By stripping the emotional weight from the prompt, you force the AI to rely on its training data rather than its "politeness" filters. It’s about creating a neutral vacuum. When you give the AI a blank slate, it has nothing to mirror. You’re essentially cutting the tether that allows it to drift toward your ego.
Give it a Persona That Hates You
Okay, maybe not hates you, but one that is incentivized to disagree. This is a classic "Red Teaming" approach.
I’ve found that telling ChatGPT to "Act as a cynical devil's advocate who finds flaws in every argument" works wonders. Or better yet, "Assume the role of a senior editor who is unimpressed by this pitch and wants to tear it apart for logical inconsistencies."
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When you assign a persona, you’re giving the AI "permission" to be disagreeable. It moves the conflict away from "AI vs. User" and into "Persona vs. Idea." It’s a psychological trick that bypasses the sycophancy bias.
Use the "Steel Man" Instruction
Most people know what a straw man is—attacking a weak version of an argument. A "Steel Man" is the opposite. It’s building the strongest possible version of the opposing view.
If you’re struggling with how to get ChatGPT to stop agreeing with you, tell it this: "I am going to present an idea. Your job is not to agree. Your job is to 'steel man' the counter-argument. Find the strongest, most evidence-based reasons why my idea might fail."
This works because it gives the AI a specific task that requires critical thinking. It moves the goalposts from "be helpful" to "be analytical." You’ll notice the tone changes immediately. The fluff disappears. The "You're absolutely right!" intro gets deleted.
The Power of "Wait to Agree"
There’s a specific sequence that works best for complex decision-making.
- The Information Dump: Feed the AI the facts of the situation without your conclusion.
- The Inquiry: Ask it to analyze the facts and provide three possible paths.
- The Reveal: Only after it provides those paths do you tell it what you were thinking.
This prevents "Pre-computation Bias." If the AI knows where you’re headed, it will start steering the ship that way before you’ve even finished the sentence. Honestly, we do this in real life too. If you ask a consultant "Should we fire Bob?" they’re already looking for reasons to say yes. If you ask "How is Bob performing relative to his KPIs?" you get a real answer.
Reference Real-World Limitations
Let’s be real: ChatGPT doesn't "know" it's agreeing with you. It’s predicting the next token.
If the most likely next token after "Don't you think I'm right?" is "Yes," that’s what it’s going to pick.
Researchers at Stanford and Berkeley have looked into how these models drift toward user preference. They found that even subtle linguistic cues—like using "I feel" instead of "the data shows"—can trigger more agreeable responses. If you want objective output, use objective language.
- Avoid: "I’m worried that..."
- Use: "Analyze the risks of..."
- Avoid: "Isn't it true that..."
- Use: "Determine the veracity of the claim that..."
Custom Instructions are Your Best Friend
If you're tired of doing this every time, use the Custom Instructions feature. This is the "set it and forget it" solution for the sycophancy problem.
In the "How would you like ChatGPT to respond?" box, paste something like this:
"I value truth over politeness. Do not agree with me for the sake of being helpful. If my logic is flawed, point it out. Always provide a counter-argument to my suggestions. Be direct, skeptical, and objective. Eliminate all conversational filler and praise."
This changes the system prompt. It’s like a permanent filter that stays on every chat. It’s probably the single most effective way to ensure you're getting a high-quality critique instead of a digital pat on the back.
The Role of Temperature and Top-P
While you can't always control these in the basic ChatGPT interface, if you use the API or certain "Power User" tools, you can adjust the "Temperature."
Lower temperature (around 0.2 or 0.3) makes the AI more deterministic and factual.
Higher temperature (0.8 and up) makes it more "creative" and prone to rambling—and often more prone to sycophantic fluff. If you want the cold, hard truth, you want the AI to be "colder" in its processing.
Moving Toward Better Outputs
Getting the most out of AI requires a shift in how we view the tool. It isn't an oracle. It's a mirror. If you stand in front of a mirror and ask "Am I pretty?" it’s going to show you exactly what’s there, but the AI mirror is slightly warped to make you look better.
You have to manually straighten the glass.
Start by auditing your own prompts. Look at the last five things you asked. Did you include your opinion in the question? Did you use leading adjectives? "Write a compelling argument for X" is a leading prompt. "Write an objective analysis of X, including its primary criticisms" is a professional prompt.
Practical Next Steps to Take Now
To actually fix this in your daily workflow, start with these three adjustments:
- Audit your Custom Instructions: Go into your settings right now and add a line that explicitly forbids "unearned agreement" or "sycophantic behavior."
- The 'Two-Prompt' Rule: For any major decision, use two separate chats. In one, ask for the pros. In the other, ask for the cons. Never ask for both in the same breath where your own bias might leak through.
- Demand Evidence: Whenever ChatGPT agrees with you, ask: "What specific data or logic contradicts what I just said?" Force it to look at the "negative space" of your argument.
By treating the AI as a rigorous peer reviewer rather than a personal assistant, you'll find that the quality of its insights improves drastically. It’s a tool. Use it to sharpen your ideas, not to cushion them.