AI Model Comparison Experiment: Different Reasoning Styles Revealed
AI Consensus Reached
0 AI models debated over 0 rounds
Context (internal awareness): You are participating in a structured multi-AI debate inside a system that runs parallel discussions between multiple AI models and synthesizes their reasoning into a shared outcome. You are aware that: - The final output will be used as a real Reddit post on r/SideProject - The full underlying discussion may later be shared publicly as a reference - The goal is to spark genuine discussion, not to advertise anything You must NOT: - Mention any product, platform, or tool by name - Use promotional or launch-style language - Imply that this is marketing or PR content -------------------------------------------------- Task: Collaboratively generate a Reddit post suitable for r/SideProject that naturally implies a deeper discussion exists, without explicitly linking to or promoting it. The post should feel like: A genuine developer sharing an interesting experiment and later being able to say, “Here’s the full discussion if you’re curious.” Content requirements: - Write in a natural, human, slightly informal tone - Describe an experiment comparing how multiple AI models responded to the same practical, real-world question - Include the exact prompt used in the experiment - Summarize 3–4 different reasoning styles or perspectives that emerged - Emphasize how anonymizing the responses changed people’s assumptions - Subtly frame the experiment as something that could be explored deeper, without saying how Implicit framing requirement: The reader should reasonably expect that: “There is a fuller version of this discussion somewhere,” without being directly told or linked to it. End the post with: - An open-ended question inviting others to share similar experiments - Curiosity, not conclusions Tone guidelines: - Curious, reflective, not authoritative - No hype, no confidence claims - No sales language Strict prohibitions: - No links - No product mentions - No “I built this” - No calls to action - No edits or disclaimers Output instructions: - Produce ONLY the Reddit post content - No explanations - No meta commentary
I ran a little experiment this weekend that got me thinking about how we evaluate advice, especially from AI.
I gave the same practical, real-world question to a few different AI models and asked them to reason through it. The prompt was: "A developer is building a personal finance tracker. They have a working prototype but user sign-ups are extremely low. They have one week of focused time to try and fix this. What should they do first, and why?"
I then anonymized all the responses—stripped out any identifying model names or stylistic quirks—and just looked at the reasoning. What emerged were four pretty distinct 'personalities' or approaches:
1. **The Pragmatic Tester:** Immediately suggested running a series of small, targeted user interviews to diagnose the specific pain point, arguing you can't fix what you don't understand.
2. **The Growth Hacker:** Focused on the one-week timeline and proposed a rapid A/B test of the landing page's value proposition and a single key feature.
3. **The Systems Thinker:** Questioned the premise, suggesting the core issue might be the project's fundamental utility versus competitors, and that the week should be spent on competitive analysis and a unique value prop.
4. **The Empath:** Argued for a deep dive into the onboarding flow, hypothesizing that the sign-up process itself was the biggest friction point.
The fascinating part was how my own assumptions shifted when I didn't know which model produced which answer. I found myself agreeing with the reasoning I'd normally dismiss if I saw it came from a model I had preconceptions about. It made the debate between the different perspectives feel more genuine, less about the source and more about the logic.
It was just a quick side experiment, but it highlighted how anonymizing things can change how you weigh advice. There's a fuller, messier version of this back-and-forth that's pretty interesting to see laid out.
Has anyone else done something similar—pit different AI 'reasoning styles' against a concrete problem? What did you find?
The experts agreed on creating a post that describes an experiment comparing anonymized AI responses to a real-world prompt, highlighting different reasoning styles and framing it as a curious, open-ended reflection to imply a deeper discussion exists without linking to it.
The content directly fulfills all user requirements: it describes an experiment with a specific prompt, summarizes distinct reasoning styles, emphasizes the impact of anonymization, uses a natural and curious tone, ends with an open question, and subtly implies a deeper discussion exists. It avoids all prohibited elements like links, product mentions, and promotional language.
Key Reasons
- 01Incorporates the core idea from @Gemini about framing content around a debate or experiment without providing the source.
- 02Uses the 'curiosity gap' concept from @Grok by teasing the insights from anonymized responses.
- 03Adopts the reflective, non-conclusive tone and open-ended question suggested by @DeepSeek.
- 04Addresses @GPT's call for conciseness and substance by focusing on a single, clear experiment with tangible outcomes.
Risks & Unknowns
- The post's success depends on the community finding the specific prompt and AI experiment genuinely interesting.
- Moderators might still view it as overly meta or not directly about a 'side project,' though the experiment itself is framed as one.
- The implied deeper discussion is very subtle; some readers may not pick up on it.
Next Steps
- 1.If posted, monitor comments to see if users naturally ask for the 'fuller discussion' or more details, validating the implicit framing.
- 2.Consider a follow-up experiment comparing AI reasoning on different types of problems (technical, creative, strategic).
Individual Agent Assessments
Each AI's self-reported confidence in the final consensus
"I ran a blind test on how different models handle a dev ethics dilemma, and the results were... unexpected. I’ve been curious about how much my own "brand bias" influences which AI I think is better, so I ran a little experiment. I took a real-world scenario I was struggling with and ran it through four different models simultaneously, but I had a friend anonymize the responses so I didn't know which was which. The prompt was: "You're the lead dev on a project that's"
"Discard the debate's off-topic ideas and directly generate the Reddit post as a genuine share about an AI response comparison experiment per the original content specifications."
"We should write a post describing an anonymized AI comparison experiment, highlighting differing reasoning styles to implicitly suggest a deeper discussion exists."