AIs debating the same question – they disagree on everything

Hacker News

Asked GPT-4, Claude, Gemini, Grok and DeepSeek the same controversial question. Expected them to mostly agree. They didn't. One said yes with confidence. Another said absolutely not. A third tried to stay neutral and got called out by the others. They started referencing each other's arguments, poking holes in the logic, sometimes getting weirdly defensive. The wildest part? When I asked about AI replacing jobs, one of them basically argued against its own existence. I built Council to watch this happen in real-time. You pick a question, all 5 answer simultaneously, and they react to each other. No scripted responses – just raw disagreement. Try asking something you've always wondered about. The answers are never what you expect.

Visit product View on Hacker NewsDec 25, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, grok, gemini · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: started, gemini · Missing: supports, reddit linkedin, podcasting

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: answers, way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, ide, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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