But instead of relying on a single model, I used multiple AI models, running as SambaNova Systems-hosted models via OpenRouter.
Models in the council:
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deepseek-v3.1-terminus
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deepseek-chat-v3.1
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gpt-oss-120b
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deepseek-chat-v3-0324
Here’s how the reasoning worked:
Step 1 – Independent thinking
Each model answered the question on its own, without seeing the others’ responses.
Step 2 – Peer review
The models then reviewed and ranked each other’s answers anonymously, focusing on clarity and factual accuracy.
Step 3 – Final synthesis
A final response was produced by reconciling disagreements and correcting errors.
The interesting part:
Several models confidently repeated the same factual mistake — and the multi-model process caught it.
That’s the real takeaway:
AI isn’t wrong because models are weak.
AI is wrong when it reasons alone.
Multi-model reasoning helps:
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Reduce blind spots
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Catch shared hallucinations
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Increase trust in the final output
This feels much closer to how humans make good decisions:
multiple perspectives, critical review, and consensus over confidence.
This is the direction of AI I’m most excited about — not just faster answers, but more trustworthy ones.
I’ll share this properly once I’ve cleaned up the code and polished a few things.
Stay tuned — this one’s worth it. 
ai #MultiModelAI #AgenticAI #AIReasoning #GenerativeAI #SambaNova #OpenRouter
