Omar Sanseviero releases LLM Council skill
Omar Sanseviero has released an LLM Council skill for AI agents, inspired by Andrej Karpathy's concept of multi-perspective LLM deliberation. The skill runs multiple open-weight models in parallel via the Fireworks AI API to answer queries, has them rank each other's anonymized responses to stress-test the advice, and then uses a designated "Chairman" model to synthesize the final output, mitigating single-model failure modes and sycophancy.
Multi-model consensus architectures are becoming standard for agent workflows, and packaging them into reusable skills lowers the barrier to entry.
* Fireworks AI's fast inference helps mitigate the latency overhead of running multiple models in parallel.
* Cross-model ranking is an elegant way to reduce bias and sycophancy, though it does increase overall token consumption.
* Synthetic aggregation via a "Chairman" model provides robust final answers but requires careful system prompting to avoid diluting strong individual responses.
DISCOVERED
1h ago
2026-06-15
PUBLISHED
1h ago
2026-06-15
RELEVANCE
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omarsar0