Using an LLM Council for Research
omarsar0 · x · 2026-07-16
The author shares how they use an LLM Council for AI research instead of throwing a single agent at a task.
The core approach: assign distinct roles and goals to different agents. For example, using rafthq to build a small team: a scout to find new papers, a critic to challenge conclusions, and a synthesizer to write briefs. The author emphasizes that the key is not just 'multi-agent' but well-designed roles and objectives.
They also note the team can run automatically on a schedule, posting updates directly to threads, so they don't need to monitor constantly; research accumulates like a snowball.
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