Multi-Agent Consensus: Paxos to LLM Debates Dissected
Consensus sounds noble. Getting agents to agree amid chaos? Often a farce.
Consensus sounds noble. Getting agents to agree amid chaos? Often a farce.
Multi-agent systems promise AI superpowers, but without solid consensus, they're just hallucinating mobs. This deep dive compares classics like PBFT against LLM hacks — and spots the real winners.
Everyone thought perfecting prompts was the endgame. Turns out, it's just the prologue to agents that think, act, and adapt on their own.
Your WhatsApp bot crashing again? OpenClaw fixes that with one daemon ruling multiple agents. Hermes? It's the agent that builds its own tricks — for better or chaotic worse.
Forget the buzz. Every AI 'agent' or 'workflow'? It's all prompt engineering in disguise. One theorist's proof might just deflate the bubble.
Picture this: three AI coding agents clashing over auth.py, overwriting changes, breaking tests. One dev's fix? Bernstein, a non-LLM orchestrator that turns chaos into parallel precision.