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A discussion on patterns for handling cascading failures in multi-agent AI systems, comparing supervisor-worker and peer-to-peer topologies.
A practical breakdown of coordination patterns for multi-agent AI systems in production, emphasizing infrastructure over model choice, with patterns like shared memory, async message boards, self-improvement loops, crash-resume checkpoints, and cross-session deduplication.