Agent swarms and the new model economics

This post details the evolution of agent swarms, moving from an empirical approach to deliberate engineering. Key contributions include the introduction of a planner/worker agent architecture, a new high-throughput version control system (1000 commits/sec), and novel failure mode mitigations for split-brain design, planner contention, merge conflicts, megafiles, and ossification. It also introduces "review lenses" for decorrelated error correction and a "Field Guide" for agents to institutionalize knowledge and shape their environment via stigmergy. The post presents experimental results showing the new swarm significantly outperforms the old one in building SQLite from scratch, with varying costs depending on model mix.