🤖 Large Language Models

Why Deterministic Schedulers Beat LLMs at Running AI Coding Agents

AI coding agents are powerful alone—but unleash a horde without a smart overseer, and your repo becomes a warzone. Enter Bernstein: a no-LLM scheduler that turns agent anarchy into orchestrated wins.

Flow diagram of Bernstein's decompose-spawn-verify-merge pipeline for AI coding agents

⚡ Key Takeaways

  • Ditch LLMs for scheduling—use deterministic Python like OS schedulers for reliable agent coordination. 𝕏
  • Git worktrees provide perfect isolation, enabling true parallelism without conflicts. 𝕏
  • Contextual bandits dynamically pick optimal models per task, slashing costs while maintaining quality. 𝕏
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Originally reported by dev.to

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