Why I Stopped Using LLMs to Schedule LLMs

Last year I had 10 open tickets, a week-long deadline, and three AI coding agents installed on my machine. Claude Code, Codex, Gemini CLI. Each one individually capable of knocking out a task in minutes. Together? Absolute chaos. Agent A edits auth.py . Agent B edits auth.py . Agent A's changes get silently overwritten. Meanwhile, Agent C decides to "refactor" the test suite and breaks everything. Nobody runs the linter. Nobody checks types. I spend more time mediating conflicts than I would have just writing the code myself. So I built an orchestrator. And the single most important design decision I made was: the orchestrator is not an LLM . The insight that changed everything My first attempt used an LLM to coordinate the other LLMs. A "manager" agent would read the backlog, decide what to assign where, check in on progress, re-plan when things failed. It was slow. It was expensive. It hallucinated priorities. It forgot what it had already assigned. It spent 40% of total tokens on co