Notes on running agent fleets.
What we learn building Maxxwell — supervising many coding agents at once, and what actually breaks when you do.
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How to tell which coding agent is stuck
2026-09-09
Past two or three coding agents, you stop being limited by model quality and start being limited by your own attention. You have more terminals than you can.
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Orchestrating agents: greenfield vs legacy
2026-09-09
Most teams now have more AI output than attention. The real problem is how to run and coordinate multiple AI coding agents without breaking prod or wasting.
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Central conductor vs peer-to-peer agents
2026-09-01
Past one or two coding agents, the problem stops being model quality and becomes orchestration. You’re suddenly a traffic controller for parallel work that can.
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Orchestrated agents vs codegen pipelines
2026-08-31
Developers are now the bottleneck, not the models. Once you’re running five or ten coding agents, the hard part is keeping them aimed, not getting more code.
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Running Claude Code and Codex in parallel
2026-08-30
Most people who run Claude Code or Codex seriously hit the same wall: the agents scale, your attention doesn’t.
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Running Claude Code agents in parallel
2026-08-29
Why the first thing that breaks when you run several coding agents on one repo is the working directory, and what git worktrees fix about it.
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Single agents vs orchestrated fleets
2026-08-29
Past one or two coding agents, the problem stops being code generation and starts being you babysitting terminals.
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IDE plugins vs. agent orchestration layers
2026-08-29
Most teams already run AI coding tools. Stack Overflow’s 2025 survey says 51% of professional developers use AI daily, and JetBrains reports 85% regularly use.