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Parallel AI Agents Only Work with Genuinely Isolated Tasks

Fazm Team··2 min read
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Parallel AI Agents Only Work with Genuinely Isolated Tasks

Running five agents at once changed everything for me. But it took several painful failures to learn the one rule that makes it work: each agent must have zero overlap with every other agent.

Not minimal overlap. Not "they probably will not touch the same files." Zero.

Why Overlap Kills Parallel Agents

When two agents modify the same file, you get merge conflicts at best and silent data corruption at worst. Agent A reads a config file, makes changes based on what it saw, and writes it back. Meanwhile Agent B read the same file, made different changes, and overwrites what Agent A just did.

Neither agent knows the other exists. There is no locking mechanism. There is no coordination protocol. The result is broken code and wasted tokens.

What Genuinely Isolated Means

Genuine isolation means each agent operates in its own scope:

  • Separate files - no two agents touch the same file
  • Separate directories - ideally each agent works in a distinct folder
  • Separate concerns - one agent handles the API layer, another handles the UI, another writes tests
  • No shared state - no common config files, no shared databases during the session

The easiest pattern is feature-based isolation. Agent 1 builds the settings page. Agent 2 builds the onboarding flow. Agent 3 writes integration tests for a completely different module. They never intersect.

Practical Setup

Before launching parallel agents, spend five minutes planning the boundaries. List exactly which files each agent will touch. If there is any overlap - even a shared utility file - restructure the tasks until the overlap is gone.

Git worktrees help here. Each agent gets its own worktree with its own branch. They can modify the same codebase without stepping on each other, and you merge the branches sequentially when they finish.

The Payoff

Five isolated agents running for 30 minutes can accomplish what would take a single agent 2-3 hours. The speedup is real - but only when isolation is absolute. One shared file can turn a 5x speedup into a debugging nightmare.


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Fazm is an open source macOS AI agent. Open source on GitHub.

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