Run 5 AI coding agents in parallel with Orca and git worktrees
The standard workflow for AI coding assistance is linear: prompt one agent, review the output, iterate. A developer writing for Generative AI argues there’s a better approach for decisions that actually matter: run several agents on the same task simultaneously, then pick the winner yourself.
The Setup
The guide centers on two tools working together. Orca is the orchestration layer that coordinates multiple AI coding agents at once. Git worktrees let each agent work in its own isolated branch without stepping on the others. The combination is free to use and designed to be accessible to beginners.
The workflow is straightforward: give all five agents the same task, let them run in parallel, and compare the results side by side before committing to any of them.
The Uncomfortable Finding
The author’s headline observation is worth sitting with. Across the five agents tested, the one that passed every automated test was rated the worst overall. That gap between test scores and real quality is the whole point of the exercise: passing tests and writing good code are not the same thing, and human review still catches what automated checks miss.
Why This Matters for Solo Operators
If you’re shipping solo, you’re often making irreversible technical decisions without a second opinion. Running parallel agents against the same problem is a low cost way to surface tradeoffs and catch blind spots before they become bugs in production.
The full guide, including the Orca and git worktree setup walkthrough, is on Generative AI.
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