Run 5 AI Agents at Once: Parallel Coding with Orca

Discover how Orca runs multiple AI agents simultaneously, creates varied code versions, and merges the strongest parts instantly for faster development.

What if you could fire up five AI coders at the same time and pick the best code from each?

⚡ TL;DR: Orca runs multiple AI agents in parallel, creates separate code versions, and lets you merge the strongest parts instantly.

The Simple Version

Think of a team of AI assistants each working on its own copy of your project. They don’t clash because each gets its own isolated folder.

How It Actually Works

Isolated Worktrees

🎯 Think of it this way: Like giving each painter a separate canvas so their brushes never mix.

Git worktrees let Orca spin up independent directories for each agent. Claude Code and Codex run inside these sandboxes, writing code without overwriting one another.

Parallel Generation

🎯 Think of it this way: It's like five chefs cooking the same dish from different recipes at once.

Five agents generate distinct versions simultaneously, giving you a palette of options to choose from.

Technical Deep Dive

Each agent starts with its own git worktree cloned from the main repo. The system launches separate processes for Claude Code and Codex, assigning unique branch names.

When an agent finishes, Orca collects the pull request style patches and stores them in a staging area.

Developers review the live emulators side by side, copy preferred snippets, and apply them to a master branch.

Why This Matters

Running multiple agents cuts iteration time dramatically. Instead of waiting for one model to stumble, you get diverse solutions instantly.

Teams can experiment with different architectural choices in parallel, accelerating innovation.

The approach also reduces the cognitive load of prompt engineering, as you no longer need to fine‑tune a single model repeatedly.

Key Takeaways

Five AI agents work in isolated git folders.
Each produces a separate code version.
Live emulators let you compare results side by side.
Best snippets are merged into a final build.
Productivity jumps because you skip endless re‑prompts.
Experimentation becomes faster and less risky.
Orca works with existing tools like Claude Code and Codex.