Parallel AI Agents Workflow for Multi-Stream Development
A workflow for managing multiple AI agents working on separate branches simultaneously, with each agent having its own repository copy and reporting progress through slash commands. This approach enables developers to manage multiple work streams without constant micromanagement.
Tools & Prerequisites
Required Tools
Step-by-Step Guide
Set Up Independent Repository Copies
Create separate repository copies for each agent to work independently. Each agent will operate on its own branch to prevent conflicts.
Pro Tip
Ensure each repository copy is properly initialized with the correct branch structure
Configure Shared Claude Rules
Establish common Claude rules that all agents will follow to ensure consistency across different work streams. These rules should define coding standards, architectural patterns, and communication protocols.
Pro Tip
Consider writing evals on your Claude rules to ensure they're effective
Implement Progress Reporting System
Set up a slash command system that allows agents to report progress by writing to a markdown file. This creates a centralized progress tracking mechanism.
Pro Tip
The progress doc helps agents and developers resume work and maintain focus
Assign Agent Roles and Tasks
Distribute work among agents based on their roles: one for researching, another for planning, another for implementing, and another for fixing bugs. Each agent works on their designated tasks independently.
Pro Tip
Focus on managing multiple work streams rather than keeping agents busy all the time
Run Regular Standup Sessions
Use Claude to run 'standup' sessions that help with context switching between different agents and their work streams. Review the progress markdown files during these sessions.
Pro Tip
This is especially helpful when managing a team and doing product/org work alongside development
Manage Concurrent Development Branches
Maintain two concurrent larger branches at a time while using parallel agents to multitrack small fixes and improvements. This balances major feature work with ongoing maintenance.
Pro Tip
Knowledge of your UI architecture helps keep agents on task and producing mergeable code
Review and Merge Agent Work
Regularly review the code produced by each agent and merge their branches when work is complete. Ensure code quality meets standards before integration.
Pro Tip
CLI tools lend themselves to composability better than IDEs for this type of workflow
This workflow demonstrates how to use parallel AI agents to manage multiple development work streams simultaneously. Each agent operates on its own branch with a dedicated repository copy, allowing for independent work on different features, bug fixes, or research tasks. The system uses shared Claude rules for consistency and a markdown-based progress reporting system via slash commands.
Key Benefits
- Manage multiple agent work streams without keeping them busy all the time
- Reduce friction from micromanaging AI agents
- Enable context switching between different development tasks
- Maintain focus across research, planning, implementation, and debugging activities
Architecture Overview
The workflow uses independent repository copies for each agent, preventing conflicts and allowing parallel work. Progress is tracked through markdown files generated by slash commands, and "standup" sessions help with context switching and coordination.
Use Cases
- One agent researching while another implements
- Parallel bug fixing and feature development
- Maintaining two concurrent larger branches while handling small fixes
- Managing development work while handling other responsibilities (team management, design, product work)
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