Agent Coordination
Strategies for coordinating multiple agents effectively
Overview
Strategies for coordinating multiple agents effectively
Learn how to effectively coordinate multiple AI agents working in parallel.
Coordination Strategies
Task Assignment Strategies
1. By Feature Boundaries
Assign complete features to agents:
{
"agent-1": ["User Authentication System"],
"agent-2": ["Blog Comment System"],
"agent-3": ["Analytics Dashboard"]
}
Pros: Clear ownership, minimal conflicts Cons: Uneven workload
2. By Component Layer
Divide by architectural layer:
{
"agent-1": ["Frontend Components"],
"agent-2": ["API Routes"],
"agent-3": ["Database Schema"]
}
Pros: Specialized work Cons: Requires coordination for integration
3. By Priority
Assign by urgency:
{
"agent-1": ["Critical Bug Fixes"],
"agent-2": ["High Priority Features"],
"agent-3": ["Nice-to-Have Enhancements"]
}
Pros: Focuses on important work Cons: May cause conflicts if priorities overlap
Coordination Patterns
Pattern 1: Independent Parallel
Agents work on completely separate features.
Use when: Features are completely independent
Pattern 2: Sequential Handoff
One agent completes work before next begins.
Use when: Work has dependencies
Pattern 3: Parallel with Sync Points
Agents sync periodically.
Use when: Features need periodic integration
Communication Protocols
Status Updates
The coordination layer maintains real-time status tracking:
Status Information
- Current work phase (not started, in progress, review, completed)
- Progress indicators and completion percentage
- Active tasks and priorities
- Notes and context about current work state
Dependency Declaration
Dependencies are explicitly tracked to coordinate work:
Dependency Types
- Depends On: Work that must complete before this task can proceed
- Blocks: Work that is waiting for this task to complete
- Related: Work that shares common interfaces or contracts
This enables intelligent scheduling and prevents agents from being blocked unnecessarily.
Conflict Prevention
Strategies to prevent conflicts:
- File ownership: Assign specific files to agents
- Module boundaries: Work in different packages
- Regular rebasing: Sync with develop frequently
- Communication: Discuss overlapping work
Coordination Tools
Configuration Management
The system maintains structured configuration for coordination:
Agent Assignment Configuration tracks:
- Agent identity and specialization
- Current task assignments
- Work status and progress
- Dependencies and blockers
- Branch and workspace information
Coordination Settings define:
- Synchronization frequency
- Conflict resolution strategies
- Integration order and priorities
- Communication protocols
State Management
Workspace State Tracking monitors:
- Last synchronization timestamps
- Commit relationships with main branch
- Uncommitted changes detection
- Rebase and integration status
Health Monitoring provides:
- Real-time agent status overview
- Workspace synchronization status
- Conflict detection and alerts
- Integration readiness indicators
Handling Conflicts
When Conflicts Occur
Detection
The system automatically detects potential conflicts during synchronization operations, analyzing file changes and merge scenarios.
Notification
Stakeholders are immediately alerted with details about the conflict, including affected files and the agents involved.
Analysis
The system provides analysis of:
- Overlapping file changes
- Nature and extent of conflicts
- Potential resolution strategies
- Impact assessment
Resolution
Conflicts are resolved through established strategies:
- Coordinated manual resolution when needed
- Priority-based change selection
- Integrated merge with adjustments
- Stakeholder decision support
Verification
Comprehensive validation ensures the resolution is correct through automated testing and quality checks.
Conflict Prevention Strategies
- Proactive sync: Rebase on develop daily
- File locking: Declare file ownership
- Communication: Discuss potential overlaps
- Small PRs: Merge frequently, reduce conflict window
- Module isolation: Work in separate packages
Monitoring & Metrics
The system tracks coordination effectiveness through key metrics:
| Metric | Target | Meaning |
|---|---|---|
| Agent utilization | >80% | Time spent on active work |
| Conflict rate | <5% | PRs with merge conflicts |
| Average PR size | <300 lines | Smaller = easier to review |
| Time to merge | <24 hours | Speed of integration |
| Rebase frequency | Daily | How often synced with develop |
These metrics provide insight into system efficiency and help identify opportunities for optimization.
Best Practices
Note:
Coordination Best Practices:
- Daily standups: Review agent status
- Clear assignments: No ambiguity in tasks
- Dependency tracking: Document dependencies
- Regular syncs: Rebase on develop daily
- Small iterations: Merge work frequently
- Communication: Over-communicate potential conflicts
Advanced Patterns
Dynamic Task Assignment
The system can automatically assign tasks based on:
- Agent specialization and skills
- Current workload and capacity
- Task complexity and priority
- Historical performance data
Load Balancing
Work distribution is optimized through:
- Real-time capacity monitoring
- Even distribution across available agents
- Skill-appropriate task matching
- Dynamic rebalancing as needed
Priority Queue
High-priority work is handled through:
- Urgent task identification
- Intelligent agent selection
- Capacity preemption when needed
- Expedited workflow processing
Next Steps
- Worktree Management - Manage Git worktrees
- Workflow Automation - Automate workflows
- Scripts Reference - Available scripts