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Features
Multi-Agent

Multi-Agent Teams

Dispersl's core strength lies in its ability to coordinate multiple AI agents that work together to accomplish complex development tasks. Each agent specializes in different aspects of software development, creating a comprehensive AI development team.

How Multi-Agent Teams Work

Agent Specialization

Each agent in Dispersl is optimized for specific development tasks:

  • Coding Agent: Generates and builds code with agentic flow
  • Testing Agent: Creates comprehensive test suites and validates functionality
  • Git Agent: Manages version control workflows and repository operations
  • Documentation Agent: Generates end-to-end documentation and guides
  • Chat Agent: Provides insights about codebase and task progress

Coordination and Communication

Agents communicate through a shared context system that enables:

  • Task Distribution: Complex tasks are automatically broken down and assigned to appropriate agents
  • Context Sharing: All agents have access to shared memory and project knowledge
  • Dependency Management: Agents understand task dependencies and execute in proper order
  • Real-time Updates: Agents provide status updates and coordinate handoffs

Agent Workflow Example

Here's how multiple agents coordinate to build a complete feature:

$ dispersl plan "Build user authentication system"
 
# Plan Agent breaks down the task
Plan Agent > Analyzing requirements...
Plan Agent > Creating task breakdown:
  1. Code Agent: Generate authentication API endpoints
  2. Code Agent: Implement JWT token handling
  3. Test Agent: Create unit tests for auth functions
  4. Test Agent: Generate integration tests
  5. Git Agent: Create feature branch and commit changes
  6. Documentation Agent: Generate API documentation
 
# Agents execute in coordinated sequence
Coding Agent > Model: Anthropic Sonnet
Coding Agent > Building authentication endpoints...
Coding Agent > Implementing JWT middleware...
 
Testing Agent > Model: OpenAI GPT-4
Testing Agent > Generating unit tests...
Testing Agent > Creating integration test suite...
 
Git Agent > Model: DeepSeek R1
Git Agent > Creating feature branch 'auth-system'...
Git Agent > Committing changes...
 
Documentation Agent > Model: Google Gemini
Documentation Agent > Generating API documentation...
Documentation Agent > Creating setup guide...

Agent Capabilities

Coding Agent

Specializations:

  • API development and backend services
  • Frontend component creation
  • Database schema design
  • Business logic implementation
  • Performance optimization

Tools Available:

  • File system operations (read, write, edit)
  • Command execution
  • Code analysis and refactoring
  • Dependency management

Testing Agent

Specializations:

  • Unit test generation
  • Integration test suites
  • End-to-end testing
  • Test data generation
  • Coverage analysis

Tools Available:

  • Test framework detection
  • Test file generation
  • Test execution and reporting
  • Mock data creation

Git Agent

Specializations:

  • Branch management
  • Commit workflows
  • Merge conflict resolution
  • Release management
  • CI/CD pipeline integration

Tools Available:

  • Git command execution
  • Repository analysis
  • Branch operations
  • Infrastructure file management

Documentation Agent

Specializations:

  • API documentation generation
  • README creation
  • Code commenting
  • User guide writing
  • Changelog maintenance

Tools Available:

  • Codebase analysis
  • Documentation generation
  • Template processing
  • Content formatting

Chat Agent

Specializations:

  • Codebase insights and analysis
  • Task progress reporting
  • Development guidance
  • Knowledge base queries
  • Interactive assistance

Tools Available:

  • Code analysis
  • Context retrieval
  • Knowledge base access
  • Real-time communication

Model Flexibility

Each agent can use different AI models based on the task requirements:

# Configure different models for different agents
$ dispersl config set coding-agent-model "anthropic/claude-3-sonnet"
$ dispersl config set testing-agent-model "openai/gpt-4"
$ dispersl config set git-agent-model "deepseek/deepseek-r1"
$ dispersl config set docs-agent-model "google/gemini-pro"

Synchronized Memory

All agents share synchronized memory that includes:

  • Project Context: Understanding of the current project structure and goals
  • Task History: Complete history of all completed and ongoing tasks
  • Code Knowledge: Deep understanding of the existing codebase
  • User Preferences: Coding standards, patterns, and preferences
  • Integration State: Status of external tools and services

Advanced Coordination Features

Dependency Resolution

Agents automatically understand task dependencies:

Error Recovery

When an agent encounters an error, the system provides automatic recovery:

  1. Error Detection: Agent reports failure with detailed context
  2. Impact Analysis: System determines which other agents are affected
  3. Recovery Strategy: Alternative approaches are automatically attempted
  4. Coordination Update: Other agents are notified of changes

Load Balancing

Tasks are distributed based on:

  • Agent availability and current workload
  • Task complexity and estimated duration
  • Agent specialization and success rates
  • Resource requirements and constraints

Best Practices

Task Design

  1. Clear Requirements: Provide detailed task descriptions for better agent coordination
  2. Logical Breakdown: Structure tasks in a way that allows natural agent specialization
  3. Context Sharing: Include relevant project context for all agents

Agent Configuration

  1. Model Selection: Choose appropriate models for each agent type
  2. Resource Allocation: Configure memory and processing limits
  3. Integration Setup: Connect agents to necessary external tools

Monitoring and Optimization

  1. Performance Tracking: Monitor agent performance and coordination efficiency
  2. Bottleneck Identification: Identify and resolve coordination bottlenecks
  3. Success Rate Analysis: Track and improve agent success rates

Integration with External Tools

Multi-agent teams can integrate with your existing development stack:

  • Version Control: GitHub, GitLab, Bitbucket
  • CI/CD: Jenkins, GitHub Actions, GitLab CI
  • Project Management: Jira, Linear, Asana
  • Communication: Slack, Discord, Microsoft Teams
  • Cloud Platforms: AWS, Azure, GCP
  • Databases: PostgreSQL, MongoDB, Redis

Getting Started

  1. Define Your Task: Describe what you want to build
  2. Let the Plan Agent Break It Down: Automatic task decomposition
  3. Monitor Progress: Watch agents coordinate and execute
  4. Review Results: Validate the completed work
  5. Iterate: Provide feedback for continuous improvement
# Start with a simple multi-agent task
$ dispersl plan "Create a REST API with authentication and tests"
 
# Monitor the coordination
$ dispersl status
 
# Get insights from the chat agent
$ dispersl chat "How is the authentication implementation progressing?"

Multi-agent coordination in Dispersl transforms complex development tasks into manageable, automated workflows that leverage the strengths of specialized AI agents working together as a cohesive team.

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