Agent Mode

Autonomous AI coding with minimal supervision

Overview

Agent Mode transforms Cubent Coder into an autonomous coding assistant that can work independently on complex tasks with minimal supervision. Instead of back-and-forth conversations, you give the agent a high-level goal, and it breaks down the task, creates a plan, and executes it step by step.

How Agent Mode Works

1. Task Planning

When you give the agent a task, it:

• Analyzes the requirements
• Breaks down the task into smaller steps
• Creates an execution plan
• Identifies potential challenges

2. Autonomous Execution

The agent then:

• Executes each step of the plan
• Makes decisions based on context
• Handles unexpected issues
• Adapts the plan as needed

3. Progress Monitoring

Throughout execution, you can:

• Monitor progress in real-time
• Intervene when necessary
• Approve or reject specific actions
• Provide additional guidance

Getting Started

Activating Agent Mode

1. Open the Cubent Coder panel
2. Click the “Agent Mode” button
3. Describe your high-level task or goal
4. Review the generated plan
5. Approve execution or request modifications

Example Tasks

Feature Development:

Create a user authentication system with login, signup, and password reset functionality using React and Node.js

Bug Fixing:

Find and fix all TypeScript errors in the project, ensuring type safety throughout the codebase

Code Refactoring:

Refactor the legacy jQuery code to modern React components while maintaining all existing functionality

Testing:

Add comprehensive unit tests for all API endpoints with at least 90% code coverage

Agent Capabilities

Code Operations

• File Creation: Generate new files and directories
• Code Modification: Update existing code across multiple files
• Dependency Management: Install and configure packages
• Configuration: Set up build tools, linters, and formatters

Development Tasks

• Feature Implementation: Build complete features from scratch
• Bug Resolution: Identify and fix issues systematically
• Code Review: Analyze code quality and suggest improvements
• Documentation: Generate comprehensive documentation

Project Management

• Architecture Planning: Design system architecture
• Migration Tasks: Upgrade frameworks and dependencies
• Performance Optimization: Identify and resolve bottlenecks
• Security Audits: Find and fix security vulnerabilities

Configuration Options

Approval Settings

Configure what actions require your approval:

• Auto-approve safe actions: File reads, code analysis
• Require approval for: File modifications, package installations
• Always ask for: Destructive operations, external API calls

Execution Limits

Set boundaries for agent behavior:

• Maximum execution time: Prevent runaway tasks
• File modification limits: Restrict scope of changes
• API call limits: Control external service usage
• Resource usage: Monitor CPU and memory consumption

Custom Instructions

Provide project-specific guidelines:

Always use TypeScript for new files
Follow the existing code style and patterns
Add JSDoc comments for all public functions
Write tests for any new functionality

Best Practices

Writing Effective Agent Tasks

1. Be Clear and Specific

   ❌ "Make the app better"
   ✅ "Improve the app's performance by optimizing database queries and implementing caching"
   

2. Provide Context

   ✅ "Add user authentication to the existing Express.js API, using JWT tokens and bcrypt for password hashing"
   

3. Set Boundaries

   ✅ "Refactor the user service module without changing the public API interface"
   

Monitoring Agent Progress

• Review the plan before approving execution
• Check intermediate results during long-running tasks
• Intervene early if the agent goes off-track
• Provide feedback to improve future performance

Safety Considerations

• Start with small tasks to build confidence
• Use version control to track all changes
• Review all modifications before committing
• Test thoroughly after agent completion

Advanced Features

Multi-Step Workflows

Chain multiple agent tasks together:

1. Analysis Phase: “Analyze the codebase and identify performance bottlenecks”
2. Planning Phase: “Create a detailed optimization plan based on the analysis”
3. Implementation Phase: “Implement the optimization plan step by step”

Collaborative Mode

Work alongside the agent:

• Pair programming: Agent writes code while you review
• Task delegation: Assign specific subtasks to the agent
• Knowledge sharing: Agent learns from your feedback

Integration with Tools

Agent Mode integrates with:

• Version Control: Automatic commit messages and branch management
• Testing Frameworks: Run tests after code changes
• CI/CD Pipelines: Trigger builds and deployments
• Code Quality Tools: Ensure standards compliance

Troubleshooting

Common Issues

Agent gets stuck:

• Provide more specific instructions
• Break down the task into smaller parts
• Check for conflicting requirements

Unexpected results:

• Review the initial task description
• Check approval settings
• Provide additional context or constraints

Performance issues:

• Reduce task complexity
• Set execution time limits
• Monitor resource usage

Getting Help

If you encounter issues with Agent Mode:

1. Join our Discord community
2. Report bugs on GitHub
3. Check our community resources for help

Next Steps

Custom Modes

Create specialized AI personas for specific workflows

MCP Integration

Extend capabilities with Model Context Protocol