# vtcode Development Roadmap

This document outlines planned enhancements and features for the vtcode coding agent, inspired by Anthropic's breakthrough engineering approach that achieved 49% on SWE-bench Verified.

## **Recently Completed - Major Breakthroughs**

### **Anthropic-Inspired Architecture Implementation**

-   **Decision Transparency System** - Complete audit trail of all agent decisions with reasoning
-   **Error Recovery Manager** - Intelligent error handling with full context preservation
-   **Conversation Summarizer** - Automatic compression for long-running sessions
-   **Confidence Scoring** - Quality assessment for all agent actions
-   **Enhanced Tool Design** - Error-proofed tools with comprehensive documentation

### **Architecture Achievements**

-   **Model-Driven Control** - Maximum autonomy given to language models
-   **Minimal Scaffolding** - Simple, robust architecture that lets models excel
-   **Error-Proofing** - Anticipate and prevent common model misunderstandings
-   **Thorough Reasoning** - Encourage deep thinking for complex problems

## **High Priority - SWE-bench Performance Optimization**

### 1. Optimized Code Understanding

-   **COMPLETED**: Replaced heavy tree-sitter language grammars with LLM-native semantic analysis.
-   **COMPLETED**: Retained tree-sitter-bash for critical shell command safety parsing.
-   **COMPLETED**: Reduced binary size by ~7MB and simplified dependency graph.
-   **COMPLETED**: Optimized memory usage by removing language-specific AST caches.

### 2. LLM-Native Code Intelligence

-   Leverage high-context LLMs for deep code understanding without local AST overhead.
-   Implement symbol extraction and cross-reference analysis via LLM tool calls.
-   Enable intelligent code completion suggestions based on project context.
-   Implement dependency analysis and import management

### 3. Multi-language Support

-   Extend beyond Rust to support other languages (Python, JavaScript, Go)
-   Add language detection and appropriate parser selection
-   Implement language-specific tool behaviors
-   Support polyglot project analysis
-   Create language-specific workflow patterns

## Medium Priority

### 4. Research-preview Context Management

-   **Conversation Summarization** - Implemented automatic compression for long sessions
-   **Context Preservation** - Full context maintained during error recovery
-   **Research-preview Compression Algorithms** - More sophisticated summarization techniques
-   **Selective Context Retention** - Intelligent pruning based on relevance
-   **Context Prioritization** - Focus on most important information
-   **Multi-session Context** - Maintain context across multiple sessions

### 5. SWE-bench Evaluation & Benchmarking

-   **SWE-bench Integration** - Create evaluation framework for measuring performance
-   **Benchmark Runner** - Automated testing against SWE-bench Verified dataset
-   **Performance Metrics** - Comprehensive scoring and analysis tools
-   **Comparative Analysis** - Compare performance across different models and configurations
-   **Optimization Insights** - Data-driven improvements based on benchmark results

### 6. Performance Optimizations

-   **Token Usage Optimization** - Intelligent prompting reduces API costs
-   **Decision Confidence Scoring** - Quality assessment for all actions
-   **Research-preview Caching** - Implement intelligent caching for frequently accessed files
-   **Incremental Analysis** - Build upon previous analysis rather than starting over
-   **Tool Execution Optimization** - Streamline tool calls and reduce latency
-   **Memory Management** - Optimize memory usage for large codebases

### 7. Research-preview Tool Suite

-   **Enhanced Tool Design** - Error-proofed tools with comprehensive documentation
-   **Code Search & Indexing** - Full-text search across entire codebases
-   **Project-wide Refactoring** - Intelligent refactoring across multiple files
-   **Testing & Debugging Assistants** - Automated test generation and debugging support
-   **Documentation Generation** - Automatic documentation from code analysis
-   **Code Review & Analysis** - Comprehensive code quality assessment

### 8. Workflow Templates & Automation

-   **Project Creation Workflows** - Complete project scaffolding with best practices
-   **Predefined Task Templates** - Common development workflows
-   **Best Practice Enforcement** - Automatic adherence to coding standards
-   **Domain-Specific Patterns** - Specialized workflows for different project types
-   **Custom Workflow Builder** - User-defined automation patterns

## Low Priority

### 9. Integration Capabilities

-   **API Foundations** - Core integration capabilities established
-   **REST API Endpoints** - External integration interfaces
-   **Webhook Support** - CI/CD and external service integration
-   **IDE Plugin Interfaces** - Editor and IDE integration
-   **External Tool Integration** - Support for third-party tools

### 10. User Experience & Interface

-   **Conversation Persistence** - Context preservation across sessions
-   **Conversation Branching** - Explore multiple solution paths
-   **Rich Terminal UI** - Enhanced interactive experience
-   **Conversation Search** - Find and reference previous interactions
-   **Session Management** - Organize and manage multiple conversations

### 11. Monitoring & Analytics

-   **Usage Analytics** - Comprehensive tracking and metrics
-   **Performance Monitoring** - Real-time performance insights
-   **Conversation Quality Metrics** - Assess interaction effectiveness
-   **Research-preview Debugging Tools** - Enhanced troubleshooting capabilities
-   **Performance Profiling** - Detailed performance analysis

### 12. Security & Safety

-   **Sandboxing Foundations** - Secure execution environment
-   **Security Scanning** - Automated vulnerability detection
-   **Audit Logging** - Complete operation tracking
-   **Access Control** - Fine-grained permission management
-   **Privacy Protection** - Data handling and privacy safeguards

### 13. Research & Innovation

-   **Research-preview Context Management** - Sophisticated conversation handling
-   **Novel Tool Design** - Innovative interface patterns
-   **LLM Architecture Experiments** - Comparative model evaluation
-   **Human-Agent Collaboration** - Enhanced collaboration patterns

## Implementation Notes

### **SWE-bench Optimization Strategy**

Following Anthropic's breakthrough approach for maximum performance:

#### Phase 1: Foundation ( Completed)

-   **Model-Driven Architecture** - Give maximum control to language models
-   **Minimal Scaffolding** - Simple, robust design that lets models excel
-   **Error-Proofed Tools** - Comprehensive documentation and validation
-   **Thorough Reasoning** - Encourage deep thinking for complex problems

#### Phase 2: Code Understanding & Safety **COMPLETED**

-   **Optimized Code Understanding** - Replaced heavy grammars with LLM-native semantic analysis
-   **Bash Safety Parsing** - Tree-sitter-bash for critical shell command validation
-   **Multi-language Support** - Universal coverage through LLM-native understanding
-   **Research-preview Code Analysis** - Context-aware analysis with quality assessment
-   **Intelligent Refactoring** - Safe code transformation with AI assistance
-   **SWE-bench Foundation** - Semantic code understanding for benchmark optimization

#### Phase 3: Optimization & Scale

-   **Benchmark Automation** - Continuous performance evaluation
-   **Model-Specific Tuning** - Optimize for different Gemini models
-   **Workflow Patterns** - Domain-specific automation
-   **Performance Profiling** - Identify and eliminate bottlenecks

### **Tool Design Principles**

Inspired by Anthropic's engineering excellence:

-   **Comprehensive Documentation** - Extensive tool descriptions with examples
-   **Error Anticipation** - Design for common model misunderstandings
-   **Clear Interfaces** - Well-defined parameters and behaviors
-   **Extensive Testing** - Validate tools across diverse scenarios
-   **Debugging Support** - Clear error messages and recovery guidance

### **Quality & Reliability Standards**

-   **Confidence Scoring** - Quality assessment for all agent actions
-   **Pattern Detection** - Automatic identification of recurring issues
-   **Error Recovery** - Intelligent handling with context preservation
-   **Transparency Tracking** - Complete audit trail of decisions
-   **Performance Monitoring** - Real-time metrics and optimization

## Contributing

### **High-Impact Areas**

**Immediate Priority:**

1. **LLM-Native Code Understanding** - Lightweight, secure, and semantic code analysis
2. **Bash Safety Parsing** - Tree-sitter-bash for critical shell command validation
3. **SWE-bench Evaluation** - Create performance measurement framework

**Key Guidelines:**

1. **Anthropic-Inspired Design** - Follow breakthrough engineering principles
2. **Error-Proofing** - Anticipate and prevent model misunderstandings
3. **Comprehensive Testing** - Validate across diverse scenarios
4. **Performance Focus** - Optimize for SWE-bench style evaluation
5. **Transparency First** - Maintain complete audit trails

### **Development Standards**

**Code Quality:**

-   Follow Rust idioms and best practices
-   Add comprehensive documentation
-   Include unit tests for all new features
-   Maintain error-proofed tool design
-   Consider performance implications

**Architecture:**

-   Preserve model-driven control philosophy
-   Maintain minimal scaffolding approach
-   Extend transparency and decision tracking
-   Follow established patterns for context management
-   Ensure backward compatibility

## **Success Metrics**

### SWE-bench Performance Targets

-   **Primary Goal**: Achieve competitive performance on SWE-bench Verified
-   **Reliability**: Maintain 99%+ tool execution success rate
-   **Context Efficiency**: Handle long conversations without losing important information
-   **Error Recovery**: Successfully recover from 95%+ of error conditions

### Quality Standards

-   **Code Coverage**: Comprehensive test coverage for all features
-   **Documentation**: Complete documentation for all APIs and features
-   **Performance**: Response times under 2 seconds for typical operations
-   **User Experience**: Intuitive and transparent interaction patterns

### Innovation Metrics

-   **Tool Design Excellence**: Error-proofed, comprehensive tool specifications
-   **Model Empowerment**: Maximum autonomy given to language models
-   **Transparency**: Complete audit trail of all agent decisions
-   **Context Management**: Intelligent handling of conversation limits
