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Trust CLI Roadmap

Vision

Privacy-first, local AI assistant for developers who value control and security, with enterprise-grade capabilities and seamless multi-model tool execution.

Phase 1: Foundation Stabilization (Weeks 1-4)

Goal: Reliable core functionality across all supported models

1.1 Core Functionality Fixes

  • Function calling reliability - Complete JSON generation across all models
  • Streaming performance - Optimize real-time response generation
  • Context management - Robust handling of long conversations
  • Error recovery - Graceful fallbacks when models fail

1.2 Model Management Improvements

  • Enhanced Model Selection UX - Interactive model picker and switching
  • Provider Auto-Detection - Smart backend discovery and configuration
  • Model Recommendation Engine - Task-based model suggestions
  • Unified Model Interface - Abstract backend differences

1.3 Multi-Model Tool Execution

  • Universal tool calling protocol - Standardized function calling across all models
  • Tool execution engine - Backend-agnostic tool handling
  • Function call validation - Robust parameter checking and error handling

Phase 2: Developer Experience Enhancement (Weeks 5-8)

Goal: Best-in-class developer workflow integration

2.1 IDE & Workflow Integration

  • VSCode extension - Native editor integration
  • Git workflow integration - Commit messages, PR reviews, diff analysis
  • Project-aware assistance - Codebase structure understanding
  • Multi-language support - Language-specific optimizations

2.2 Configuration Profiles

  • Layered configuration system - Global, project, and runtime configs
  • User profiles - Save model preferences for different tasks
  • Team configurations - Shared settings and tool definitions

Phase 3: Local AI Optimization (Weeks 9-12)

Goal: Maximum performance from local hardware

3.1 Performance Optimization

  • Hardware acceleration - GPU support, Apple Silicon optimization
  • Model quantization pipeline - Optimize models for local hardware
  • Resource management - Smart memory and CPU usage optimization
  • Model caching - Efficient storage and loading strategies

3.2 Advanced Model Management

  • Fine-tuning workflows - Train models on specific codebases
  • Model capability tracking - Rich metadata and feature detection
  • Dynamic model selection - Automatic model switching based on task

Phase 4: Plugin Architecture & Extensibility (Weeks 13-16)

Goal: Extensible ecosystem for specialized tools

4.1 Plugin System Foundation

  • Plugin architecture design - Secure, sandboxed plugin execution
  • Tool registry system - Discovery and management of available tools
  • Plugin SDK - Developer tools for creating custom plugins
  • Built-in tool marketplace - Curated collection of useful plugins

4.2 Specialized Tool Ecosystem

  • Code analysis tools - Static analysis, security scanning, performance profiling
  • Documentation tools - API doc generation, README creation
  • Testing tools - Unit test generation, test data creation
  • DevOps tools - Docker, CI/CD, infrastructure management

Phase 5: Enterprise Features (Weeks 17-20)

Goal: Production-ready for teams and organizations

5.1 Team Collaboration

  • Shared configurations - Team-wide model and tool settings
  • Collaborative sessions - Multiple developers working with same AI context
  • Knowledge sharing - Team-specific model fine-tuning and tool libraries

5.2 Security & Compliance

  • Audit logs - Complete interaction tracking
  • Access controls - Role-based permissions and restrictions
  • Privacy controls - Data retention policies, local-only modes
  • Compliance frameworks - SOC2, GDPR, HIPAA support

Phase 6: Advanced Features (Weeks 21-24)

Goal: Cutting-edge local AI capabilities

6.1 Unique Local-First Features

  • Offline documentation - Local knowledge bases and search
  • Custom model training - Easy fine-tuning on project data
  • Multi-agent workflows - Coordinate multiple AI models for complex tasks
  • Performance monitoring - Usage analytics and optimization insights

6.2 Deployment & Distribution

  • Docker containers - Easy deployment and distribution
  • Cloud deployment - Hybrid local/cloud architectures
  • Package managers - Homebrew, apt, yum distribution
  • Auto-updates - Seamless version management

Success Metrics

Phase 1-2 (Foundation)

  • Function calling success rate > 95% across all models
  • Model switching time < 5 seconds
  • Zero crashes during normal operation

Phase 3-4 (Optimization)

  • 50% reduction in model loading time
  • Plugin ecosystem with 10+ high-quality tools
  • Support for 5+ major IDEs

Phase 5-6 (Enterprise)

  • 10+ enterprise customers using Trust CLI
  • SOC2 Type II compliance
  • 99.9% uptime for team deployments

Getting Started

Current Priority: Phase 1.3 - Multi-Model Tool Execution

  • Investigate Forge CLI's approach to handling 300+ models with tool execution
  • Design universal tool calling protocol
  • Implement backend-agnostic function calling system

This roadmap is a living document and will be updated based on user feedback, technical discoveries, and changing priorities.