- Specs capture user intent and requirements
- Issues track agent tasks and implementation work
- Relationships model dependencies between work items
- Feedback enables agents to improve specs as they implement

Why sudocode?
Learn Why sudocode Matters
Understand the problems sudocode solves and how it transforms AI-assisted development
Who is sudocode for?
Perfect For
AI-Assisted Development Teams
Teams using Claude Code, Cursor, Copilot, or custom agents for daily development work
Long-Horizon Projects
Projects spanning weeks/months where context needs to persist across many sessions
Complex Requirements
Features with many interdependent tasks, dependencies, and design decisions to track
Multi-Agent Workflows
Running multiple AI agents concurrently (e.g., one on backend, one on frontend)
Spec-Driven Development
Teams that value written requirements and want iterative refinement from implementation
Open Source Projects
Need context that lives in the repo, accessible to all contributors without external accounts
Maybe Not For
- Quick prototypes: Single-session exploratory coding without need for persistence
- Solo scripts: One-off automation where there’s no ongoing maintenance
- Non-AI workflows: Teams not using AI coding assistants (though sudocode still works as a lightweight issue tracker)
Quick Start
Get up and running in minutes:Quick Start Guide
Create your first spec and issue in under 5 minutes
Learn the Core Concepts
Understand how sudocode organizes context:Specs
Capture user requirements and design decisions
Issues
Track agent tasks and implementation work
Relationships
Model dependencies and connections between work
Feedback
Enable bidirectional learning between agents and specs
Integration Guides
Connect sudocode to your AI agents and workflows:Quick Start
Set up sudocode and create your first issue in minutes
Workflows
Learn spec-driven development and best practices
MCP Integration
Use sudocode with Claude Code and other MCP-compatible agents
Key Features
- Dual representation: Human-readable markdown + machine-queryable JSONL
- Graph-based planning: Topological ordering finds ready work automatically
- Bidirectional linking: Obsidian-style
[[SPEC-001]]references with backlinks - Smart anchoring: Feedback tracks specific lines and relocates intelligently
- Distributed sync: Git handles distribution; AI handles merge conflicts
- Multiple interfaces: CLI, MCP server, REST API, and web UI
Community & Support
Philosophy: Context should be treated like code—version-controlled, collaboratively edited, and evolved alongside your implementation. sudocode makes this possible for AI-assisted development.

