
Why Loom?
AI coding agents face several challenges when working on long-horizon tasks:| Challenge | Loom Solution |
|---|---|
| Context Loss | Intelligent memory management with importance-weighted compaction |
| Poor Prioritization | Smart scoring based on blocking impact, staleness, and failure history |
| Coordination Gaps | File-level locking and conflict detection for multi-agent work |
| No Learning | Retrospectives and pattern extraction for continuous improvement |
| Memory Pressure | Context compaction that preserves critical information |
Key Features
Smart Prioritization
Score tasks by downstream impact, staleness, and failure history:Lifecycle Hooks
Inject context, validate commands, and auto-create follow-ups at key orchestration points:pre-prompt- Inject context before prompt processingpre-tool-call- Validate tool calls, block dangerous commandspost-tool-call- Truncate large outputs, attach snippetspost-response- Auto-create follow-up beadson-error- Log failures, attempt recoveryon-claim- Run setup/linting on claimpre-close- Verify tests pass before closingon-block- Notify for reprioritization
Multi-Agent Coordination
When multiple agents work on the same codebase:- File-level locking prevents conflicts
- Automatic lock expiration
- Conflict detection and reporting
Learning System
Loom learns from each session:- Pattern extraction from successful strategies
- Global knowledge sharing across projects
- Failure history for better prioritization
Quick Start
Next Steps
Get Started
Install Loom and run your first orchestration
CLI Reference
Explore all available commands
Configuration
Customize Loom for your workflow
Architecture
Understand how Loom works under the hood