Features
Run multiple AI coding agents in parallel within one project
Sandboxed execution with command and file change review
Subagent delegation for breaking large refactors into subtasks
Each agent operates with its own context, prompt, and git state
Real-time progress tracking while agents work in the background
Git integration: review, test, compare, and ship desired work
Terminal-based workflow without leaving the development environment
Automatic code review and pull request generation
Auditable session logs and visible agent activity
Cross-platform support (macOS, Windows, Linux)
Complementary to existing AI tools (Cursor, Cline, Kilo, Codex, Claude, ChatGPT)
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
