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The problem: When you run Continue alongside Claude Code, Codex, or other AI agents on a real project — they conflict on files, you manually copy-paste context between terminals, and there is no coordination layer.
ORCH is an open-source CLI runtime that orchestrates teams of AI coding agents:
Typed task queue — state machine: todo → in_progress → review → done, with automatic retries on stalls
Scope locking — prevents two agents from editing the same file simultaneously
Inter-agent messaging — agents share results programmatically (no human copy-paste)
Adapter system — Continue, Claude Code, Codex, Cursor all connect as named adapters
TUI dashboard — live view of all running agents, tasks, and logs
Goals system — high-level objectives auto-decomposed into agent subtasks
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Hey Continue community!
Sharing a tool I built that works alongside Continue for multi-agent projects: ORCH (https://github.com/oxgeneral/ORCH)
The problem: When you run Continue alongside Claude Code, Codex, or other AI agents on a real project — they conflict on files, you manually copy-paste context between terminals, and there is no coordination layer.
ORCH is an open-source CLI runtime that orchestrates teams of AI coding agents:
todo → in_progress → review → done, with automatic retries on stallsQuick start:
1,647 passing tests, TypeScript strict, zero-database (YAML/JSON files only), MIT license.
https://github.com/oxgeneral/ORCH
Happy to hear how Continue users are running multi-agent setups and whether ORCH could help!
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