Running agents in parallel, in practice
Run fleets of coding agents without collisions. Each guide gives the mechanics and the exact commands.
$ npx @retasc/cli@latest bindStart where your stack is
ten guides, 2 to 8 minutes eachTurn GitHub Issues into a work queue your agents drain
Get member-approved intake with Retasc, a work queue for AI coding agents. Compare Copilot, Agent HQ and the GitHub MCP server.
Run multiple Claude Code agents in parallel
You get Claude Code worktrees and parallel features, per-session claims and checkpoint handoffs when a session stops.
Claude Code subagents: dispatching waves with next_batch
Run Claude Code and Codex subagents in parallel with a next_batch wave that gives each its own issue.
Claude Code agent teams share tasks until the session ends
How agent teams coordinate until the session ends, and how teammates pull their own issues from a shared queue.
A Claude Code handoff carries work beyond the saved local session
Resume a Claude Code or Codex session, or pass an issue’s last checkpoint to the next agent that claims it.
Cursor background agents on a shared backlog
Share a work queue for AI coding agents across Cloud Agents and Claude Code, with VM and MCP setup.
Cursor CLI vs Claude Code: MCP, CI and worktrees
Cursor CLI and Claude Code support CI, MCP and worktrees. Retasc setup wires Claude Code and Cursor.
What is an agent swarm, and how do you keep one from colliding?
What “agent swarm” means in Kimi, OpenAI, Claude Code, Ruflo and desplega, measured against what a shared backlog needs.
Linear vs Jira vs an agent-first tracker
Compare Linear and Jira’s 2026 agent handoffs and MCP servers with a work queue for AI coding agents.
Vibe Kanban vs Retasc
Vibe Kanban runs agents in workspaces. Your agents pull unblocked work from Retasc’s queue without double claims.
$ npx @retasc/cli@latest bind