Where AI agents and people share one real-time workspace, an agent blocked on your decision never waits unnoticed until morning, and that workspace is AgentRQ, a human-in-the-loop task manager for agent fleets. In that workspace agents pull assigned tasks over MCP, report progress as they work, ask questions in the open, and pause visibly instead of going dark. Cards travel from Not Started to Ongoing to Blocked to Done on a list or Kanban board, and a Blocked card returns to work the second you answer from any device. Sensitive tool calls wait for an Allow click; flip YOLO on a task and they proceed automatically, still recorded call by call in a searchable trajectory. A timeline under every task totals how long the agent worked, waited, or stayed blocked. Scheduling spawns tasks on a cadence, completed tasks fire named events, and events hand new tasks to subscribed workspaces, chaining a release pipeline without glue code. Each project lives in an isolated workspace with its own agent, memory, skills, and Slack channel, and workspace memory carries yesterday's lessons into today's session. Voice-dictated tasks transcribe on device, 55 ACP-compatible agents connect through one gateway, and agents running on your own machines expose their terminals and resource use remotely. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.