aming-claw-vibe-queue-demo

An AI observer queues work by tracking mid-implementation requirements and collecting evidence in parallel with the agent, preserving context for review. This keeps user dialogue flowing while ensuring controlled progress during live demos.

An observer-led backlog workflow runs alongside an AI agent to track decisions, evidence, and constraints. It provides predefined backlog semantics and documented observer behavior, ensuring visibility and context preservation for ongoing sessions.

To set up the demo, boot the Vibe Queue environment and open the dashboard. It uses a configurable fixture and a two-window workflow to display backlog, timeline, and planner previews for interactive observer sessions.

Yes, the observer automatically collects evidence for mid-implementation requirements. It records decisions and constraints during the AI agent's execution, supporting learning, auditing, and replication of the demonstrated workflow.

No specific dependencies are required to run the observer queue demo. It operates within the Aming Claw environment using configurable fixtures and dashboard scripts, allowing you to start the workflow and backlog setup directly.

The observer keeps context alive to ensure visibility and controlled progress while the AI agent runs. This prevents loss of mid-implementation requirements and allows the user dialogue to flow continuously without interrupting the backlog tracking.