Overview
What Agent Observer is, who it is for, and how to use it as a local control plane for AI coding workflows.
Overview
Agent Observer is a local-first control plane for AI-assisted development work.
It combines chat, terminal, file context, and operational telemetry so users can run agent workflows with tighter scope and better observability.
Who It Is For
- developers running AI workflows across local repositories
- operators managing recurring and long-running coding tasks
- teams that need clearer runtime visibility than plain terminal sessions
Core Product Surfaces
- Explorer: choose and verify workspace scope
- Search: fast local file discovery
- Chat: workspace-scoped agent interactions
- Terminal: command execution visibility
- Activity/Office/Tokens: runtime observability and status
- Settings: scheduler and todo-runner automation controls
Primary Jobs To Be Done
- Run one-off coding tasks with exact workspace context.
- Schedule recurring checks and maintenance prompts.
- Execute large todo backlogs to completion with progress tracking.
- Diagnose failures quickly from runtime state and error surfaces.
Product Principles
- Scope first: every run should be anchored to a known directory.
- Local first: workflows should work with local files and local tooling.
- Operational clarity: state should be visible without guesswork.
- Recoverability: long tasks should resume safely after interruption.
Choosing The Right Automation Mode
- Use Schedules for recurring, time-based prompts.
- Use Todo Runner for finite large checklists that must run until done.