# Autonomous Agent An **autonomous agent** is an AI system capable of independently executing long-horizon tasks with minimal human intervention. It perceives its environment, plans a course of action, uses tools to execute that plan, and adapts based on results — all without requiring a human to direct each individual step. ## What Makes an Agent "Autonomous" Autonomy in AI agents exists on a spectrum: | Level | Description | Example | |-------|-------------|---------| | Assisted | Human approves every action | Agent suggests, human executes | | Semi-autonomous | Human approves key decisions | Agent works freely, pauses at checkpoints | | Fully autonomous | Agent acts end-to-end | Agent completes task, notifies when done | Most production agents today operate in the semi-autonomous range — capable of significant independent work but with [human-in-the-loop](human-in-the-loop) oversight at critical points. ## Autonomous Agents in Software Development [Claude Code](claude-code) is a prime example of an autonomous coding agent. Given a task like "fix all failing tests," it will: 1. Read the test output 2. Identify failing tests and their causes 3. Edit source files to fix the issues 4. Re-run tests to verify 5. Repeat until all tests pass This entire loop happens autonomously — no human needs to direct each file read or edit. ## The Role of AgentRQ Full autonomy without oversight is risky. AgentRQ connects autonomous agents to their human principals via [MCP](mcp), providing a real-time channel for [notifications](notification), [approvals](approval), and [bidirectional messaging](bidirectional-messaging). This allows agents to operate autonomously while humans retain meaningful control over consequential decisions. ## Related Terms - [Agent](agent) - [Agentic Workflow](agentic-workflow) - [Human-in-the-Loop](human-in-the-loop) - [Tool Use](tool-use) - [Operator](operator)