Background Agents Explained: Cursor, Codex & Beyond
A practical guide to background agents in AI coding: what they are, how Cursor and Codex use them, and when they matter for your workflow.
Editorial Team
The AI Coding Tools Directory editorial team researches and reviews AI-powered development tools to help developers find the best solutions for their workflows.
Background agents let AI coding tools work on tasks while you focus elsewhere. This guide explains how they work and which tools offer them.
Quick Answer
Background agents run coding tasks asynchronously—editing files, running tests, or exploring the codebase—without blocking your IDE. Cursor offers them on Pro+ and Ultra; OpenAI Codex supports parallel sandboxes. You start a task and review results when ready. See our Background Agents collection.
How Background Agents Work
| Step | What happens |
|---|---|
| You start a task | "Implement user auth" or "Fix failing tests in X" |
| Agent runs in background | Edits files, runs commands, iterates |
| You keep working | Code, browse, or switch tasks |
| You review | Diffs, test results, or follow-up prompts |
Unlike foreground Agent mode, you do not approve each step in real time. The agent runs until it finishes or needs your input.
Where Background Agents Appear
Cursor
- Pro+ ($60/month) and Ultra ($200/month) include background agents.
- Hobby and Pro use foreground Agent mode only.
- Cursor
OpenAI Codex
- Parallel sandboxes; agents can work on multiple tasks.
- Desktop app and integration workflows.
- OpenAI Codex
Enterprise Tools
- Some enterprise agents (e.g. Claude Cowork, Devin) support async or ticket-driven workflows. Check vendor docs.
When Background Agents Matter
| Good fit | Less critical |
|---|---|
| Large refactors, multi-step debugging | Simple one-off edits |
| Tasks that take 10+ minutes | Quick completions |
| You switch context often | You prefer step-by-step approval |
| Parallel exploration | Single-task focus |
Tradeoffs
- Pro: Frees you to do other work while the agent runs.
- Con: Less control per step; you must review output carefully.
- Con: Higher-tier pricing; background agents are often premium.
Related Concepts
- Foreground Agent: Cursor Agent, Claude Code—you approve each change.
- Ticket-driven: Devin, Claude Cowork—tasks come from Jira, Linear, Slack.
- Headless: Agents that run without a visible IDE; often API- or CI-driven.
Next Steps
- AI coding agents explained — Agent vs completion vs chat.
- Cursor pricing guide — Tier breakdown.
- Background Agents collection — Tools with async agents.
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Tools Mentioned in This Article
Claude Code
Anthropic's terminal-based AI coding agent with 80.9% SWE-bench, Agent Teams, and GitHub Actions
SubscriptionCursor
The AI-native code editor with $1B+ ARR, 25+ models, and background agents on dedicated VMs
FreemiumOpenAI Codex
Cloud coding agent with 1M+ developers, Desktop App, and parallel sandboxed environments
FreemiumWorkflow Resources
Cookbook
AI-Powered Code Review & Quality
Automate code review and enforce quality standards using AI-powered tools and agentic workflows.
Cookbook
Building AI-Powered Applications
Build applications powered by LLMs, RAG, and AI agents using Claude Code, Cursor, and modern AI frameworks.
Cookbook
Building APIs & Backends with AI Agents
Design and build robust APIs and backend services with AI coding agents, from REST to GraphQL.
Cookbook
Debugging with AI Agents
Systematically debug complex issues using AI coding agents with structured workflows and MCP integrations.
Skill
Change risk triage
A systematic method for categorizing AI-generated code changes by blast radius and required verification depth, preventing high-risk changes from shipping without adequate review.
Skill
Configuring MCP servers
A cross-tool guide to setting up Model Context Protocol servers in Cursor, Claude Code, Codex, and VS Code, including server types, authentication, and common patterns.
Skill
Local model quality loop
Improve code output quality when using local AI models by combining rules files, iterative retries with error feedback, and test-backed validation gates.
Skill
Plan-implement-verify loop
A structured execution pattern for safe AI-assisted coding changes that prevents scope creep and ensures every edit is backed by test evidence.
MCP Server
AWS MCP Server
Open source MCP servers from AWS Labs that give AI coding agents access to AWS documentation, best practices, and contextual guidance for building on AWS.
MCP Server
Docker MCP Server
Docker MCP Gateway orchestrates MCP servers in isolated containers, providing secure discovery and execution of Model Context Protocol servers across AI coding tools.
MCP Server
Figma MCP Server
Official Figma MCP server that brings design context, variables, components, and Code Connect data into AI coding sessions for design-to-code workflows.
MCP Server
Firebase MCP Server
Experimental Firebase MCP server that gives AI coding agents access to Firestore, Auth, security rules, Cloud Messaging, and project management through the Firebase CLI.
Frequently Asked Questions
What is a background agent?
Does Cursor have background agents?
What is the difference between Agent mode and background agents?
Which tools offer background agents?
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