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Who is agentOS for?

From personal assistants to enterprise fleets, agentOS powers every kind of AI agent.

Programming Agents

Purpose-built for agents that write, test, and deploy code autonomously.

  • Native file system access with git support
  • Shell execution with full toolchain access
  • Package installation and dependency management
  • Test runner integration
Example

An agent that takes a GitHub issue, writes the fix, runs tests, and opens a pull request.

Background Agents

Long-running agents that operate asynchronously, processing tasks over hours or days without human intervention.

  • Persistent state survives crashes and restarts
  • Queue commands while agents work
  • Resume from exactly where they left off
  • Monitor progress in real-time
Example

A code migration agent that refactors a large codebase over several hours, committing changes incrementally.

Evals

Run agent evaluations and benchmarks at scale without spinning up expensive sandboxes for each test.

  • Low memory per instance compared to sandboxes
  • Near-zero cold starts for rapid iteration
  • Deterministic replay for debugging
  • Cost-effective at thousands of runs
Example

Evaluating 10,000 agent responses in parallel to measure performance across different prompts.

Multi-Agent Systems

Coordinate multiple agents working together on complex tasks with shared state and communication.

  • Shared file systems between agents
  • Real-time inter-agent messaging
  • Workflow orchestration primitives
  • Centralized observability
Example

A team of agents where one researches, one writes, and one reviews, all collaborating on a document.

Data Processing

Run ETL pipelines, data transformations, and analysis tasks with agent intelligence.

  • Stream processing capabilities
  • Database connections and queries
  • File format conversion
  • Incremental processing
Example

An agent that ingests raw data, cleans it, runs analysis, and generates reports on a schedule.

Workflow Automation

Chain agent tasks into complex workflows with conditional logic and human-in-the-loop steps.

  • Durable workflow execution
  • Retry and error handling
  • Scheduled and triggered runs
  • Approval gates and notifications
Example

A hiring workflow where agents screen resumes, schedule interviews, and prepare onboarding docs.

Personal Agents

Lightweight agents that assist individual users with daily tasks and workflows.

  • Low resource overhead for personal use
  • Local-first with optional cloud sync
  • Custom tool integration
  • Privacy-focused execution
Example

A personal agent that organizes your calendar, drafts emails, and manages your todo list.

Ready to build?

Get started with agentOS in minutes. One npm install, zero infrastructure.

Read the Docs