# Use Cases

agentOS runs coding agents inside isolated VMs with a real filesystem, shell,
and process model. These are the shapes that keep coming up.

## 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.