OpenHands - AI-powered open source coding agent platform

What Is OpenHands?

Every developer knows that feeling—spending hours tracking down a tricky bug, or watching precious engineering time disappear into repetitive code reviews and dependency updates. The reality is that modern software teams spend far more time maintaining existing code than building new features. Security vulnerabilities pile up, technical debt accumulates, and the bottleneck isn't ideas—it's bandwidth.

OpenHands is an open-source cloud coding agent platform designed to automate the tedious, time-consuming tasks that slow your team down. Think of it as an AI-powered software engineer that can work alongside your team—independently tackling bug fixes, code reviews, refactoring projects, and more. Built with security and flexibility at its core, OpenHands runs in isolated Docker containers, scales from a single task to over a thousand concurrent agents, and works with virtually any large language model you prefer.

What makes OpenHands different? First, it's completely open-source under the MIT license—you can inspect every line of code, understand exactly how the agent thinks, and contribute to its evolution. Second, it's model-agnostic: whether you prefer Claude, GPT,4, Anthropic, AWS Bedrock, or MiniMax (which offers free usage), OpenHands integrates seamlessly. Third, it's built for scale. From one developer running a single agent locally to an enterprise deploying thousands of agents across a Kubernetes cluster, the architecture grows with your needs.

The numbers speak for themselves: over 69,600 GitHub stars, more than 5 million downloads, and a community of 65,000+ members. On SWE-bench—the gold standard benchmark for software engineering agents—OpenHands achieves a score of 77.6%, outpacing most solutions in the space. Companies like TikTok, VMware, Roche, Amazon, Apple, Netflix, and Mastercard trust OpenHands to accelerate their development workflows.

Core Features That Power Your Development Workflow

OpenHands isn't a single tool—it's a flexible platform with multiple entry points designed to fit different workflows and team preferences. Here's how you can put it to work.

OpenHands SDK gives you a modular Python library that encapsulates all agent technologies. You can embed AI agents directly into your applications and workflows, whether you're running a single agent on your laptop or orchestrating thousands in the cloud. The SDK is the foundation that powers every other interface—CLI, Local GUI, and Cloud all build on top of it. If you're building custom agent systems or integrating automation into existing platforms, this is your starting point.

OpenHands CLI brings the power of autonomous agents to your terminal. If you're comfortable with command-line tools like Claude Code or Codex, you'll feel right at home. The CLI supports real-time interaction, a command palette accessible via Ctrl+P, and a confirmation mode that lets you review and approve agent actions before they execute. It's perfect for developers who want rapid task execution without leaving their terminal.

OpenHands Local GUI runs a full-featured web interface on your laptop, giving you complete visibility into what the agent is thinking and doing. Built with REST APIs and a React single-page application, the Local GUI mirrors the experience you'd expect from products like Devin or Jules—except it runs entirely on your own machine. Every agent action, file change, and decision is visible in real-time, all running safely in a sandboxed environment.

OpenHands Cloud takes the platform to hosted infrastructure, designed for teams that need collaboration, multi-user support, and enterprise-grade access controls. With role-based access control (RBAC), your team can work together securely. Deep integrations with GitHub, GitLab, Bitbucket, Slack, Jira, and Linear mean the agent fits naturally into the workflows you're already using. Assign agents to review pull requests, respond to incidents, or automate routine maintenance tasks without lifting a finger.

Containerized Sandbox Runtime is the security backbone of the entire platform. Every agent task executes inside an isolated Docker container (or Kubernetes pod), completely separated from your host machine. This means agents can modify code, run tests, and execute commands without risking your development environment. Fine-grained access controls and audit trails ensure you always know what's happening.

Enterprise Security Features take things further for larger organizations. SAML/SSO integration connects with your identity provider, RBAC provides granular permissions down to individual resources, and you can deploy OpenHands in a private VPC with complete data isolation. Bring your own LLM (BYOK) to keep sensitive code within your own infrastructure.

Who's Using OpenHands?

OpenHands serves a diverse range of teams—from individual developers automating their personal workflows to Fortune 500 enterprises running mission-critical development operations. Here's what real users are achieving.

Flextract needed a way to handle a massive backlog of bug reports. Before OpenHands, their team was drowning in tickets—manual triage and fixing consumed weeks. After deploying OpenHands, the platform automatically fixed 87% of bug tickets on the same day they were filed. Their engineering lead put it simply: it felt like hiring an entire army of engineers.

C3 faced a unique challenge: they needed to orchestrate autonomous coding agents at scale across remote infrastructure. After evaluating every option on the market, OpenHands was the only solution that could reliably prompt and manage coding agents in a distributed, large-scale environment. Today, C3 runs OpenHands as a core part of their AI-driven development infrastructure.

AMD partnered with OpenHands to bring AI-powered coding agents to Ryzen AI PCs. Through integration with Lemonade Server, AMD users can run local coding agents directly on their machines—bringing the power of autonomous development to edge devices without depending on cloud connectivity.

These aren't isolated success stories. OpenHands powers development teams at TikTok, VMware, Roche, Amazon, Apple, Netflix, Mastercard, Red Hat, MongoDB, NVIDIA, and Google. The ROI is tangible: teams report up to 30× productivity improvement, have fixed thousands of vulnerabilities, and completed work that previously took weeks in just hours.

The Technology Behind OpenHands

If you're evaluating OpenHands from a technical perspective, here's how it works under the hood—and why it performs so well on real-world software engineering tasks.

Model-agnostic architecture is central to OpenHands' design philosophy. Rather than tying you to a single LLM provider, the platform exposes a unified interface that works with Claude (Anthropic), GPT-4/4o (OpenAI), AWS Bedrock, MiniMax, and any other LLM with API compatibility. This means you're never locked in—you can experiment with different models, switch based on pricing, or use specialized models for specific tasks. MiniMax is even available for free usage, lowering the barrier to experimentation.

The codebase itself reflects this flexibility. The project is built primarily in Python (73.2%) for the agent logic and orchestration, with TypeScript (24.9%) powering the web interface and APIs. A small amount of Go templates and Jinja round out the stack. This architecture is deliberately modular—each component (agent runtime, sandbox, web UI, API) can be used independently or combined.

Concurrency is where OpenHands really shines. The platform supports 1,000+ concurrent agents running simultaneously, whether in a cloud cluster or your own Kubernetes infrastructure. This isn't theoretical—enterprises are running large-scale agent farms today, assigning different agents to different repositories, projects, or tasks in parallel. From a single debugging task on your laptop to a massive CI/CD pipeline with hundreds of autonomous reviewers, the same underlying technology scales seamlessly.

On SWE-bench, the most respected benchmark for evaluating software engineering agents, OpenHands achieves a score of 77.6%. This places it among the top-performing solutions for realistic software engineering tasks like bug fixes, feature implementation, and code refactoring. The benchmark tests agents on real-world GitHub issues from popular open-source projects—so these scores translate directly to the kinds of tasks you'll actually delegate to the agent.

For organizations with massive codebases, the Large Codebase SDK provides enterprise-grade capabilities: deep code analysis across thousands of files, intelligent navigation of multi-repository projects, and the ability to run agents that understand your entire architectural context. Combined with MCP (Model Context Protocol) support, you can extend the agent's toolset to connect with external systems, databases, and data sources—building truly custom automation workflows.

Practical Use Cases

Here's where OpenHands delivers real value in everyday development. Each scenario represents a task that's either too tedious, too repetitive, or too time-consuming for human engineers to handle manually.

Vulnerability remediation is one of the most impactful use cases. Security vulnerabilities in your codebase need fast action, but manual patching is slow and error-prone. OpenHands agents scan your codebase, identify known vulnerabilities, and automatically generate and test fixes. Thousands of vulnerabilities have already been patched through OpenHands—work that would have required dedicated security sprints is now handled continuously.

Automated code review transforms your PR pipeline. Instead of waiting hours (or days) for a human reviewer, you can deploy agents that summarize pull requests, apply consistent feedback, suggest improvements, and even fix failing tests automatically. Code reviews that once took hours now complete in minutes—and they're consistent, thorough, and available 24/7.

When production incidents strike, speed matters. OpenHands agents can be deployed immediately to analyze logs, trace errors across your codebase, identify root causes, and generate pull requests with potential fixes. Your team gets a head start on resolution while the on-call engineer assesses the situation—turning hours of debugging into minutes of evaluation and approval.

Test coverage expansion keeps your codebase healthy without adding burden to your team. Agents automatically generate and maintain tests for new features, ensuring you catch regressions before they ship. This is especially valuable for legacy codebases where test coverage has lagged—OpenHands can methodically improve coverage across the entire project.

Speaking of legacy code, code refactoring with OpenHands is remarkably effective. Agents can decompose monoliths, clean up technical debt, modernize legacy codebases, and apply architectural patterns—all without slowing down your roadmap. The agent works incrementally, submitting well-reviewed PRs at each step.

For teams with COBOL systems, OpenHands offers something genuinely unique: the ability to understand, document, and modernize COBOL codebases while preserving business logic. These systems often contain decades of critical business rules that no one fully understands anymore. OpenHands can analyze the code, generate documentation, and even translate functionality to modern languages—safely and incrementally.

Dependency upgrades are notoriously painful—updating one library can cascade into breaking changes across dozens of files. OpenHands automates this end-to-end: it identifies outdated dependencies, researches breaking changes, applies necessary code modifications across multiple repositories, and runs your full test suite to verify everything still works.

Finally, if you're migrating between Apache Spark versions—whether upgrading to newer Spark releases or moving workloads between environments—OpenHands handles the analysis, migration, and validation. It understands Spark APIs, identifies deprecated methods, and generates compliant code for your target version.

Frequently Asked Questions