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3 changes: 2 additions & 1 deletion docs.json
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"overview/first-projects",
"overview/faqs",
"overview/community",
"overview/contributing"
"overview/contributing",
"overview/strategy"
]
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{
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208 changes: 208 additions & 0 deletions overview/strategy.mdx
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---
title: OpenHands Commercial Open Source Strategy
description: OpenHands' strategy to become the open standard for AI coding agents
---

## Vision


OpenHands' vision is to become **the open standard for AI coding agents** — a foundation for AI software development that is transparent, extensible, and community-driven.


## Problems We Solve


### "Building With" OpenHands: Use OpenHands as an Inner Loop local AI coding agent


**Problem:** Developers need a reliable and powerful AI coding agent to boost productivity.


- Designed for most **individual developers**
- **Ad-hoc usage** focused on local or small-team development
- Solves **developer productivity** challenges
- Provides **model-agnostic AI code assistance** that integrates locally
- Operates in a **highly competitive** landscape with multiple alternatives


### "Building On" OpenHands: Use OpenHands to solve repetitive engineering tasks


**Problem:** Organizations need a way to reduce the toil and burden of recurring engineering tasks that distract from roadmap; and they seek solutions that can be scaled to nearly every development team in the organization.

- Designed for **teams and organizations — these tend to be Commercial entities**
- Within organizations, used by **Agent Engineers** who build agents with OpenHands
- Supports **repeatable, cloud-based workflows and automations.** Sometimes this is referred to as "Outer Loop" engineering tasks, such as PR reviews, security remediation, and documentation updates.
- Enables **API-driven integration** into applications and development pipelines
- Solves problems around **scalability, extensibility, and control**
- Focused on enabling **custom agent orchestration**


**Strategic Shift:**


We're evolving OpenHands to support "Building On" use cases — turning OpenHands into a platform for scaling 100s of agents that address repetitive engineering problems


## Example Use Cases — Repetitive Engineering Tasks


OpenHands is used across a wide range of powerful, scalable use-cases in the SDLC process:


- **Maintenance**
- Example: 30x throughput on CVE resolution
- Example: Automatic documentation and release notes
- **Modernization**
- Example: Adding type annotations to an entire Python codebase
- Example: Refactoring a monolithic Java application to microservices
- **Migration**
- Example: Upgrading 1000s of jobs from Spark 2 to Spark 3
- Example: Moving from Redux to Zustand
- **Tech Debt**
- Example: Detecting and deleting unused code
- Example: Adding error handling based on production logs
- **Automated Testing, Bug Fixing, Documentation**, etc.


## Target Customers for OSS and Commercial


### Open Source (OSS)


- **Goal:** Empower individual developers with a model-agnostic, open, and extensible coding agent that integrates seamlessly into their workflows.
- **Primary audience:** Individual developers on the bleeding edge of software development; AI hobbyists.
- **Use cases:** Personal productivity, ad-hoc local development, experimentation, and contributing to open AI infrastructure.


### Commercial

- **Primary audience:** Mid-to-large enterprises and technical teams.
- **Goal:** Help organizations safely leverage AI at scale to modernize, refactor, and maintain complex systems across 100s of development teams.
- **User personas:**
- **Developers w/ AI experience:** Developers who already may be familiar with pairing with AI to accomplish work, but ready to begin delegating wholesale tasks to AI agents for maximum productivity.
- **Agent Engineers:** Developers on the edge of AI engineering who are looking to integrate agents into workflows or applications.
- **Buyer personas:** Engineering Leaders
- **Use cases:**
- "An OpenHands agent for every developer": Multi-user collaboration, scalability, governance, and security
- Refactoring and code modernization
- Embedding AI agents into apps and workflows


## Dividing Lines Between OSS and Commercial

_OpenHands' CEO and founder discusses the lines between OSS and Commercial in this blog post: [Walking the Line with Commercial Open Source (June 2025)](https://openhands.dev/blog/walking-the-line-with-commercial-open-source)_


OpenHands follows an **Open Core** model:


- **Open Source Core:**

The foundation of OpenHands is open and free for all developers. Most new features default to open source unless they explicitly solve enterprise-specific needs.

- **Enterprise Offering:**

Focused on mid-to-large enterprises, addressing needs around multi-user management, scalability, and security.



Our investment is roughly **50/50** between open source and commercial development.


### **Feature Selection Principle**


- **Developer problems → Open source by default:**

Features that solve an individual developer's needs belong in the open source core (e.g., productivity, model integration, developer tooling).

- **Buyer problems → Commercial features:**

Features designed to solve organizational or managerial challenges are commercial (e.g., organizational management, collaboration, scalability).



**Example:**


- Commercial feature: Organizational Management — features for managing OpenHands access across hundreds of developers
- Open Source: MCP support, Secrets Support, Planning Agent mode, etc.


## Strategic Challenges


1. **Large Product Portfolio**

Balancing focus and resources across a broad range of features and use cases.

2. **Driving More Community Contributions**

Encouraging external contributors while maintaining code quality and stewardship.

3. **Increasingly Crowded "Build With" Market:**

Differentiating in a competitive field of AI coding assistants.

4. **Wide-Ranging Developer Profiles:**

Supporting diverse users — from new-to-AI developers to hobbyists to enterprise teams.



## Unique Differentiators


- **Open Source Foundation:** Transparent, extensible, and community-driven.
- **Model-Agnostic Architecture:** Works with any LLM — the durable value lies in the agent layer, not the model.
- **Cloud-First Scalability:** Supports persistent, autonomous cloud agents that can handle repetitive, large-scale tasks.
- **Focus on Repetitive Tasks:** Automates ongoing engineering work — refactoring, maintenance, dependency upgrades — where AI delivers compounding value.
- **Dual Persona Alignment:** Serves both individual developers ("Build With") and enterprise teams ("Build On") through a unified ecosystem.


## Strategic Roadmap Pillars


1. **Bet on Cloud Agents as the best way to work with AI coding agents**

Prioritize cloud-based runtimes for scalable, persistent, autonomous systems.

2. **Shifting towards "Build On" to optimize for repetitive, high-leverage work**

Emphasize ongoing tasks like maintenance and refactoring over one-off code generation.

3. **Maintain a high performance, model-agnostic approach**

Continue to integrate multiple models and support extensibility as the LLM ecosystem evolves.

4. **Bridge both developer needs and enterprise needs**

Build pathways that help individual developers grow into organizational adopters — "Build With" → "Build On."

5. **Foster a thriving Open Source community**

Grow contributor engagement, maintain transparent governance, and accelerate open development.



## Commitment to Open Source


We believe open source works best with clear stewardship and active participation.


- We maintain the **roadmap** and **good first issues** to guide community contributions.
- We **review pull requests diligently** and recognize valuable contributions.
- We maintain **transparent metrics** across:
- **Community:** Total contributors and open PRs awaiting review.
- **Product Quality:** NPS and SaaS adoption as a proxy for user satisfaction.
- **Adoption:** Public reference examples and tutorials.
- **Impact:** Case studies highlighting enterprise deployments.


### Our long-term commitment:


To make OpenHands the **best open source generalized AI coding agent**, serving as the backbone of transparent, collaborative AI development.