What is OpenClaw? A Simple Guide to AI Agents That Actually Do Things

OpenClaw is an open-source personal AI assistant — created by Peter Steinberger, an Austrian engineer and former founder of PSPDFKit — that runs on your local machine and connects to the messaging apps you already use. With over 200,000 stars and 35,000+ forks on GitHub, it has become the fastest-growing repository in GitHub history and one of the most talked-about tools for AI that actually does things, not just answers questions.

What is OpenClaw?

Most people are familiar with AI assistants that answer questions. You type something in, you get a response, and then you go do the thing yourself. That is useful, but it is only half the picture.

OpenClaw is different. It is a personal AI assistant that runs on your own machine and works through the messaging platforms you already use — WhatsApp, Telegram, Discord, Slack, Microsoft Teams, Signal, iMessage, SMS, and more. Rather than opening a separate app, you just message your assistant the way you would message a friend, and it takes care of the rest.

Under the hood, a component called the Gateway handles the connection between OpenClaw and those messaging channels, routing your instructions to the agent and delivering results back to you wherever you are.

The project has an interesting naming history. It was originally published as Clawdbot in November 2025 by Peter Steinberger. Following trademark complaints from Anthropic, it was briefly renamed to Moltbot on January 27, 2026, and then renamed again to OpenClaw just three days later — the name that stuck.

OpenClaw can execute shell commands, read and write files, browse the web, send emails, manage your calendar, run scheduled automations, and maintain persistent memory across sessions. Skills — add-ons that extend what the assistant can do — are installed from ClawHub, the official skill marketplace.

To put it simply: if a regular AI chatbot is like a very smart advisor who tells you what to do, OpenClaw is more like a capable assistant who actually goes and does it — right from your phone or desktop, through apps you already have.

OpenClaw is open-source, which means the code is freely available for anyone to look at, use, and improve. That transparency is a big part of why so many developers and companies trust it. You are not locked into a single company’s decisions about what the AI can or cannot do.

What Can AI Agents Do?

Before diving deeper into OpenClaw specifically, it helps to understand what AI agents are capable of. The short answer is: a lot more than most people realize.

Here are some real-world examples of tasks that AI agents can handle:

Email management. An agent can read your inbox, sort messages by priority, draft replies based on your preferences, and flag anything urgent — all without you having to touch your email client.

Travel booking. Rather than spending an hour comparing flights on different websites, an agent can search across multiple platforms, filter by your preferences (aisle seat, no layovers, under a certain price), and present you with the best options — or even book the trip outright if you give it permission.

Scheduling. Agents can look at your calendar, find gaps, coordinate with other people’s availability, and book meetings on your behalf. What used to take a back-and-forth chain of emails can happen in seconds.

Research. Need to understand a new topic for work? An agent can browse the web, pull together information from multiple sources, summarize the key points, and deliver a clear briefing — saving you hours of reading.

Social media. Agents can monitor mentions of your brand, draft responses, schedule posts, and track engagement trends, all while you focus on something else entirely.

These are not hypothetical future capabilities. They are things people are building and using with frameworks like OpenClaw right now.

Why is OpenClaw So Popular?

OpenClaw did not become one of the most starred projects on GitHub by accident. Several things set it apart.

It is modular. OpenClaw is built so that you can swap pieces in and out easily. Want to use a different AI model? Switch it. Want to add a new tool your agent can use? Plug it in. This flexibility makes it attractive to everyone from solo developers experimenting on weekends to large engineering teams building production software.

It has a thriving community. Over 200,000 GitHub stars and 35,000+ forks is not just a vanity metric — it makes OpenClaw the fastest-growing repository in GitHub history by star count. That reflects the size of the community contributing code, writing tutorials, answering questions, and building tools that extend what OpenClaw can do. When something breaks or you get stuck, there is a very good chance someone has already solved your exact problem.

It sits at the right moment in time. The AI agent market was valued at around $7.6 billion in 2025 and is projected to surpass $50 billion by 2030. That kind of growth means there is enormous demand for tools that let people build agents quickly and reliably. OpenClaw arrived with good timing, solid design, and an open-source ethos that the developer community embraced immediately.

It handles the hard parts. Building an AI agent from scratch means solving a lot of tricky problems: how does the agent decide what to do next? How does it recover when something goes wrong? How does it keep track of context across a long task? OpenClaw has built-in answers to all of these questions, so developers do not have to reinvent the wheel every time.

It works with the big AI models. OpenClaw is designed to work alongside the leading large language models — the AI brains that power tools you may already use. It acts as the coordination layer, giving those models hands and feet so they can interact with the real world.

The Challenge with OpenClaw

OpenClaw is powerful, but power comes with complexity. For all its strengths, it is not exactly designed for beginners.

Getting started requires Node.js version 22 or higher, and the initial setup runs through a wizard launched with openclaw onboard. From there, configuring the Gateway process — the component that connects OpenClaw to your messaging channels — adds another layer of setup that assumes familiarity with the command line and networking basics.

Security is an active concern as well. A recent audit identified 512 vulnerabilities in the default OpenClaw stack, including 8 critical ones. Separately, a Censys scan found over 21,639 exposed OpenClaw instances reachable from the public internet — meaning many deployments are running without adequate access controls. This is not a hypothetical risk; it is a live one that anyone self-hosting OpenClaw needs to think carefully about.

There is also the question of ongoing maintenance. Agents that do real things in the real world need to be monitored. They need credentials to access your accounts and services, and those credentials need to be stored securely. When an agent makes a mistake — and they do make mistakes — you need a way to catch that and correct it. All of this requires ongoing attention that a bare OpenClaw setup does not automatically provide.

Documentation, while improving, can be dense and assumes a fair amount of existing knowledge. The community is helpful, but navigating it as a newcomer can feel like being dropped into a conversation that started without you.

None of this is a criticism of OpenClaw. These trade-offs are inherent to any powerful, flexible, open-source tool. The people building with it are often sophisticated developers who want that level of control. But for businesses and individuals who want the benefits of AI agents without the engineering overhead, there is a gap.

Enter ZeroClaw

That gap is exactly what ZeroClaw was built to address.

ZeroClaw takes the power of OpenClaw and wraps it in an experience that does not require a computer science degree to use. The underlying agent capabilities are the same — the real-world automation, the tool use, the ability to string together complex tasks — but the process of setting up, configuring, and running those agents is handled for you.

Think of it this way: OpenClaw is the engine. ZeroClaw is the car with a steering wheel, a dashboard, and a comfortable seat.

If you have been curious about what AI agents could do for your work or your business but found the technical side intimidating, ZeroClaw is worth a look. It is designed to make powerful agent automation accessible to anyone, not just developers.

Conclusion

OpenClaw represents something genuinely new in the world of software: a serious, battle-tested personal AI assistant that takes actions, not just gives advice. Its 200,000+ GitHub stars and 35,000+ forks reflect both the quality of the tool and the size of the community rallying around it. On February 14, 2026, creator Peter Steinberger announced he was joining OpenAI, and that the OpenClaw project would be handed off to an open-source foundation — a move that signals just how significant the project has become.

The rise of AI agents is not a distant trend. With the market on track to grow from $7.6 billion to over $50 billion by 2030, the question is not whether AI agents will become part of everyday work and life — it is when, and how smoothly that transition happens.

OpenClaw makes it possible to have an agent that manages email, books travel, handles scheduling, conducts research, and manages social media on your behalf — all through the messaging apps you already use. For technically minded users willing to handle their own setup and security, it is an exciting and capable platform. For everyone else, tools like ZeroClaw exist to make those same capabilities accessible without the technical friction.

The future of AI is not just about answering questions. It is about getting things done. OpenClaw — and the ecosystem growing around it — is a big part of how that future gets built.