What Is OpenClaw?
OpenClaw is an open-source AI assistant that runs on your own machine and works through chat apps you already use, including WhatsApp, Telegram, Discord, Slack, Teams, Signal, and iMessage. It is designed as a personal agent platform, which means it does more than answer prompts: it can remember context, connect to tools, browse the web, work with files, and carry out actions on a computer.
Who Built OpenClaw?
OpenClaw was created by Peter Steinberger, an Austrian developer who introduced the project publicly as something he hacked together as a weekend build before it took off. In the launch post, Steinberger says the project started as “WhatsApp Relay,” then moved through the names Clawd and Moltbot before settling on OpenClaw.
As the project grew, it shifted from a one-person experiment into a broader open-source effort with maintainers and contributors. Reporting in February 2026 also said Steinberger joined OpenAI while OpenClaw was set to continue as an open and independent foundation-backed project.
That background helps explain the tone of the software. OpenClaw was not introduced as a polished corporate product first; it began as a builder-led tool meant to give people a practical AI assistant they could run on their own systems.
What AI Models Does It Use?
OpenClaw does not depend on one single model. Its own site says it works with Anthropic, OpenAI, and local models, while the launch post for the OpenClaw name also lists support added for KIMI K2.5 and Xiaomi MiMo-V2-Flash in that release.
In practice, that means OpenClaw acts more like a control layer or agent framework than a model itself. You connect the assistant to a provider and model you want to use, and OpenClaw handles the chat interface, memory, skills, tool access, and actions around that model.
Public write-ups and configuration guides around the project mention support or use cases involving Claude models, GPT models, DeepSeek, Gemini, and local models through Ollama. Model references are described in a provider-and-model format such as openai/gpt-5.1-codex or ollama/llama3.3, which shows that the platform is built to route across several back ends rather than lock users into one vendor.
Why the Model Choice Matters
The model choice shapes what OpenClaw feels like day to day. Stronger models tend to do better with long instructions, tool calling, multi-step tasks, and messy real-world workflows, while local models can be attractive for privacy or lower ongoing cost.
That flexibility is one of the project’s biggest selling points. A person can run OpenClaw on a laptop or server they control, pick a cloud model for stronger performance, or point it to a local model if keeping data on-device matters more.
This also explains why different people describe very different OpenClaw experiences. The platform may stay the same, but the result changes depending on the selected model, the connected tools, and how much access the assistant has to files, browsers, and other systems.
What OpenClaw Really Is
The clearest way to describe OpenClaw is this: it is a self-hosted personal agent system created by Peter Steinberger and expanded by an open-source community. It runs on your machine, lives inside chat apps, and can be connected to several AI model families instead of relying on one built-in brain.
So if someone asks what OpenClaw is, the short answer is not just “an AI chatbot.” It is a user-controlled assistant layer that sits between your chat apps, your computer, your tools, and whichever supported model you choose to power it.
