OpenAI hires the creator of OpenClaw: the illusion of an “open” agentic future

Last updated: February 17, 2026 by the editorial team

Author's): Mandar Karhade, MD. Doctorate

Originally published in Towards Artificial Intelligence.

When an architect of the open source agent revolution joins a closed source giant, we must ask ourselves whether innovation is being encouraged or stymied

This is a quick and short article I guess. But the news got out. Peter Steinberger, creator of the viral AI agent OpenClaw, has officially joined OpenAI.

OpenAI hires the creator of OpenClaw: the illusion of an “open” agentic future

OpenAI CEO Sam Altman announced that Steinberger is joining to lead the “next generation” of personal agents. But wait. There is a twist. They claim that OpenClaw will become a “foundation” and remain an open source project powered by OpenAI.

The article discusses the implications of Peter Steinberger joining OpenAI and the potential transition of OpenClaw from an independent open source project to a corporate-controlled entity. This raises concerns about the compatibility of OpenAI's business model with OpenClaw's initial ethos, raising questions about whether the project will maintain its open source purity or become a vehicle for corporate profits. The author highlights the risks of centralizing AI development and the need for community adaptation, while calling on developers to remain active in open source initiatives despite corporate interference.

Read the entire blog for free on Medium.

Published via Towards AI


We create enterprise-class artificial intelligence. We will also teach you how to master it.

15 engineers. Over 100,000 students. Towards AI Academy teaches what will actually survive production.

Get started for free – no strings attached:

→ Agentic's 6-day AI Engineering email guide – one hands-on lesson per day

→ Agent Architecture Cheat Sheet – 3 years of architecture decisions in 6 pages

Our courses:

→ AI Engineering Certificate – over 90 lessons from project selection to implemented product. The most comprehensive practical LLM course on the market.

→ Agent Engineering Course – hands-on learning about production agent architectures, memory, routing, and evaluation platforms – built on real-world enterprise encounters.

→ Artificial Intelligence at work – Understand, evaluate and apply artificial intelligence to complex work tasks.

Note: The content of the article contains the views of the authors and not Towards AI.


LEAVE A REPLY

Please enter your comment!
Please enter your name here