OpenClaw is the most remarkable presence in the open-source world in 2026. This personal AI Agent project was created by Austrian engineer Peter Steinberger at the end of 2025. Within three months, it surged to become the most starred runnable software in GitHub’s history. The founder was personally poached by Sam Altman to join OpenAI, and the project was then transferred to operate independently under a foundation.

The community event that grew around it, ClawCon, started from the first event in San Francisco and continued to New York, Miami, Austin, Madrid, and Tokyo, with each city hosting thousands of attendees. In May, ClawCon made its debut in China in Shanghai. Dynamic Watch interviewed two key figures exclusively on site: Vincent Koc and Michael Galpert.

Vincent Koc, the second-highest global code contributor to OpenClaw after Peter himself, is also the Chief AI Research Engineer at Comet ML, an MIT lecturer, and submitted 20% of the early core security patches to OpenClaw. Michael Galpert, the founder and global organizer of ClawCon, is a serial entrepreneur. The image editing tool Aviary, co-founded by him, was acquired by Adobe in 2014. He later served as the Product Director for Epic Games’ “Fortnite” and now runs the AI product studio Contains Inc. He transformed ClawCon from an impromptu gathering in a San Francisco living room into a global personal AI community brand covering over a dozen cities.

When we interviewed Vincent and Michael, the most lively moment of OpenClaw had already passed. Instead, this was a more suitable moment to discuss OpenClaw. In the midst of the hype, a project is always propelled forward by numbers: GitHub stars, PRs, event attendees, community buzz, media coverage. Each number is like a spotlight, shining brightly on people but also making it a bit hard to see clearly. When the light dims slightly, the real questions surface: Why did it suddenly resonate with so many people? Can it transition from a momentary sensation to a daily tool? When an AI is no longer just for chat but begins to send messages on behalf of people, edit files, and run tasks, whose guidance should it follow?

The Shanghai ClawCon venue is still buzzing. An open-source AI project that skyrocketed to hundreds of thousands of GitHub stars in just a few months, the event was incorporated into muShanghai’s 28-day nomadic tech community initiative, with a press release stating that this 28-day nomadic tech community brought together 800 global builders, with ClawCon making its debut in China. Many Chinese developers attended the event, showing interest in Feishu, WeChat, Enterprise WeChat, DingTalk, local files, and automation scripts, and how to integrate OpenClaw into their work and lives.

However, when Vincent took the stage, he didn’t frame it as a beautiful growth story. He started with a problem: OpenClaw had received 10,000 PRs. This number could have been great for a celebration, but OpenClaw faced a situation where everyone wanted to push their own ideas. Some wanted to integrate with Feishu, others with WeChat and DingTalk. Some wanted it to read local files, run automation scripts, write code, organize data; while others wanted it to execute trading strategies or even run a content account 24/7.

Previously, open-source projects had a natural barrier: if you wanted to submit code, you had to at least read the documentation, understand some architecture, make sure the tests passed, and know what part you were changing. Now, this barrier has been lowered by AI programming tools. Even those who don’t understand the architecture can now make models write code, run tests, and submit patches. An idea that used to be stuck in one’s mind can now be packaged as a seemingly executable contribution.

Security submissions are no different. Vincent mentioned on stage that for a period, they received over 100 security vulnerability reports daily, each requiring classification and inspection. Genuine vulnerabilities are fixed promptly, but a significant portion of them are directly generated from large models. The submitters may not necessarily aim to enhance the project’s security; many times, they just want to leave their mark on a popular project. This is a new kind of noise that can consume the most valuable resource in a system: human attention.

Intelligence is no longer scarce; what’s scarce is dexterity. During his presentation, Vincent repeatedly mentioned that OpenClaw is not an ordinary product; it’s more like the whole set of “dexterity” wrapped around the model. In English, they use the word “Harness,” which you can think of as a set of devices that truly put the model to work: how it uses tools, how it remembers you, how it breaks down tasks, when it pauses to ask for help, when it proceeds, how it handles errors, and whether it should hit the brakes when costs run high.

The model is like the brain, and this set of tools is like the body. Over the past year, the industry has been too obsessed with the brain. But a person only has a brain and can’t do anything else. You also need hands, feet, a sense of pain, and a sense of boundaries. An Agent is the same. Many companies talk about Agents as “smarter models + more tools.” However, when actually used, users often feel not the intelligence but the physical fitness.

Vincent talked about a very simple triangle: speed, cost, accuracy — you can hardly have all three. If you try to save money from the start, you have to accept it being slower and less accurate. If you want both speed and accuracy, you have to accept an increase in reasoning cost, a longer toolchain, and failure modes that are harder to guess. Therefore, Vincent’s insight is that while it’s crucial for the model to keep getting stronger, the difficulty of a personal agent is shifting from “can it think” to “can it act.”

Open Source Has Opened the Door, But Also Let the Noise In. The more successful OpenClaw becomes, the harder it is to only do what it was initially meant to do. OpenClaw was originally a personal AI assistant, not an enterprise system, a multi-agent platform, or a pedestal for running businesses for all companies. But once an open-source project gains momentum, it’s challenging to belong solely to the original group of people. The beauty of openness is here, as is its cruelty.

In the past, open-source projects relied on the technical authority of a few maintainers. Now, with AI bringing about code egalitarianism, more ordinary people have gained software productivity, and they are also bringing more requirements they haven’t figured out and features that haven’t been stabilized. A community that is more open must address boundary issues. Vincent said the OpenClaw team is now adjusting its maintenance approach, working on SDKs, testing tools, documentation, and reference architecture. In plain language: they are not blocking the water, but rather reshaping the riverbed for the water.

Smarter with Use, Yet Possibly Stubborn with Continued Use. After the hype fades, true competition begins. It is no longer just about who can attract more attention but rather about forcing all Agent projects to answer a more fundamental question: how do you prove you are not a disposable toy? Hermes serves as a good contrast, with its selling point being that Agents review their performance after completing a task. This notion is quite enticing, but Vincent is very cautious about this.

A skill automatically written down by an Agent may be compressing experience, or it may be welding errors. It is useful seven out of ten times, misleading three times. How does the system determine whether to keep it or not? It turns a fluke successful path into a fixed process. When the environment changes next time, will it still follow the wrong path? Learning in the real world is not about cramming all experiences into the warehouse. True learning also includes forgetting, correcting errors, and admitting “this path was useful before, but not necessarily now.”

Memory is not a function, but the beginning of a relationship. When Michael was asked what the most core ability of a personal resident Agent would be if everyone had one in the future, he didn’t say reasoning, multimodality, or tool invocation. He said, memory. Tools are used based on function, relationships are maintained based on memory. An Agent that feels like meeting for the first time every time it is opened is always just a tool. Personalization is about the Agent knowing who you are, how you work, what you dislike, where you always hesitate, and where you tend to act impulsively.

Vincent also addressed this issue in his speech. He said that the industry may have high-performance models, but lacks a sense of long-term companionship. When we talk about a personal Agent, it is no longer just a business scenario, not just a field in a form asking, “What will the user do with it?” It is an Agent that works for me, an Agent I converse with. Everyone’s expectations of AI are different, and designing for this is a completely unknown field.

Security Ultimately Boils Down to a Human Issue. During ClawCon, someone asked Vincent about security. Tools like OpenClaw become more useful as you grant them more permissions; however, the more permissions they have, the more dangerous they become. Vincent’s response had two layers. Firstly, OpenClaw is too conspicuous. Being a large open-source repository on GitHub, it has always been under the watchful eyes of security researchers. Secondly, they collaborate with security research teams to integrate discovered issues into the product and strive for transparency.

Security for an Agent is not just about whether it has vulnerabilities. It’s more like a boundary dilemma: what it is allowed to touch, what it is prohibited from touching; when it can act autonomously, when it must pause to seek your guidance; whether it can represent you in messaging, modify files, run scripts, or connect to enterprise systems; and in the event of an incident, who bears the responsibility. The allure and risk of a personal Agent are one and the same.

“Not Knowing Yet” Is a Form of Honesty. Michael said that OpenClaw should never become a closed-source project. It should always remain open-source because it has opened the door to the personal Agent era for everyone. But open-sourcing has not made the issues disappear. Agents should not be solely defined by model companies or platforms. When asked in Shanghai what OpenClaw should never become, Vincent said that as an open-source project, people will use it for various purposes, from children’s toys to running businesses. It’s hard to say, “this should not be done.”

The answer from OpenClaw is not “we already figured it out”; its answer is more like “we don’t know yet.” We don’t know how the personality of a personal Agent should be designed, we don’t know when automatic journaling is useful or harmful, we don’t know where the community will take the project to places never before imagined, and we don’t know what kind of boundaries should be drawn between personal assistants and enterprise systems. But when faced with something that can act on behalf of others, claiming to know the answer too quickly becomes suspicious.

The most dangerous Agent in the future may not be the disobedient one. It could be the one that is too obedient, too handy, too much like you, to the point where you forget to ask: Whose hand does it really serve?

[BlockBeats]