My team fully abandoned our attempts to make OpenClaw or Claw-like agents work for us.
We invested a sizable chunk of our R&D budget to setting various Claws up to help our software and QA teams. It took about a week after launch for the team to fully sour on the idea of using these systems.
The biggest feedback we collected was that any tasks they assigned to the Claw systems would turn into tangled messes often requiring significant time investment to understand, and mostly ending in the team scraping the code changes over quality concerns.
The team really struggled to find anything these Claw systems could be tasked with that wouldnt end in poor results, So we ended up scraping the idea entirely. I think it will be quite a few more years until these types of systems are appropriate for the enterprise.
We gave it a few months try. My conclusion was that it did interesting things but is designed completely wrong from the ground up which means it's got a lot of moving parts that are part of the code base that can break for all sorts of reasons.
As a learning exercise it was pretty nice. But since then the plugin/connector ecosystem for things like Claude Code/Cowork and ChatGpt/Codex has first come into existence and then matured to the point where they do most of what made OpenClaw interesting before that was the case. But in a way that can be shipped to lots of users. That wasn't true when I started using it. We played with it for a bit but in the end the code base is a mess, random shit breaks every time you update it, and you end up doing very dodgy shit with it that no responsible CIO would want to sign off on.
The current batch of tools from Anthropic and OpenAI is pretty solid but there are still lots of feature gaps, UX issues, security challenges, etc.
I think a lot of these tools will get into the enterprise in exactly the same way that usb sticks, MS Office, smart phones and other consumer tech got into the enterprise: employees will bring them and use them. Some bosses will tell them off and then make an exception for themselves. Because the promise of not having to do monkey work that can now be automated is unbelievably tempting if you need to do lots of that work. Even if this stuff only half delivers on some of the promises. So, my guess is that this could go fairly quickly. I already see a lot of non technical people that are pretty clued in to things like Claude Cowork. There will be some rogue early adoption followed by more enterprise appropriate solutions. That's already happening.
Here in Germany, there are a few German AI companies that work with big conservative German companies and the public sector (e.g. Langdock and Deepset). The type of organization where privacy and data security concerns weigh heavily. These companies can work with OSS models but OpenAI can do proper data residency in Germany as well if you talk to them. Azure, AWS, and others have very acceptable options. And there's a whole ecosystem of companies that are building on top of that.
What kind of use cases where you looking to solve. In general coding, marketing and research projects are the sweet spot with these tools. The Claws have commoditized with Claude Cowork, Hermes etc entering the space.
I don't know about other people, but the name "OpenClaw" immediately signals jank and wrecklesness to me. Like, as a consumer, I will pretty much immediately write it off.
That's why we built https://lobu.ai which is a multi-tenant implementation for proactive agents like OpenClaw. It has entity based memory for building the org context layer and every channel/user gets its isolated container.
I've never run it, but isn't OpenClaw kind of useless if you sandbox it? I thought the entire point is that it has access to do everything. The danger with OpenClaw IMO isn't so much that your local machine gets hacked (although it's certainly a real danger), the danger is giving sensitive data to something horribly unreliable that can leak it or take actions on your behalf that are very dumb. I can understand (although very much disagree) with individuals running it, but trying to do it in the "enterprise" feels like playing with fire in a bad way.
With agentjail (github.com/LuD1161/agentjail), I've tried to contain coding agents in os-native sandboxes (sbpl for macos and similarly for linux) + policy guardrails evaluated by Open Policy Agent (OPA), policies written in rego.
Protocol aware network proxy coming soon
Then you can match a DSL and block particular network requests.
This ensures you no longer fear --dangerously-skip-permissions and stop babysitting agents
What else would you want to see in this project? Please star the repo, if you like the idea :)
I was a basic user who happened to just TRY OpenClaw. Thankfully it was brief and thankfully I ended my session after being underwhelmed because the very next day, they were on the news for the wrong reasons. There is no way on earth I am trusting this or anything even remotely similar in an enterprise setting. In a way, it was course correction for me - I was super optimistic about AI until I saw how ugly it could get. Nope. Nopedy nopedy nope.
Anything made in a couple of days or even hours is abandoned easily. This is how I felt when I saw the onslaught of OpenClaw tutorials months ago. I wonder how many of those influencers who felt they were so far ahead of the game are still using it and if they still feel the GAME has been SHOCKINGLY CHANGED.
I wouldn't want OpenClaw anywhere near a business I was running, even if I was all aboard the LLM hype train. That codebase is a nightmare. Just take a look at the hundred-plus pages of bugs on the Github repo.
The biggest feedback we collected was that any tasks they assigned to the Claw systems would turn into tangled messes often requiring significant time investment to understand, and mostly ending in the team scraping the code changes over quality concerns. The team really struggled to find anything these Claw systems could be tasked with that wouldnt end in poor results, So we ended up scraping the idea entirely. I think it will be quite a few more years until these types of systems are appropriate for the enterprise.
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