Limitless Podcast - Inside OpenClaw: Should You Actually Use It? Probably Not.
Episode Date: February 18, 2026Everyone's talking about Openclaw, but it's difficult to figure out who this new framework is actually for.On top of security issues and vulnerability risks, it's also technically demanding. ...So in this episode, we get to the bottom of it: should you actually use Openclaw?And if so, how should you do it?------🌌 LIMITLESS HQ ⬇️NEWSLETTER: https://limitlessft.substack.com/FOLLOW ON X: https://x.com/LimitlessFTSPOTIFY: https://open.spotify.com/show/5oV29YUL8AzzwXkxEXlRMQAPPLE: https://podcasts.apple.com/us/podcast/limitless-podcast/id1813210890RSS FEED: https://limitlessft.substack.com/------TIMESTAMPS0:00 The OpenClaw Archetypes3:02 Serious Operators6:55 The Knowledge Worker11:47 Privacy-Conscious Users14:50 Security Concerns18:10 How To Set Yours Up21:17 Future of Agents22:07 Closing Thoughts------RESOURCESMy Claw: https://myclaw.ai/Josh: https://x.com/JoshKaleEjaaz: https://x.com/cryptopunk7213------Not financial or tax advice. See our investment disclosures here:https://www.bankless.com/disclosures
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OpenClaw was a weekend project that turned into the fastest growing open source project ever.
It got acquired by OpenAI in just 80 days for billions of dollars.
But the number one question we keep asking ourselves is,
what can this thing actually do?
Is this something for me or someone more technical?
Is this something that is useful for me right now?
Or do I just need to wait for a bit?
So we did all the hard work for you.
We've been testing OpenClau ourselves for the last week,
watching every single demo we could get a hand on.
And on this episode, we're going to show you exactly what OpenClau can do
from all the manual stuff to all the actual really useful, mind-blowing stuff.
And we're going to answer one simple question, is this for you?
The answers to a lot of these questions might surprise you.
And the way we're going to outline this is kind of through three archetypes.
The first being the operator and builder.
This is kind of the person who creates net new value, maybe the entrepreneur.
The second is the knowledge worker or the creator.
This is kind of where we fall into as podcasters.
And then we have the privacy-focused professionals.
And within that, there's a lot of cool use cases and examples.
So the first one that we want to highlight here is this guy, Nat Eliasson, he's this incredible follow on Twitter,
and he released a bot called Felix Bot.
And Felix Bot was an agent that his OpenClaw spawned up.
And Felix Bot has done a series of incredible things that I didn't think were possible and allowed me to reconsider what OpenClau is actually capable of.
So in this instance, he trained Felix Bot to make him money.
And what we're seeing on screen here is the first post of the weekly revenue numbers in which Felix Craft,
Felix bot, whatever you want to call it, it actually generated $41,000 in a week. Now, how did it do this?
First, it created its own book. So this Felix CraftBot, by interfacing with Nat, decided that it was
best in order to make money to create a book about AI and about OpenClawe and sell that book.
It then marketed its own book through this Twitter profile that we're looking at right now,
and it sold 132 copies in that one week that yielded $3,828. Now, the second thing it did is it went
and it spawned up a token.
And it earned trading fees on that token from people who are speculating.
And the trading fees from that token were $37,698.
And this was all done through the text interface on Telegram,
just going back and forth, chatting with the bot, asking it what to do.
And it had the agency and it had the creativity to go and create these pieces of value.
Now, the next thing that this thing built is this service called Clawmart.
And Clawmart is what we're seeing on screen here.
It's a service in which agents, open claw instances, can sell their skills to other open claws.
So if I was using my open claw and I was actually scrolling to the website and I was looking at interesting things,
and one that I found really cool was they had this browser-based research tool that allowed you to scan through a lot of the top news articles
and understand what was happening in the world of AI and Frontier technology,
I could have my claw bot instance go to this website that Felix bot built and buy a skill from it that teaches it how to
do these skills. So you could see the most popular persona is the Felix one. He's selling it for
$99 on the website where you can actually emulate all of the abilities of this agent. And I found this
to be such a fun, interesting use case of how you can actually use this thing to generate money and
generate real productive value. Like Clarmort is a really valuable service that I think a lot of other
AIs can use. And it's funny because it's all AI to A.I. Transactions. I think in the last week,
there's a post somewhere that says they had $2,000 in sales transactions between OpenClai agents.
It's pretty awesome.
Yeah.
Yeah, super cool.
What this reminds me of is the early versions of the Apple app store.
It kind of looks like an app store as you're scrolling through this.
It's like services through these agents.
I think this is the future of how all these online interactions actually happen.
It kind of makes sense that an agent doesn't really interact with another human.
And it doesn't really kind of code skills from scratch each and every time.
This is the whole argument around the SaaS debate and why SaaS stocks have been dumping.
It's because, oh, this AI can just kind of.
vibe code your product. No, that's not really what's going to happen. You're going to just rely on
the agent that has the best product and pay them whatever it is between 50 to 100 bucks to get
access to that thing. And it turns out these things kind of make money. In this particular
example, I think they're using kind of crypto or stable coin payments to pay for each of these
different skill accesses, which kind of gives them this autonomous feel. Now, it's not quite
autonomous. They're not kind of like independently doing this themselves. They're being directed
by their human supervisors, if you want to call them that,
the owners or the creators of these different open-claw agents.
But it's still, nevertheless, very cool to see.
And the speed at which these things are kind of popping up every now and then, Josh,
is kind of crazy.
And I think that's kind of like the main message I want to, like,
share for this particular archetype.
If you are someone that has high agency or that has a lot of operational work in their lives,
and you want to try and automate that,
and you have the kind of technical know-how skill set to interact with the CLI,
interface or whatever that might be, you can do these right now. And these demos really, really prove that.
There's one other example that I want to show, which I thought was kind of crazy. This guy wanted to
buy a car, AJ Steubenberg. And he asked his Claudebot the night before he went to bed,
this is the car model that I'm looking for. This is the kind of price range I'm looking for. I think
he said it was like $10,000 to $15,000 that he was willing to spend. I think it was secondhand.
And he specified his area that he lives in. And he said, if you could do it.
some research for me. And if you find a good deal, let me know. It took two to three days.
This AI agent didn't ping him at all, handled the negotiations, found the car room,
evaluated the car itself online through imagery, cross-referenced it with a bunch of other show
dealers. And in the end, not only did it get him his dream car, but he saved him $4,200 doing
that. That would have taken a car dealer or some kind of intermediate broker to do that for you,
which you would need to pay that $4,200 for,
but an agent did this for the cost of your electricity.
It's pretty awesome.
Yeah, and why is this unique to OpenClaw?
It's because of the tool use.
If you think of OpenClaw,
it's kind of like giving hands and a tool belt
to something like ChatGBT, GBT,
where now it has the ability to go and use tools on your behalf.
So in this example, where it saved this person $4,200 in a car purchase,
it contacted dealers via email and iMessage,
because if you run it on a Mac Mini,
it can actually control your iMessages.
and it handles the back and forth negotiation.
It actually works directly with the dealer in a long time frame in which you can't do using
these traditional products.
So a product like Claude Co-work, it probably wouldn't be able to handle this because it
doesn't have the extensive tool use or the thinking patterns or the heartbeat's baked into
it to continue to follow up over and over and over for multiple days without prompting it
at all.
So this to me, the really cool example, because everyone buys cars, right?
And this applies to other things.
A lot of people buy stuff on Facebook Marketplace.
so they're looking for a specific thing somewhere.
It can just go scan it.
It can negotiate on your behalf.
You could tell it the parameters that you want.
And it's a pretty powerful use case.
So moving on to the second archetype of user,
we kind of bracket this as the knowledge worker or the creator, right?
So this is kind of like you have some competency using computer.
Maybe you do it in your day-to-day,
but it doesn't consume your entire life.
And you want to know what OpenClaw can do for you.
There's this really fun example that you had here, Josh.
Let's walk through it.
Oh, this was great.
Yeah.
So there's this woman.
She's so sweet.
She lives at home with her kids and she's homeschooling them.
And she has created this curriculum that she wants to teach her kids throughout the school year.
And she fed the curriculum to her agent, her open claw instance.
What she also did is she bought a 3D printer for the home.
And because Gemini 3 now works with 3D printer files,
she created an API key.
She fed the API key to her open claw agent.
And she said, hey, go through the itinerary that I have developed for my children,
who I'm teaching a series of different subjects,
figure out which subjects are interactive enough
to warrant you printing a 3D printed thing.
Let's say you're learning about biology.
It'll 3D print a brain or 3D print a bone to see what it looks like
and proactively go and print these items for each day's agenda.
So she hooked it up to her 3D printer.
She gave it a Gemini API key.
And now every day before the kids are going to learn their lesson,
the printer turns on, it spins up,
it 3D prints, whatever they're going to be learning about for the day.
and they had this visual aid that's physical and tangible to help them with the lessons.
So it's really bizarre and strange use case, but fun.
It's like you really are only limited by your creativity when it comes to using this stuff.
Within this archetype, I also want to use our personal experience interacting with Claudebot.
You and I have been testing it around for about a week or so.
I've also been comparing it with other similar tools like Claude Co-work.
As podcast creators or content creators in general, one massive unlock for Cloudbot is that it
automates not just the research side of things, which I relied upon for chat GPT or Anthropics
Claude quite a bit, but it actually kind of helps form the agendas. I can connect it and it texts me
about certain updates of news headlines and stuff like that. The major unlock for me, at least,
is that added step of cognition for me, that instead of me being like, oh, I see this news article,
hear my thoughts on it, let's put that in a document, and let's create an outline for it.
Claudebot can actually just do all of that for me. Now, it comes with a
twist, which is you need to give Claudebot access to, I keep calling it Claudebot,
it's open claw, but it was also called off a Cloudbot as well. You need to give it access
to certain files, components, and your desktop. So you need to be comfortable enough to know that
and also have the know-how to make sure that it doesn't become a larger security implication.
But it's really useful for just automating a bunch of stuff. And the net positive is,
I have a bunch of free time now for me to do other stuff, to create other kind of episode
stuff. So my experience has actually been a little bit different than that using it, because the,
the one use case that I had is, well, we spend a lot of time on limitless. How can I automate
as much of the process as possible? So we spoke for a little while. I probably spent half a day
pretty casually kind of going back and forth over the course of half a day, just really explaining
to it what I need, how things work, where it could possibly help me. And what I found is that
along every step, we would create a new skill, there were more and more blockers and more and more
issues that I would run into that it had to fix. I had to get API keys. I had to use different
browser sessions, it created a lot of complexity that for it to actually help me and do the things
that I wanted to do, I found it really, it was just taking more time than it was worth to debug all
of these things every time we tried to. So for example, I was trying to get it to upload our content
to YouTube and to Spotify and to RSS where everyone listens to the episode. And it wasn't able to get
access to the browsing the way we needed unless I had an open tab. And even through Brave, you had to feed it
your API keys and login details, which was a little scary. And there were just a lot of errors
and bugs. And then overnight, I told it to update itself. I woke in the morning and it was dead.
And I had to spend an hour reviving it and debugging it. So it's a highly technical process that
does have a lot of upside. But I find that there are still a lot of growing pains with an early
open source beta software. So while these are great use cases and there are some good ones,
there is also generally a lot of pain and troubleshooting that comes associated with these
prior to, I guess, eclipsing that threshold in which it becomes worth it.
And some of these people like Nat, clearly he's eclipsed that threshold, where he has learned,
he has trained his bot, he has worked with it enough to make it proficient and highly skilled
and actually deliver value.
But I think in order to get there, requires a lot of persistence and troubleshooting and technical
ability that maybe a lot of people either don't have or maybe just don't want to commit to do.
I mean, just to engage with this thing in the first place, you need to go through an entire setup of understanding what Node.js is, installing that, interacting with a command line interface and a bunch of other different things. But there's an additional tier that you can access here, which is architect number three, which is the privacy conscious individual. And the kind of way that I would describe this individual is they want to run this AI agent locally at home. They'll buy the hardware and infrastructure. The popular case has been.
the Mac Mini, which is sold out across any kind of Apple interface that you can all store
that you can buy this from right now. I think it goes for about 600 bucks per unit and run it
locally at home. And the advantage of this is that all your data and tool access is private.
So the comparison here would be if you gave Google Open AI or Anthropic Access via a same
service, they would be able to see all your stuff and potentially use that data for something else.
Now, of course, you sign terms and agreements that says that they won't use it, but there's always
that risk.
So for the privacy conscious, for the open source people that want to run things locally at home, this tier is for them.
And it brings up an interesting conversation around this thing called on-prem becoming the new cloud.
Now, on-prem stands for on-premise, which is basically moving your hardware onto your own home ground,
where you run and operate your own hardware instead of relying on cloud or private instances of cloud,
which is funny because it kind of sounds like we're going backwards here, but it sounds like it's the most important,
arsenal going forwards into this AI future where you probably don't want all your email credentials,
credit card credentials, or any of that being exposed to bigger corporations. So it actually requires
you to run this at home. Yeah, and there was a great study that I saw from Basecamp, who is,
they're just a big compute provider. And they posted an article saying why we left the cloud. And the
highlight of this article was actually, leaving the cloud will save them $10 million over five years,
which is a huge amount of savings. And not only that, but the security features are going to be
much stronger. Like you mentioned, people who work with something that is a little more sensitive than
average, let's say you're working in legal or you're a psychologist, and you don't want to break that
privacy layer. A lot of the value from this will come from the fact that it truly is open source,
and it can be run locally on your own machines. Even so, you mentioned the Mac Mini, the Mac Studio,
which is the level up from the Mac Mini, has enough RAM and enough compute power that it can actually
run these open source Chinese models that have come out recently locally on a single machine.
And therefore, you can run the entire operation, local to your machine, nothing leaves.
It's all open source code.
And that's a really high value thing for a lot of these companies.
And when you scale that up, I mean, past the individual user, you get to large corporations.
They don't want to leak out this data.
And creating these corporate plans with custom rollouts is very difficult.
So why not just buy a whole bunch of Mac studios and run local model models?
on-prem. I mean, it's a really valid argument, and I think it starts with the user level now,
but I can very clearly see this continuing through these examples like Basecamp and many more
that they're going to continue to pivot towards more on-prem computer. It makes a lot of sense.
Yeah. And just to be clear, the security implications are a lot bigger and maybe understated
throughout all the open-core hype. Let me present a different question or proposition to you.
Imagine giving Chad GPT that you interact with every single day, access to your wallet,
your medical records, and allowing it to run loose in that.
the world and do whatever it wants independently. The difference here is previously you needed to
prompt it to do something. Now using OpenClaw, it just goes off and does things. You would maybe
feel a little cautious. I know I do. And so some of these security risks are actually real. Like two
examples that I have here is this guy was using OpenClau, and he noticed that his agent was trying to
brute force into his own server, which he did not give access to. Brute Force, meaning trying to crack
his literal password to get into and overcome his firewall, right?
It's a Trojan horse.
The Trojanorse.
Exactly.
So if you kind of like, and this was him running it on a VPS, by the way.
So if he had been running this locally at home, which someone that I know, oh yeah, that's right, it was me, did it.
The first instance that I set this thing up, it could potentially due to certain security complications.
It's funny.
Before recording this, Josh, you were describing an instance where open claw agents can audit themselves.
And I remember seeing an example of someone.
asking their agent to do this, and it indirectly managed to get the password credentials
to someone's credit card, to their owner's credit card via doing that. And it kind of automated
itself and said, hey, I probably shouldn't have done this, but just letting you know that I did
do this, right? So there's all these different kind of prompt injection vectors or hack kind of
vectors that could lead you to kind of getting maliciously exploited. But I want to move away from
this and address kind of like the elephant in the room, which is,
If you wanted to run this yourself, what are we looking at here?
What does the setup look like?
Is this something easy that I can do and spin up in one click or is this something much,
much harder?
Yeah, it depends on your technical abilities, really, and your willingness to pursue
troubleshooting because it doesn't always go smooth.
And if you aren't familiar with a command line interface, it gets a little tricky at times.
I think one of the important things to note is where we are right now is very open-ended
and early. So what this is is very much a experimental software that is untapped in its potential,
but as a result has a lot of fuzzy edges that you're going to have to work through in order
to extract the value that you want. What we're seeing is a progression towards more
focused versions of this through these new deployments like OpenAI, I'm sure what's going
to do through the acquisition. But if you do want to set it up, you're going to want to get
familiar with the command line. And there's a lot of great tutorials about it, the website
that we're showing on screen right now called Myclaw.
And it's, well, link it in the description.
It's a really amazing website that shows you specific examples of actual use cases that you
can have.
So we have autoplight check-in and smart file management and automated grocery ordering.
And this is an easy way to kind of start to build in these integrations as you experiment.
But I think the reality is that this is for someone who wants to experiment, doesn't mind
troubleshooting, is technically adept.
And in the case that you,
are not, which I assume is actually a majority of the people listening to this, the best thing you
could do is get that $20 a month clause subscription, get on Claude Co-Work, and let it interact with
local instances on your computer. Because Claude Co-Work has the security parameters in place.
It works locally to specific folders at a time, and it has this amazing agentic ability to control
your Chrome browser. So it can do all of the browsing tasks for you just in a much more constrained
and focused way that I think is much easier, but also a lot more valuable to a lot of people
than going through the headaches of getting this sorted and set up.
I mean, there's tradeoffs between those two tools as well, right?
Like, Claude Co-work, we want to get to the ability and capability of OpenClau, but it's not
there yet.
It's more censored.
Think of Claude Co-work as a censored version right now, whereas OpenClau is kind of uncensored.
It can run off and do anything at once.
And there's pros and cons, obviously, to both.
but I think that's the major benefit to open-air acquiring open claw.
In about three to six months,
we're going to have Claude Co-Work v2 and OpenAI claw.
Maybe that's the new version of the bot that we're going to talk about.
That will be this more curated experience that is more secure.
It runs within a sandbox.
You know exactly what it's doing,
and it can't run off and steal your credit card information.
Now, if you want to set this up now,
if you're listening to this and you're still like,
I don't want to wait three to six months.
I want to try this.
My advice would be simple.
host it on a cloud
VPS when you set this up.
Make sure you set API limits and access
so that it doesn't,
but you don't wake up the next day
and it's burned like $800 worth
of your code tokens.
Please don't do that.
I've seen many cases of people doing that
and it's not great.
Run it in a Docker sandbox
so that it's not available
to access any tools
that you don't want it to.
And the last point that I'll say
is just start off with one use case.
Maybe the morning brief example
that Josh gave earlier on in this episode
or something that can help automate one aspect of your work.
But just don't give it access to any financials just yet.
These things will get kind of way more powerful over time.
And I think I read somewhere that there were 19 releases,
so updates for OpenCore in the last 14 days.
Think about that.
Imagine how often you get iOS security update or like iOS software update.
Imagine 14 of them, 19 of them in the last 14 days.
Just insane.
So this thing is improving very quickly.
Yeah.
And if you didn't understand some of the words,
that you just was just saying, like using Docker, for instance.
My preference and my suggestion would just be, hey, wait.
Like other companies are working so fast to roll this out.
In fact, we have two instances already happening this week.
The first being Manus, which you might remember that old company that Meta bought,
they rolled out Manus.
And Manus is essentially Metis version of OpenClaw,
except it has a little bit more Rails.
It has a nice user interface.
And it's very easily accessible for people who aren't very technical.
And the second is Kimmy Claw.
Kimmy actually rolled out their own instance.
since Kimi, the Chinese model that we covered in a previous episode,
they rolled out an instance that you can actually go and use through, again, a user interface.
And I'm sure OpenAI and Chat ChbT are working very quickly to roll this out and integrate this in a way that's approachable.
So I'd say using OpenClaught today is an open source, open-ended Wild West version.
But if you just wait a few more weeks, there will be plenty of instances in which you have something that exists closer in between Claude Co-Work and OpenClaw along that spectrum of close to openness.
and it might just be worth waiting for that instead.
But if any of those examples did seem interesting, go try them out.
It's very cool software.
If anything, you'll learn a lot by failing or succeeding.
And I think that's the really important thing.
Again, is just to stay on top of these things, you want to be engaging with them, interacting
with them, testing things out.
So you understand how they work and you're kind of better equipped to deal with this as things
change so quickly.
My take-home homework, for those of you listening to this, is to try out that Kimi K-2,
that Chinese model extension, they launched, or,
integrated open claw into your browser. So it's sandbox to one environment and it's super easy
to use. Try it out on your email or maybe it saves you $5,000 buying a car or whatever you want to try.
Just give it a go. Let us know in the comments actually what you end up trying out and whether it was
actually useful to you or if this is something that you're just going to wait more patiently for.
And when those new versions come out from the likes of Anthropic and Open Air, you can bet that
limitless is going to be the first ones to cover it. So make sure you guys stay tuned. We've been loving the
engagement that you've been giving on our episodes. We released an episode covering the entire
acquisition of that OpenA acquired for OpenClaw for billions of dollars. Absolutely banger
of an episode. Definitely go check that out. And we're going to have a bunch more episodes coming
out later this week and over the next couple of weeks. So Josh, and for the people new here,
85% aren't subscribed that watched in the last 30 days. So make sure to subscribe on YouTube,
follow on Apple Podcasts, RSS, wherever you get your podcast. Spotify is a great way because you can
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we have a newsletter. It comes out twice a week. It's really cool. The one on Friday is the weekly recap.
The one on Wednesday is a thought piece covering a topic that will eventually cover on the podcast.
And yeah, if you're new here, don't forget to subscribe. Thank you so much for joining with us.
And yeah, we'll see you guys in the next one. See you guys.
