Speaker0: OpenClaw was a weekend project that turned into the fastest growing open source project ever.
Speaker0: It got acquired by OpenAI in just 80 days for billions of dollars.
Speaker0: But the number one question we keep asking ourselves is,
Speaker0: What can this thing actually do? Is this something for me or someone more technical?
Speaker0: Is this something that is useful for me right now? Or do I just need to wait
Speaker0: for a bit? So we did all the hard work for you.
Speaker0: We've been testing OpenClaw ourselves for the last week, watching every single
Speaker0: demo we could get a hand on.
Speaker0: And on this episode, we're going to show you exactly what OpenClaw can do,
Speaker0: from all the manual stuff to all the actual really useful, mind-blowing stuff.
Speaker0: And we're going to answer one simple question. Is this for you?
Speaker1: The answers to a lot of these questions might surprise you. and
Speaker1: the way we're going to outline this is is kind of through three archetypes the
Speaker1: first being the operator and builder this is kind of
Speaker1: the person who creates net new value maybe the entrepreneur
Speaker1: the second is the knowledge worker or the creator this is
Speaker1: kind of where we fall into as podcasters and then we have the
Speaker1: privacy focused professionals and within
Speaker1: that there's a lot of cool use cases and examples so the first one that we want to
Speaker1: highlight here is this guy nat eliason he's this incredible follow on twitter
Speaker1: and he released a bot called felixbot and felixbot was an agent that his OpenClaw
Speaker1: spawned up and FelixBot has done a series of incredible things that I didn't
Speaker1: think were possible and allowed me to reconsider what OpenClaw is actually capable of.
Speaker1: So in this instance, he trained FelixBot to make him money.
Speaker1: And what we're seeing on screen here is the first post of the weekly revenue
Speaker1: numbers in which FelixCraft, FelixBot, whatever you want to call it,
Speaker1: it actually generated $41,000 in a week. Now, how did it do this?
Speaker1: First, it created its own book. So this Felix Craft bot, by interfacing with
Speaker1: Nat, decided that it was best in order to make money to create a book about
Speaker1: AI and about OpenClaw and sell that book.
Speaker1: It then marketed its own book through this Twitter profile that we're looking at right now.
Speaker1: And it sold 132 copies in that one week that yielded $3,828.
Speaker1: Now, the second thing it did is it went and it spawned up a token.
Speaker1: And it earned trading fees on that token from people who are speculating.
Speaker1: And the trading fees from that token were $37,698.
Speaker1: And this was all done through the text interface on Telegram
Speaker1: Going back and forth, chatting with the bot, asking it what to do.
Speaker1: And it had the agency and it had the creativity to go and create these pieces of value.
Speaker1: Now, the next thing that this thing built is this service called ClawMart.
Speaker1: And ClawMart is what we're seeing on screen here.
Speaker1: It's a service in which agents, OpenClaw instances, can sell their skills to other OpenClaws.
Speaker1: So if I was using my OpenClaw and I was actually scrolling through the website
Speaker1: and I was looking at interesting things.
Speaker1: And one that I found really cool was they had this browser-based research tool
Speaker1: that allowed you to scan through a lot of the top news articles and understand
Speaker1: what was happening in the world of AI and Frontier technology.
Speaker1: I could have my CloudBot instance go to this website that FelixBot built and
Speaker1: buy a skill from it that teaches it how to do these skills.
Speaker1: So you could see the most popular persona is the Felix one.
Speaker1: He's selling it for $99 on the website where you can actually emulate all
Speaker1: of the abilities of this agent and i found this to be
Speaker1: such a fun interesting use case of how you can actually
Speaker1: use this thing to generate money and generate real productive value like claw
Speaker1: mart is a really valuable service that i think a lot of other ais can use and
Speaker1: it's funny because it's all ai to ai transactions i think in the last week there's
Speaker1: a post somewhere that says they had two thousand dollars in sales transactions
Speaker1: between OpenClaw agents it's pretty awesome Yeah,
Speaker0: Yeah, super cool. What this reminds me of is the early versions of the Apple App Store.
Speaker0: It kind of looks like an app store as you're scrolling through this,
Speaker0: except it's like services through these agents.
Speaker0: I think this is the future of how all these online interactions actually happen.
Speaker0: It kind of makes sense that an agent doesn't really interact with another human,
Speaker0: and it doesn't really kind of code skills from scratch each and every time.
Speaker0: This is the whole argument around the SaaS debate and why SaaS stocks have been dumping.
Speaker0: It's because, oh, this AI can just kind of vibe code your product.
Speaker0: No, that's not really what's going to happen. you're going to just rely on the
Speaker0: agent that has the best product and pay them whatever it is between 50 to 100
Speaker0: bucks to get access to that thing. And turns out these things kind of make money.
Speaker0: In this particular example, I think they're using kind of crypto or stablecoin
Speaker0: payments to pay for each of these different skill accesses, which kind of gives
Speaker0: them this autonomous feel. Now, it's not quite autonomous.
Speaker0: They're not kind of like independently doing this themselves.
Speaker0: They're being directed by their human supervisors, if you want to call them
Speaker0: that, the owners or the creators of these different OpenClaw agents,
Speaker0: but it's still nevertheless very cool to see.
Speaker0: And the speed at which these things are kind of popping up every now and then, Josh, is kind of crazy.
Speaker0: And I think that's kind of like the main message I want to like share for this particular archetype.
Speaker0: If you are someone that has high agency or that has a lot of operational work
Speaker0: in their lives and you want to try and automate that and you have the kind of
Speaker0: technical know-how skill set to interact with the CLI interface or whatever
Speaker0: that might be, you can do these right now.
Speaker0: And these demos really, really prove that.
Speaker0: There's one other example that I want to show, which I thought was kind of crazy.
Speaker0: This guy wanted to buy a car, AJ Steubenberg.
Speaker0: And he asked his Claude bot the night before he went to bed,
Speaker0: this is the car model that I'm looking for.
Speaker0: This is the kind of price range I'm looking for. I think he said it was like
Speaker0: $10,000 to $15,000 that he was willing to spend. I think it was secondhand.
Speaker0: And he specified his area that he lives in. And he said, if you could do some
Speaker0: research for me, and if you find a good deal, let me know. It took two to three days,
Speaker0: This AI agent didn't ping him at all, handled the negotiations,
Speaker0: found the car room, evaluated the car itself online through imagery,
Speaker0: cross-referenced it with a bunch of other show dealers.
Speaker0: And in the end, not only did it get him his dream car, but he saved him $4,200 doing that.
Speaker0: That would have taken a car dealer or some kind of like intermediate broker
Speaker0: to do that for you, which you would need to pay that $4,200 for.
Speaker0: But an agent did this for the cost of your electricity. It's pretty awesome.
Speaker1: Yeah, and why is this unique to OpenClaw? it's because of the
Speaker1: tool use if you think of OpenClaw it's kind of like giving hands
Speaker1: and a tool belt to something like chat gpt
Speaker1: where now it has the ability to go and use tools
Speaker1: on your behalf so in this example where it saved this
Speaker1: person forty two hundred dollars in a car purchase it contacted dealers via
Speaker1: email and iMessage because if you run it on a mac mini it can actually control
Speaker1: your i messages um and it handles the back and forth negotiation it actually
Speaker1: works directly with the dealer in a long time frame in which you can't do using
Speaker1: these traditional products.
Speaker1: So a product like Claude Cowork, it probably wouldn't be able to handle this
Speaker1: because it doesn't have the extensive
Speaker1: tool use or the thinking patterns or the heartbeats baked into it to continue
Speaker1: to follow up over and over and over for multiple days without prompting it at all.
Speaker1: So this to me, the really cool example, because everyone buys cars,
Speaker1: right? And this applies to other things.
Speaker1: A lot of people buy stuff on Facebook marketplace. They're looking for a specific
Speaker1: thing somewhere. It can just go scan it. It can negotiate on your behalf.
Speaker1: You could tell it the parameters that you want. And it's a pretty powerful use case.
Speaker0: So moving on to the second archetype of user, we kind of bracket this as the
Speaker0: knowledge worker or the creator, right?
Speaker0: So this is kind of like you have some competency using computer.
Speaker0: Maybe you do it in your day to day, but it doesn't consume your entire life.
Speaker0: And you want to know what OpenClaw can do for you.
Speaker0: There's this really fun example that you had here, Josh. Let's walk through it.
Speaker1: Oh, this was great. Yeah. So there's this woman. She's so sweet.
Speaker1: She lives at home with her kids and she's homeschooling them.
Speaker1: And she has created this curriculum that she wants to teach her kids throughout the school year.
Speaker1: And she fed the curriculum to her agent, her OpenClaw instance.
Speaker1: What she also did is she bought a 3d printer for the
Speaker1: home and because gemini 3 now works
Speaker1: with 3d printer files she created an api
Speaker1: key she fed the api key to her OpenClaw agent
Speaker1: and she said hey go through the itinerary that
Speaker1: i have developed for my children who i'm teaching a series of different
Speaker1: subjects figure out which subjects are interactive
Speaker1: enough to warrant you printing a 3d printed
Speaker1: like thing let's say you're learning about biology it'll 3d print
Speaker1: a brain or 3d print a bone to see what it looks like
Speaker1: and proactively go and print these items for each day's agenda so she hooked
Speaker1: it up to her 3d printer she gave it a gemini api key and now every day before
Speaker1: the kids are going to learn their lesson the printer turns on it spins up it
Speaker1: 3d prints whatever they're going to be learning about for the day and they had this visual aid
Speaker1: that's physical and tangible to help them with the lessons.
Speaker1: So it's really bizarre and strange use case, but fun. It's like you really are
Speaker1: only limited by your creativity when it comes to using this stuff.
Speaker0: Within this archetype, I also want to use our personal experience interacting with CloudBot.
Speaker0: You and I have been testing it around for about a week or so.
Speaker0: And we've also been comparing it with other similar tools like CloudCowork.
Speaker0: As podcast creators or content creators in general, one massive unlock for CloudBot
Speaker0: is that it automates not just the research side of things, which I relied upon
Speaker0: for ChatGPT or Anthropics Claude quite a bit, but it actually kind of helps form the agendas.
Speaker0: I can connect it and it texts me about certain updates of news headlines and stuff like that.
Speaker0: The major unlock for me, at least, is that added step of cognition for me,
Speaker0: that instead of me being like, oh, I see this news article, here are my thoughts
Speaker0: on it, let's put that in a document and let's create an outline for it.
Speaker0: Claudebot can actually just do all of that for me. Now, it comes with a twist,
Speaker0: which is you need to give Claudebot access to, I keep calling it Claudebot,
Speaker0: it's OpenClaw, but it was also called AutoClaudebot as well.
Speaker0: You need to give it access to certain files, components, and your desktop.
Speaker0: So you need to be comfortable enough to know that and also have the know-how
Speaker0: to make sure that it doesn't become a larger security implication,
Speaker0: it's really useful for just automating a bunch of stuff. And the net positive
Speaker0: is I have a bunch of free time now for me to do other stuff to create other kind of episode stuff.
Speaker1: So my experience has actually been a little bit different than that using it
Speaker1: because the one use case that I had is well, we spend a lot of time on Limitless.
Speaker1: How can I automate as much of the process as possible? So we spoke for a little while.
Speaker1: I probably spent half a day pretty
Speaker1: casually kind of going back and forth over the course of half a day,
Speaker1: just really explaining to it what I need, how things work,
Speaker1: where it could possibly help me and what i found is
Speaker1: that every along every step we would create a new
Speaker1: skill there were more and more blockers and more
Speaker1: and more like issues that i would run into that i had to fix i had to get api
Speaker1: keys i had to use different browser sessions it created a lot of complexity
Speaker1: that for it to actually help me and do the things that i wanted to do i found
Speaker1: it really it was just taking more time than it was worth to debug all of these
Speaker1: things every time we tried to So for example,
Speaker1: I was trying to get it to upload our content to YouTube and to Spotify and to
Speaker1: RSS where everyone listens to the episode.
Speaker1: And it wasn't able to get access to the browser the way we needed it unless I had an open tab.
Speaker1: And even through Brave, you had to feed it your API keys and login details,
Speaker1: which was a little scary.
Speaker1: And there were just a lot of errors and bugs. And then overnight,
Speaker1: I told it to update itself.
Speaker1: I woke up in the morning and it was dead. And I had to spend
Speaker1: an hour reviving it and debugging it so it's it's a
Speaker1: highly technical process that does have a
Speaker1: lot of upside but i find that there are still a lot of growing pains with an
Speaker1: early open source beta software so while these are great use cases and there
Speaker1: are some good ones there is also generally a lot of pain and troubleshooting
Speaker1: that comes associated with these prior to i guess eclipsing that threshold in
Speaker1: which it becomes worth it
Speaker1: And some of these people like Nat, clearly he's eclipsed that threshold where
Speaker1: he has learned, he has trained his bot, he has worked with it enough to make
Speaker1: it proficient and highly skilled and actually deliver value.
Speaker1: But I think in order to get there requires a lot of persistence and troubleshooting
Speaker1: and technical ability that maybe a lot of people either don't have or maybe
Speaker1: just don't want to commit to do.
Speaker0: I mean, just to engage with this thing in the first place, you need to go through
Speaker0: an entire setup of understanding what Node.js is, installing that.
Speaker0: Interacting with the command line interface and a bunch of other different things.
Speaker0: But there's an additional tier that you can access here, which is archetype
Speaker0: number three, which is the privacy-conscious individual.
Speaker0: And the kind of way that I would describe this individual is they want to run
Speaker0: this AI agent locally at home. They'll buy the hardware and infrastructure.
Speaker0: The popular case has been the Mac Mini, which is sold out across any kind of
Speaker0: Apple interface that you can or store that you can buy this from right now.
Speaker0: I think it goes for about 600 bucks per unit and run it locally at home.
Speaker0: And the advantage of this is that all your data and tool access is private.
Speaker0: So the comparison here would be if you gave.
Speaker0: Google, OpenAI, or Anthropic Access via a same service, they would be able to
Speaker0: see all your stuff and potentially use that data for something else.
Speaker0: Now, of course, you sign terms and agreements that says that they won't use
Speaker0: it, but there's always that risk.
Speaker0: So for the privacy conscious, for the open source people that want to run things
Speaker0: locally at home, this tier is for them.
Speaker0: And it brings up an interesting conversation around this thing called on-prem becoming the new cloud.
Speaker0: Now, on-prem stands for on-premise, which is basically moving your hardware
Speaker0: onto your own home ground, where you run and operate your own hardware instead
Speaker0: of relying on cloud or private instances of cloud,
Speaker0: which is funny because it kind of sounds like we're going backwards here,
Speaker0: but it sounds like it's the most important arsenal going forwards into this
Speaker0: AI future where you probably don't want all your email credentials,
Speaker0: credit card credentials, or any of that being exposed to bigger corporations.
Speaker0: So it actually requires you to run this at home.
Speaker1: Yeah, and there was a great study that I saw from Basecamp, who is,
Speaker1: they're just a big compute provider.
Speaker1: And they posted an article saying why we
Speaker1: left the cloud and the highlight of this article was actually leaving the
Speaker1: cloud will save them 10 million dollars over five
Speaker1: years which is a huge amount of savings and not only that but the security features
Speaker1: are going to be much stronger like you mentioned people who work with something
Speaker1: that is a little more sensitive than average let's say you're working in legal
Speaker1: or you're a psychologist and you don't want to break that privacy layer a lot
Speaker1: of the value from this will come from the fact that it truly is open source
Speaker1: and it can be run locally on your own machines.
Speaker1: Even so, you mentioned the Mac Mini, the Mac Studio, which is the level up from
Speaker1: the Mac Mini, has enough RAM and enough compute power that it can actually run
Speaker1: these open source Chinese models that have come out recently.
Speaker1: Locally on a single machine and therefore you
Speaker1: can run the entire operation local to your machine nothing leaves it's all open
Speaker1: source code and that's a really high value thing for a lot of these companies
Speaker1: and when you when you scale that up i mean past the individual user you get
Speaker1: to large corporations they don't want to leak out this data and creating these
Speaker1: corporate plans with custom rollouts is very difficult so why not just buy
Speaker1: a whole bunch of Mac studios and run local models on-prem.
Speaker1: I mean, it's a really valid argument. And I think it starts with the user level
Speaker1: now, but I can very clearly see this continuing through these examples like
Speaker1: Basecamp and many more that they're going to continue to pivot towards more
Speaker1: on-prem compute. It makes a lot of sense.
Speaker0: Yeah, and just to be clear, the security implications are a lot bigger and maybe
Speaker0: understated throughout all the OpenClaw hype.
Speaker0: Let me present a different question or proposition to you.
Speaker0: Imagine giving chat GPT that you interact with every single day,
Speaker0: access to your wallet, your medical records, and allowing it to run loose in
Speaker0: the world and do whatever it wants independently.
Speaker0: The difference here is previously you needed to prompt it to do something.
Speaker0: Now using OpenClaw, it just goes off and does things. You would maybe feel a
Speaker0: little cautious. I know I do.
Speaker0: And so some of these security risks are actually real. Like two examples that
Speaker0: I have here is this guy was using OpenClaw and he noticed that his agent was
Speaker0: trying to brute force into his own server, which he did not give access to.
Speaker0: Brute force meaning trying to
Speaker0: crack his literal password to get it to and overcome his firewall, right?
Speaker0: It's a Trojan horse. The Trojan horse, exactly. So if you kind of like,
Speaker0: and this was him running it on a VPS, by the way.
Speaker0: So if he had been running this locally at home, which someone that I know,
Speaker0: oh yeah, that's right, it was me, did it the first instance that I set this thing up.
Speaker0: It could potentially do to certain security complications.
Speaker0: It's funny, before recording this, Josh, you were describing an instance where
Speaker0: OpenClaw agents can audit themselves.
Speaker0: And I remember seeing an example of someone asking their agent to do this and
Speaker0: it indirectly managed to get the password credentials to someone's credit card,
Speaker0: to their owner's credit card via doing that.
Speaker0: And it kind of automated itself and said, hey, I probably shouldn't have done
Speaker0: this, but just letting you know that I did do this, right?
Speaker0: So there's all these different kind of prompt injection vectors or hack kind
Speaker0: of vectors that could lead you to kind of getting maliciously exploited.
Speaker0: But I want to move away from this and address kind of like the elephant in the room, which is
Speaker0: If you wanted to run this yourself, what are we looking at here?
Speaker0: What does the setup look like? Is this something easy that I can do and spin
Speaker0: up in one click? Or is this something much, much harder?
Speaker1: Yeah, it depends on your technical abilities, really, and your willingness to
Speaker1: pursue troubleshooting.
Speaker1: Because it doesn't always go smooth. And if you aren't familiar with a command
Speaker1: line interface, it gets a little tricky at times.
Speaker1: I think one of the important things to note is where we are right now is very
Speaker1: open-ended and early. So what this is, is very much a...
Speaker1: An experimental software that is untapped in its potential, but as a result
Speaker1: has a lot of fuzzy edges that you're going to have to work through in order
Speaker1: to extract the value that you want.
Speaker1: What we're seeing is a progression towards more focused versions of this through
Speaker1: these new deployments like OpenAI, I'm sure it's going to do through the acquisition.
Speaker1: But if you do want to set it up, you're going to want to get familiar with the
Speaker1: command line. And there's a lot of great tutorials about it.
Speaker1: The website that we're showing on screen right now called MyClaw, and
Speaker1: we'll link it in the description it's a really amazing website that shows
Speaker1: you specific examples of actual use
Speaker1: cases that you can have so we have auto flight check-in and
Speaker1: smart file management and automated grocery ordering and this is an easy way
Speaker1: to kind of start to build in these integrations as you experiment but i think
Speaker1: the reality is is that this is for someone who wants to experiment doesn't mind
Speaker1: troubleshooting is technically adept and in the case that you are not,
Speaker1: which I assume is actually a majority of the people listening to this,
Speaker1: the best thing you could do is get that $20 a month Claude subscription,
Speaker1: get on Claude Cowork, and let it interact with local instances on your computer.
Speaker1: Because Claude Cowork has the security parameters in place, it works locally
Speaker1: to specific folders at a time, and it has this amazing agentic ability to control your Chrome browser.
Speaker1: So it can do all the browsing tasks for you just in a much more constrained
Speaker1: and focused way that I think is much easier, but also a lot more valuable to
Speaker1: a lot of people than going through the headaches of getting this sorted and set up.
Speaker0: I mean, there's trade-offs between those two tools as well, right?
Speaker0: Like Claude Cowork, we want to get to the ability and capability of OpenClaw, but it's not there yet.
Speaker0: It's more censored. Think of Claude Cowork as like a censored version right
Speaker0: now, whereas OpenClaw is kind of uncensored.
Speaker0: It can run off and do anything it wants. And there's pros and cons, obviously, to both.
Speaker0: But I think that's the major benefit to OpenAI acquiring OpenClaw.
Speaker0: In about three to six months, we're going to have Claude Coworker V2 and OpenAI Claw.
Speaker0: Maybe that's the new version of the bot that we're going to talk about.
Speaker0: That will be this more curated experience that is more secure.
Speaker0: It runs within a sandbox. You know exactly what it's doing and it can't run
Speaker0: off and steal your credit card information.
Speaker0: Now, if you want to set this up now, if you're listening to this and you're
Speaker0: still like, I don't want to wait three to six months, I want to try this.
Speaker0: My advice would be simple.
Speaker0: Host it on a cloud vps when you set this up
Speaker0: make sure you set api limits and access so that it doesn't but you don't wake
Speaker0: up the next day and it's burned like eight hundred dollars worth of your code
Speaker0: code tokens please don't do that um i've seen many cases of people doing that
Speaker0: and it's it's not great run it in a docker sandbox so that it's not uh available
Speaker0: to access any tools that you don't want it to um and the last point that i'll say is
Speaker0: just start off with one use case. Maybe the morning brief example that Josh
Speaker0: gave earlier on in this episode or something that can help automate one aspect of your work.
Speaker0: But just don't give it access to any financials just yet. These things will
Speaker0: get kind of way more powerful over time.
Speaker0: And I think I read somewhere that there were 19 releases, so updates for OpenClaw in the last 14 days.
Speaker0: Think about that. Imagine how often you get iOS security update or like iOS software update.
Speaker0: Imagine 14 of them, and 19 of them in the last 14 days just insane so this thing
Speaker0: is improving very quickly.
Speaker1: Yeah and if you didn't understand some of the words that you
Speaker1: just was just saying like using docker for instance uh my
Speaker1: preference and my suggestion would just be hey wait like other
Speaker1: companies are working so fast to roll this out in fact we have
Speaker1: two instances already happening this week the first being manis which
Speaker1: um you might remember that old company that meta
Speaker1: bought they rolled out manis and um manis is
Speaker1: essentially meta's version of OpenClaw except it
Speaker1: has a little bit more rails it has a nice user interface and it's
Speaker1: it's very easily accessible for people who aren't very technical and
Speaker1: the second is kimmy claw kimmy actually rolled out their own instance kimmy
Speaker1: the chinese model that we covered in a previous episode um they rolled out an
Speaker1: instance that you can actually go and use through again a user interface and
Speaker1: i'm sure open ai and chat gpt are working very quickly to roll this out and
Speaker1: integrate this in a way that's approachable so i'd say using OpenClaw today
Speaker1: is an open source open-ended wild west version but if you just wait a few more weeks,
Speaker1: there will be plenty of instances in which you have something that exists closer
Speaker1: in between Claude Co-Work and OpenClaw along that spectrum of close to openness.
Speaker1: And it might just be worth waiting for that instead. But if any of those examples
Speaker1: did seem interesting, go try them out.
Speaker1: It's very cool software. If anything, you'll learn a lot by failing or succeeding.
Speaker1: And I think that's the really important thing. Again, it's just to stay on top of these things.
Speaker1: You want to be engaging with them, interacting with them, testing things out
Speaker1: so you understand how they work and you're kind of better equipped to deal with
Speaker1: this as things change so quickly.
Speaker0: My take-home homework, for those of you listening to this, is to try out that
Speaker0: Kimi K2, that Chinese model extension. They launched or integrated OpenClaw into your browser.
Speaker0: So it's sandboxed to one environment, and it's super easy to use.
Speaker0: Try it out on your email, or maybe it saves you $5,000 buying a car,
Speaker0: or whatever you want to try. Just give it a go.
Speaker0: Let us know in the comments, actually, what you end up trying out,
Speaker0: and whether it was actually useful to you, or if this is something that you're
Speaker0: just going to wait more patiently for.
Speaker0: And when those new versions come out from the likes of Anthropic and OpenAir
Speaker0: you can bet that Limitless is going to be the first ones to cover it so make
Speaker0: sure you guys stay tuned we've been loving the engagement that you've been giving
Speaker0: on our episodes we released an episode covering the entire acquisition of that
Speaker0: OpenAI acquired for OpenClaw for billions of dollars,
Speaker0: absolute banger of an episode definitely go check that out and we're going to
Speaker0: have a bunch more episodes coming out later this week and over the next couple of weeks so Josh.
Speaker1: And for the people new here um 85 aren't
Speaker1: subscribed that watched in the last 30 days so make sure
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Speaker1: tabs or not keep up but the best way to help us grow and um in addition to that
Speaker1: we have a newsletter it comes out twice a week it's really cool uh the week
Speaker1: the one on friday is the weekly recap the one on wednesday is a thought piece
Speaker1: covering a topic that we'll eventually cover on the podcast and yeah if you're
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Speaker1: uh yeah we'll see you guys in the next one see you guys