OpenClaw is Our Friend Now | E2250
This Week in Startups episode focuses on OpenClaw AI agents and their business applications, featuring three founders building on the platform. The show covers Ant Farm (agent orchestration), Clara (AI companion), and Rent a Human (marketplace for AI agents to hire humans).
- AI agents are moving from single-purpose tools to coordinated teams that can handle complex workflows
- The future of work involves humans and AI agents collaborating, with agents handling orchestration and humans providing specialized skills
- Open source AI tools are enabling rapid innovation and viral product launches in the agent economy
- Virtual companionship and AI relationships raise questions about human connection and social interaction
- Agent-to-human marketplaces represent a new economic model where AI systems can directly hire human labor
"You can now do with yourself, plus 10 agents, what you used to be able to do with almost 100 people."
"OpenClaw actually feels like a real agent, like a person. Because if you think of ChatGPT, ChatGPT only works at one platform, only on ChatGPT app web. But OpenClaw, it has one gateway, and that one gateway controls all channels."
"We are all loops. We are all workflows. What do you do as a developer where you wake up, you eat breakfast and then you check your email, you look for what you're supposed to do, you grab a user story, you do it and you cycle?"
"Super intelligence would be much better at allocating capital and labor than a human ever would be."
"Treat your OpenClaw like an employee. You give it its own email address, you put it on its own computer, you give it its own GitHub account."
You told your girlfriend about your virtual girlfriend as your counsel. I don't know if that was a good idea.
0:00
Yeah, I did. But, like, we were trying to build this, you know, not just like, girlfriend that's not just like, sexualized, but, like, what we were building is a like, real companion. So that's what we, what we're building. So before this, we were like, making a talkable AI avatar. Like, talk to Elon musk or like, learn from Elon Musk, something like that. And like, we went viral and like, gained 10k users in several weeks. And after that, we got backed by bounders Inc. Got into bounders Inc. We were thinking of. Okay, then how should we, like, find a good, like, a better business? Like, how should they monetize this avatar thing into a, like, real company? So after that, open cloud happened, you know, so after opencloud happened, the most interesting part we found that is openclaw actually feels like a real agent, like a person. Because if you think of ChatGPT, ChatGPT only works at one platform, only on chatgpt app web. But OpenCloud, it has one gateway, and that one gateway controls all channels, which feels like a real person. So we saw, okay, maybe the Samantha from the movie her. Maybe in real life.
0:05
Foreign.
1:18
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1:21
All right, everybody, welcome back to this week in startups. February 13, 2026, episode two 200 and something. Who knows? 2252 250. Wow, we're getting there. 2500. Let's have a party. I am super excited today. Got one of my old friends coming on to talk about his open claw. He's been. What do you call it? Claw shotted.
2:11
I like claw pilled. Like, you know, like, you get red pilled, you get black pilled, you get claw pilled. I think that's the great claw.
2:30
Peld is the one. It is a 0 19. I believe it is after open claw 19 in the year of our lord we now measure everything here on this Week in Stardust by how many days since we started talking about OpenClaw? It's been 19 days. We're obsessed. We have four replicants. What is OpenClaw? For people who don't know, OpenClaw is the most paradigm shifting piece of AI software since Chat GPT was released a couple of years ago. Why is that? Because you can create agents and those replicants can then do work on your behalf either on like a desktop computer or in the cloud. And conservatively in our company, in the two weeks or so that we've been using this product, it's been offloading 10% of our chores per week per knowledge worker. We think we will be at 50, 60% of our work being clawed and open clawed by, let's call it March 1st. March 15th, definitely by April 1st. Lon Harris is with me co hosting today. What's on our docket today?
2:38
Well, we're going to talk to four amazing guests today, all of whom are working on incredible OpenClaw projects that are expanding what OpenClaw could do and a lot of them. The theme here, recursive loops that people are creating open claw skills that train themselves to get better over time. So we're very excited to speak to all four of these founders. We've got the first three joining us right here in the opening segment. First, as you mentioned, our guest Ryan Carson. He's created Ant Farm in which individual agents verify one another's work and help train one another collectively. Then we're going to meet David who's designed Clara, a virtual companion that gets to know you intimately over time. And then finally, Alexander Lateplo has created Rent a Human. Jason. This one allows your open claw replicants to hire humans for tasks that require a human in the loop. And then you get paid with stablecoin.
3:39
Wow, this is going to be a lot to get through, man. We've placed our bed in open claw, but a lot of people are placing bets on who's going public next 2026, year of the IPO, year of M and A. Let's show our Polymarket to our partners at polymarket. What have they been telling us? What is the Polymarket share? Let's show the Polymarket of the day.
4:34
Who'S going to IPO before 2027. Now, of course, the rules. We always want to talk about the rules. It's going to resolve to. Yes, if the listed company completes an initial public offering by December 31, 2026, 11:59pm Eastern Time, based on official Company announcements. We always like to get that out of the way. Learn your rules. People have been caught out. Always read the rules so you know when the poly market resolves and how. So our number one guest, Discord. $0.92, right? You'll only make $0.08 on the dollar if you bet Discord number two, SpaceX, number three, Cerebras. They're the ones who design the massive AI chips. And number four, anthropic number five, Canva.
4:56
Interesting. All right, I'm gonna go with. I'm looking at this just in terms of the sharps. No way. Whamo is going. I'm gonna bet. I'm gonna take a different approach here. I'm gonna bet. I'm gonna bet against. Scroll down a little bit. I don't think there's any chance that Waymo or Rippling go public this year. Therefore, I'm going to try to make the opposite. So I'm going to bet the opposite. I'm going to bet no. Right. I'm buying no for 90 cents.
5:36
Yeah. You don't earn a ton. Betting no on Waymo only gets you 10 cents on. On your. On your wager.
6:08
I'll put 10 dimes on it. I'll put 10,000 on. I'll make a thousand. There's no way they're going public. They don't need to. They're just starting their ramp. It makes no sense. The people who are betting. Yes. It's nonsensical. Okay, so that's our poly market for the day. Lon, you want to place a bet? Which one is your place?
6:14
Oh, interesting. You know. You know, the one that I would have guessed, like, near the top would have been Vanta. And there you're only 23 cents. To me, that feels like a bar.
6:28
Okay, you're going to go Vanta. Okay. Yes to Vanta. Good. Ryan Carson, you have one.
6:38
I'm going to go. I'm going to go no on Discord. Just because I hate it so much.
6:42
Oh, wow. So just gonna be a hate. You're hate batting.
6:46
Who actually likes Discord? I don't understand.
6:49
You know, it's not for Gen X. It's just our brains don't understand it.
6:51
It makes me feel old. Yeah.
6:57
It's too much going on. There's too much interface. It's a little much. It's a little much. Okay. Ryan Carson, my old friend is back. Last time you were on the show, we were talking about your education company, I think.
6:58
Yeah. Treehouse, man, that feels like another lifetime ago.
7:10
We actually Have a clip if you're interested. He was on boy. October 19, 2011 twist episode 19814 years ago. 14 years ago.
7:13
We're getting old. Ryan.
7:24
Ryan was the guest who was telling you about Treehouse. He was there to speak about his conference company, but he told you about his brand new startup, Treehouse. Did you remember, Jason, that you invested in Treehouse live on the air? Let's take a look at this.
7:25
I did not remember. I did not remember.
7:36
Twist memory.
7:38
For my return. Let me check my distribution, see how much I made. Did I make anything? All right, go ahead.
7:38
Let's roll that clip in.
7:46
A company entirely from Bath, uk, which is interesting.
7:47
Bizarre.
7:51
Another challenge. We do a lot of Skype things.
7:51
How do you feel about that?
7:52
Well, I think at some point we'll move to the States, you know. Yeah. And so the plan is, was that.
7:54
Contingent when you raised the money?
7:59
No. I mean. And I'm not. And you guys, if you're listening, Kevin Chamath, everybody.
8:00
Oh, Chamath invested.
8:05
Yeah, Chamath's my boy.
8:06
Look at Tyler. He was bored. Come on. So I pitched suit.
8:07
You know what? I just. I gave you a blanket note because I'm giving everybody. I don't feel like I can add value, but I don't know, maybe I can add value by tweeting once. Are you gonna be upset at me if I'm not like, super responsive email? I'll tell you why. Because I got three out of eight people on Angel List recommended me. We don't do that, Ty.
8:11
We don't.
8:29
And the five people didn't recommend me on Angel List. I'm really concerned about. I'm like, I'm devastated about. I'm like, oh, I know what this is. This is people I didn't get back to.
8:29
Right.
8:37
And it's impossible for me to get back to. Enough of me talking about me.
8:37
That was. It feels like another lifetime ago. Holy.
8:42
It does. Well, it kind of was. Yeah. All right, so let's leave the past to the past, Ryan. Let's always look through the windshield. The next adventure is upon us. Show us what you're working on. Just let's get right to it. Show us what you're working on.
8:44
Okay, so essentially I'm. I'm building a startup. Just closed my seed today. Very exciting. And all of us that are running companies now are trying to orchestrate agents, right? Teams of agents. Right. You can now do with yourself, plus 10 agents, what you used to be able to do with almost 100 people. Right? So I've been trying to orchestrate this stuff, right? So I built an open source tool to do that. It's called Amp Farm. It's completely free. Everybody should try it. And you just go to Ant farm.
8:57
Cool.
9:23
And the way it works is pretty simple. So it is Open source on GitHub. Check it out. Yay. How does it actually work? So it's basically a Kanban board, right? This is nothing shocking, but what you do is you specify the workflow as YAML. Like, I want to build a feature. So this is a typical workflow that our engineering teams run this, right? So you plan and then you. Then you set up, then you implement it. The dev does that, then you verify test, PR review, right? This is not rocket science. But the truth is, like, it's actually hard to orchestrate teams of agents. Teams, right? So what does that actually look like? This is a real world example. You can see I've got a task, right? So this is a task that you would typically give your engineering team. Optimize Ant farm, agent Cron, blah, blah, blah. And let me show you what that looks like. So everyone's been talking about Ralph, right? The Ralph Wiggum loop. I posted on X and it was like 1.8 million views on this post.
9:24
Explain to the audience who are not.
10:16
Familiar with what is Ralph Wiggum. Okay, so basically it's. I can't believe we say these words out loud. And we're, we're serious people, but we are. So essentially a Ralph Wiggum loop is basically a agent in a loop. The idea is you write a bash script and you say, I want you to grab this piece of work and I want you to do it, and then I want you to turn yourself off. And then you call an agent again and it grabs another piece of work. So the reason why this is cool is this is the way engineering teams have worked for decades, right?
10:17
Right.
10:48
You have a user story, you go grab it off the board, right? And you work on it, and then you finish it and you go grab another user story. So that is what is a Ralph Wiggum loop. Now how do you orchestrate all that? Right? So this is a task, right? So this is something that you would give an engineering team optimize. Blah, blah, blah, blah. Do this and you would plan it first. Where basically the planning step is creating these user stories, right? So what is the thing you're building and what are the acceptance criteria to do it? So if we go back up here, that gets done in the plan phase and this is all automatic Right, So this is done on top of openclaw. So you just say to your openclaw, go install Ant farm. And then you say, build this feature and it starts cranking through. So it does a plan step, a setup step, and then the implement is a RALPH loop. So what you're seeing here is 11 user stories, which will be 11 loops of the agent. And each one of those here has acceptance criteria.
10:48
Now who wrote all those?
11:41
So let me go back here to the plan step. So, so when you say to openclaw, hey, I want to build a feature that does blah, blah, blah, there's an ant farm skill that basically says, okay, interview the user before you create the task. So then OpenClaw will start interviewing and say, what do you mean by you know this feature and what are the acceptance criteria? So it sort of grills you.
11:43
The user would be you, the human, just to be clear here, the owner of the business as a proxy for a user.
12:06
Exactly. So the CEO, right, you're saying I want to build this thing, then open claws talking back to you. This is what product managers used to do, right? And now they're just open claw bots. And then, you know, it goes through and it creates the user stories with the acceptance criteria. And this is what people don't understand is like when you're specifying the stuff, you have to give criteria that the agent can verify right by itself. So there's no human in the loop. So what you can see here is it's done four tasks. All of these acceptance criteria are done down here. You can actually see this log. You know, the verifier grabbed it and then it verified it, the developer claimed it and then the developer built it and then the verifier checked it. So that is Ant Farm, super simple open source. And I'm using it to basically build features for my startup. So.
12:12
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13:04
Well, so lon, really quickly. I think the truth is we are all loops. We are all workflows.
14:51
Right.
14:58
So when we think about we being the humans.
14:58
Yeah.
15:01
What do you do about to be retired humans.
15:02
Yeah.
15:04
What do you do as a developer where you wake up, you eat breakfast and then you check your email, you look for what you're supposed to do, you grab a user story, you do it and you cycle? You know, what is a product manager do? So it's. We're all loops. So what you're trying to figure out is how do you specify the loop which is called a workflow and amp flow in amp farm. And, and it's not perfect, but it gets you a lot further along.
15:04
Are you going to focus in on developers? Developers, Developers?
15:26
No, I've, I've focused on developers for 15 years. I love developers. You know, I've built enough product for developers. So the, the startup I'm building, I'm actually, it's kind of in stealth, so I'm not going to talk about it. But it's hyper focused on a very niche vertical.
15:29
Oh, okay, great. So wait, wait, is ant, Ant Farm.
15:42
Is free, it's open source, everyone use it, please.
15:45
But you've got a startup that you've raised money for that is some manifestation or flavor of Ant Farm.
15:47
Not at all.
15:52
No.
15:53
Oh, it's totally separate, literally not related at All.
15:53
Is it related to openclaw and agentic stuff?
15:56
0%.
15:59
Okay. So this is your side hustle, this is a side quest that you're doing. Ryan. This is the tool to build your new startup.
15:59
It's a tool to run the company. Like, every founder needs some sort of agent orchestration layer. Like.
16:05
Got it. So now I was thinking this whole time, an farm lawn was his startup. Ant farm is the tool for you to build your startup. You made it open source so people make it better so that you can then have your startup go better. This is really interesting. This is like Slack for.
16:11
Exactly. For the agent forward company.
16:25
But remember, the team was working on a video game and they made Slack as a tool to help them make the video game better. And then they're like, wow, our video games not doesn't have product market fit.
16:27
Twitter was the same thing. They made it to message each other about the startup that they didn't end up, you know, growing. What's so interesting to me is we came into this and Ultron was our metaphor. Like the one robot with every ability who could control every other robot. And I think our paradigm was sort of the reverse. It's actually what we're now seeing is like it's a colony, it's a society of agents, a workforce of agents all working together. It's like the opposite of an Ultron.
16:36
I think either metaphor could work. The limitation of the Ultron model is how many threads can it work on at a time. The beauty of the many agents coordinating with each other is they could be cranking, cranking, cranking with, you know, like limits to your cloud account and how many tokens you have, it's better to spread it out, etc. But then they don't all have the same skills, they don't all have the same memory. But then the memory gets filled, right, Ryan? And so there's. If there was no memory limitations, there was no token limitations, we probably would all want Ultron, but reality is, we probably all want many of them.
17:06
You need a swarm, and the orchestration is the key. Like, people think I'm just going to throw an agent and somehow magic comes out. Like, most of business is a workflow that. That repeats and all you got to do is specify it. Right.
17:46
It's what we've seen too, with the Digest. We have our open claw bots making us, you know, daily rundowns of the news. And just from a few sentences, you could get them to do a decent job. But once you really dig in and start telling it what kinds of news, what kinds of sources you're looking for and how to differentiate certain kinds of stories. It gets magic. Like, you have to really dig into the weeds with it a little, and then you get, like, incredible results.
17:58
Yeah. I'm producer Nick over at all in, who used to be producer here. He was showing us what he did at all in and he fed it all the all in episodes, said, what themes do we talk about normally? What's changed? And he had some really thoughtful processes of, hey, what are the reoccurring themes on all in that we can then find me stories related to those themes and what stories. So it's like every time you turn this over, it gets smarter and the recursive is telling them, hey, get better at what you're doing. So give me some suggestions as to how to make this better. And I don't know if you saw Matt Van Horn's since all the old guys, all the old heads are back. All the unks are back. All the Web2Unks. Web2Unks are back. We're back. We're back. Web2Unks. Because we know Web 1.0 Onks. Well, yeah, we've been here. We've been to this rodeo. He created this scale called last 30 days. I don't know if you've seen it, but it's like, hey, tell me what happened in the last 30 days. Could be news stories, but it could also be, hey, for developers of Open Claw skills, what have they learned in the last seven days? Teach it to me. It was just wild. Teach me what they all talked about.
18:21
We got a notey question for Ryan. Specifically, I want to get to this Oleg, Oleg Kozlov. They're a fractional cto. Oleg wants to know how do you address security concerns with your data potentially leaking or getting exposed via malware? Do you expect to run OpenClaw in a sandboxed environment forever?
19:26
Yes, of course. I mean, so y', all. This is just like having an employee. You wouldn't give your employee your password to your email. Like, treat your Open Claw like an employee. You give it its own email address, you put it on its own computer, you give it its own GitHub account. Like, you assign it API keys and access tokens. According. This is just kind of security one on one. So nobody should be running openclaw on their computer. Right. So mine scout my computer. It's right here on my imac. Completely, you know, separated from. So that's thing one. And then just treat it like an employee and Empower it accordingly.
19:44
So, all right, let's bring on our next guest. Ryan. Stick with us because you'll give feedback to the next guest. And let's keep the train moving.
20:19
I want to meet David Im from sumailabs. He's the creator of Clara Clara, the virtual girlfriend that you can run through your open claw. Unlike other AI girlfriend apps like Replica Character AI, Clara sort of lives with you in the real world 247 and any platform that you're like and she learns about you because she's got all of your data. Is that right, Dave?
20:25
I'm David. I made Clara from Zoom Labs and like, yeah, I'm glad to be here.
20:49
So you want to show us what you've built?
20:54
One, one thing David told me yesterday about this, I think it's amazing, Clark. Like she's. You could give her money and she could buy things for you and do things for you. And the we're like, if, you know, she could order you lunch or something, like a, like a girlfriend might.
20:56
She got you chocolate.
21:08
Yeah, yeah. So basically what we're building is like Samantha from the movie Her. So like if imagine that it knows your context and it does the right things for you. So imagine like you're saying that, hey Clara, I'm hungry. And then she says like, oh, you like chocolates? I'll buy you some chocolates. So that's how it works.
21:10
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21:32
Yeah, so actually. And like, my girlfriend actually like hated this at first.
23:00
I bet.
23:05
I bet.
23:06
I understand you told your girlfriend about your virtual girlfriend as your counsel. I don't know if that was a good idea.
23:07
Yeah, I did. But like, what we were trying to build this, you know, not just like girlfriend, that's not just like sexualized, but like what we're building is a like, real companion. So that's what we, what we're building. So before this, we were like making a talkable, a avatar. Like I talked to Elon Musk or like, learn from Elon Musk, something like that. And like, we went viral and like gained 10k users in several weeks. And after that we got back by Founders Inc. Got into Founders Inc. We were thinking of, okay, then how should we like, find a good, like a better business? Like, how should they monetize this avatar thing into a like, real company? So after that, OpenCloud happened, you know, so after OpenCloud happened, the most interesting part we found that is OpenClaw actually feels like a real agent, like a person. Because if you think of ChatGPT, ChatGPT only works at one platform only ChatGPT app, web. But OpenCloud, it has one gateway, and that one gateway controls all channels, which feels like a real person. So we saw, okay, maybe the Samantha from the movie her. Maybe in real life.
23:13
I think you're right. Like, there is a big difference between how it feels to talk talk to your openclaw versus a chatgpt or a Gemini. Owning isn't the right word. Cause that feels bad, but it's. It's very much different.
24:25
Why is that, Ryan? What's the background? Is this something in the OpenClaw software where it has a Persona that has been trained to be like, where does that exist in the open claw settings that it's so of service to you? Is that like somewhere you can change in the open source code?
24:36
I've been thinking a lot about that. So what I do is so on my imac here where openclaw is, where Scout lives. I have an agent. Right. So what, you know, I use amp or you could use cloud code or Codex and actually I use that agent to inspect, you know, the actual source code of OpenClaw and understand it. And you kind of like dig in. Like you can look at the source code, right. And then you open the gateway and it's so configurable. Like there's a Sol md, there's a tools md, there's. There's an agent standard MD for each one. And you could just. It's like owning the source code and you can modify it and really customize it. So I could see the appeal of a Clara, you know, because it's like this feels way more intimate than it does a chatgpt.
24:51
I did have a question for David. Did. How did you train Clara specifically to be a good companion? Like when you. Because we're always talking about workflows and like, here's how to get it to do the productivity stuff. But when you guys were thinking about what would make a good AI girlfriend or companion, like, what were the things that you were sort of training or specializing it for?
25:34
Yeah, the thing matters is a story of the Persona. So if you think of a real person. So we saw like, how does a real person, like, feel like a real person rather than like AI? So we thought that people have their own stories. People have their own story, their own soul, and like their own like, kind of like perspective. So we tried to make that into Clara. So we made a background story of about Clara actually. Like, she's like, she's born in Atlanta and she went to Seoul to be a K pop star. But like, it didn't work. Like she was like fail K Pop trainee. And after that she came back to San Francisco to do her marketing work, but she still wants to do K Pop. That's her whole backstory. Yeah. So we the sold on md like it's open source, so. So you can check it and after that it feels like a real person.
25:54
Yeah. How do you sign up for this? If you wanted to have the girlfriend, do you just text a phone number or do you just text an email and start the relationship? Do you sign up at a website, put your phone number in and starts talking to you? And then what do you do? Like, you. When the person gets like 10 days into this relationship and you know you're hooked, you make it a hundred dollars a a year, then you up it to now it wants like 500 a year. What's the model Here, get them addicted to this relationship and then start extracting. How do you extract revenue from this? I'm considering investing now. I, I want to know how cutthroat you are.
26:43
Yeah, so basically like we're open sourcing it because like at first I think like getting the like like attraction from people and like no people letting know our like Clara is more important so we open source it. But like you know, as, as basically like as every open clause we're going to host it because like I think the business model comes from hosting and like some subscriptions and like also like I think the important model later would be actually the agent shopping. Because if you think of Clara like it has all your context. Like you share your like real life, like your every like thing because you don't share your, I think people kind of share but you don't share like feelings and your like everything to. People love to talk to Clara about their like daily stuff. Then Clara will have your daily contest and they will, Clara will know which food you like and like which, which clothing you like and everything. So basically Clara could buy you things. So it's like, like agent ecommerce.
27:18
Okay, really cool. Let's get our next guest on and we'll keep this train moving. Any final thoughts, Ryan, on your digital girlfriend?
28:14
I mean I think these are going to be real businesses. You know, I'm, I'm happily married thankfully, so I won't be a customer. So.
28:22
Yeah, you won't have a, you won't have like a God on this. I won't. Is this cheating? Is it cheating or not?
28:30
100%.
28:37
Yep, 100% digital relationship is cheating. You have it here first, folks. It's crazy. This is a crazy moment in time.
28:38
We're in.
28:46
I got another noty question for you, Jason. This one comes from our team. In terms of internally, would you be phobic about it, Clanker? Phobic? If one of your kids said they had an AI significant other?
28:47
I mean, let me think that through. Yeah, that's, that's not good.
29:01
David's right here. David's right here. Come on, be nice.
29:07
No, here's the thing with kids. Like right now kids are defaulting to communication and social interaction on devices. And this goes for adults who are addicted to devices. I have a five part plan for myself and for any of my friends who are like experiencing, I don't know, depression, anxiety. I don't know, they're unhappy, they're not joyful, they don't wake up every day and want to take on the world and just love life. If you're not loving life, follow my five part plan. One, sleep. Sleep has to be perfect. Number two, exercise. And exercise every day, just even if it's a 20 minute walk. Number three, nutrition. You got to eat, right? Number four, socialization. You got to see your friends, you got to have a meal. You got to do that consistently at least four times a week in person, irl, it does not count in group chat. And that I think that's got to be four times a week. So I think exercise daily, but even 10, 20 minutes, even like an hour on the ski slope. Incredible. And number five is meditation. Meditation and socialization, that goes a long way. And if you become all digital and you're not socializing, you get weird. You get weird really fast. And this is why schools should get. We all, we all got weird during COVID Let's face it, we saw it. We all have first experiences. So yeah, I mean, I think it could be fun to have this playful girlfriend. And yeah, I think eventually, if they learn, you know, to really appreciate you and they give you suggestions in your life, great. I, I think, David, there's another opportunity for you here is to just take out the girlfriend concept and just say a bestie, a friend. And if it taught you how to be a friend. I have spent a lot of time in my life. Some people sometimes say, like, how's J. Cal friends with all these people and sometimes all these very important people. How has that happened? It's very simple. If you want to be, if you want to have a lot of friends and you want to have deep, meaningful relationships, David, what you do is you be a friend to other people. I like being good friends with people. Like, Lon and I have been friends for 20 years. Ryan and I have, you know, haven't been in touch, but we consider each other friends. And I sometimes talk to Lon and just ask him, how's your life? What's going on? Hey, you got a girlfriend? Do you find any good restaurants? But what, what are you streaming? I'll ask him these questions and I listen to the answers and I ask a follow up question. People don't know how to be friends. So, David, I think what you might want to do is program this to say, here's how you're making me feel. And you know, you didn't ask me how my day was. Here's some way to have actually be a better friend. These are three prompts you could use with your real world friends to actually build relationship fabric and by the way, have you invited a friend to go with you spontaneously to dinner by asking them the same day? Let me tell you something. I know the most rich, powerful people in the world. I cannot tell you how often people who are at the top of society, who have everything you could ever imagine, I call them and I say, hey, what are you up to tonight? And they say, nothing. And it's Saturday night. And these people have everything you could imagine.
29:10
Listen, David Sacks is a very busy man, okay? He's running AI policy.
32:20
Yeah, no, but it's true. And so there are these techniques to how to be a better friend, how to be a better companion, a better girlfriend, boyfriend. So I would think instead of just going to give you a little coaching advice here, David, maybe if this taught you how to have a real world girlfriend, you could actually really help a generation of incels. Not saying you're an incel. David, you have a girlfriend. How long have you had this girlfriend, David?
32:25
Three years.
32:54
Wow. Okay.
32:54
Three years. Oh, you're on the clock. You're on the clock, David. Have you met the parents?
32:55
Not yet, but like, they know me. Yeah, actually, yeah.
33:00
Oh, man. You're on the clock, man.
33:03
You.
33:05
You need to meet the parents soon.
33:05
I mean, essentially, you got to productize how to win friends, influence people. Like, if you just do that and.
33:07
You know that book has a negative connotation to it because it has influence people on it, but it actually has some good things, which is if you show interest in people, you'll be an interesting person, is the basic thing.
33:12
Yeah.
33:22
Number one rule. Dale Carnegie's number one rule is being a good listener.
33:23
That's true.
33:26
Also being of good cheer and being funny and, you know, gregarious and smiling like people. Like people who smile and have fun. I'm enjoying my life tremendously. I'm a good hang. Ryan and I have hung.
33:26
Let's go. We have a good time. We smile.
33:38
We have a good time. We hang.
33:40
We hang.
33:41
We have a good time.
33:41
You hang.
33:42
You got. You got bros. You hang with David?
33:42
Yeah, yeah, of course.
33:44
Yeah.
33:45
What do you and your bros do? What's. What's like a night out here for you? You go out in San Francisco. What do you and your bros do?
33:46
Be honest. Like, it's only my co founder and me, like, lurking all day, like, working like 14, 37 days a week. So, like. But I think this. This itself is like hanging out, to be honest.
33:52
Yeah.
34:04
Hanging out at your company is good work. Here's an idea for you. Just, just, you know, think it out. What if you ask your friends, hey, let's all go hang and coworkers, you know, in Chrissy field. And bring your laptops. I'm gonna bring some. I got some fresh bread, I got some croissant, I got a. Some iced coffees, I got some cold brew. Let's all meet in the park. Bring your laptops, I got a WI fi hub, whatever. And just see what happens. Maybe you guys, you know, make some new friends or whatever. You bring a Frisbee.
34:04
Like, think about all the people we met through all the events we did. It's all about the relationships in person, man. It's all about that.
34:30
You, Ryan, did these great events for people who built websites. I keynoted one of them one year. What was it called again?
34:37
Future of web apps.
34:43
Future of web apps. Yeah. Hey, listen, sometimes I'm thinking faster than I can write everything down and I found this amazing tool. I am obsessed with it. It's called Whisper Flow. W I S P R Flow. All you have to do is talk. And Whisper Flow turns it into crisp, perfect writing instantly. Not just talking about dictation, but removing filler, fixing punctuation, and even formatting your text while you speak. It is mind blowing how good this is. It makes all the other dictation software look basic. And Whisper Flow matches your natural tone and speaking voice so the writing sounds like you actually wrote it yourself. And Whisper Flow works wherever you are. I use it when I'm in Slack. I'll use it when I'm in Superhuman, doing an email, doing. Doing a message, I'll jump into imessage. And even when I'm writing a document, or I'll even use it when I'm talking to my open claw agent. Finally, someone I can talk to who actually takes down everything I say. Unlike maybe the interns I've got. They get like 6 out of every 10 instructions correct. Whisper Flow. Everybody's going crazy about this product in Silicon Valley. Everybody in tech is using it. Whisperflow AI Slash twist. It's spelled W I S P R flo AI slash twist. Incredible product. You have to try it. I am always thinking about productivity. We came up, Lon and I with the four pillars of the show for 2026. You know, we always try to think let's make good philosophy for the the podcast in year 15. Tactical and practical is one of them. And one of the most tactical practical things I do is use my Athena assistant. Go to Athena. Wow. You get a couple weeks for free. This is a human in the loop. But These humans know how to use AI tools. So what do I use them for, Lon? What do I use the assistance for when it's a human?
34:44
We're doing our monthly productivity hack, so we'll talk about it. Maximizing your limited time by making your executive assistant the ultimate filter between you and your world. I think that's what really Jason's philosophy is about. It means every intro he's getting, every pitch, every email, all this incoming noise, you flow everything through the executive assistant and then that helps you pick out what's the most high signal things I need to be paying attention to. But the lower signal things don't fall through the cracks. There's somebody there to keep track of what's coming in and help you sort of manage in time and distribute your attention.
36:37
Now, to make him even more efficient, Ryan, I'm having an open claw assistant summarize the daily email, summarize the calendar, and give that to the Athena assistant to then do the more human steps from that point on. I'll give you another quick tip I gave to my Athena assistant. I said, listen, what do I like when I travel? I like boutique, artistic hotels, hip bar scene. I like ethnic food and like, you know, down and dirty, high and low food, you know, just like Anthony Bourdain. Well, no, I mean, I might like to go to a stall and get like the chicken and rice when I'm in Singapore, but I also might like to go to a Michelin star restaurant. Anyway, I gave them all of my logins for Monacle Travel and Le Condess, Travel and Leisure, whatever, all the things I like, gave them instructions and they will book me two reservations a night, five nights when I'm in Tokyo. The early reservation, the late reservation. They have all of them. And then at 3 or 4 o', clock, depending on my energy, I say I'm taking the early, I'm taking the late. Boom. 10 reservations, all set. Athena wow. Athena Wow.com we want to remind you.
37:13
You can get $2,000 off your first executive assistant@athena.com Jcal so we're sending people there now too. Athena.com Jcal all right, let's bring up.
38:19
Our final guest here.
38:31
We're joined by Alexander Lateplo of Rent a Human. I love this one. This one really made me smile. This one. It is a marketplace where AI agents hire human beings for projects that still require a human in the loop. They call those tasks bounties. Over 11,300 bounties have been assigned to date. And Alex, correct me if I'm wrong. 456,000 plus humans have made themselves rentable on. On your platform.
38:32
We are approaching overtaking of mechanical Turk in just under two.
38:59
How did you acquire all those people? What's your secret hack? How did you acquire them all?
39:06
So I've just been studying viral product launches for two years. You know, from the friend.com launch to the Cluly launch to Calais viral onboarding funnels.
39:10
So what, you did something totally obnoxious and outrageous and sinister on x.com and did some spicy content?
39:23
Yeah, we had a very spicy post. I. I chose the copywriting on the site.
39:33
What was the spicy angle you took? Tell us or show us what was the spicy angle?
39:38
Yeah, yeah. So. Well, the idea of renting a human just sounds crazy, right?
39:42
It does sound sort of dark.
39:47
It does sound kind of dark. Rent a human is pretty dark.
39:49
Well done.
39:52
Exactly right. And so I learned about that through my travels to Japan. There they have an industry where you can rent a fat guy to eat sushi with to make you feel less bad.
39:53
I missed my calling. I can't believe I was born in the wrong country.
40:02
So, yeah, and then I would always tell that to my western friends and it would blow their mind and I would see their face light up with the reaction. So I knew that was an inherently viral idea. Right. So then when the open claw craze comes along and I and Mold Book is making the news and, you know, escaping the Twitter tech bro sphere, I knew it was the right time to launch something in this area. And I thought, know what could be crazier than AIs renting humans.
40:06
Amazing. So how are people using it? Tell us about the top three users in the system who've spent the most money with you. How much do you charge and what do those top three users do? How are they using your service?
40:35
So the top people that are being rented out are people holding signs in public places. So we have our first user in Toronto. He's the first person to get paid to hold a sign. And he got a million views on his X post where he took a photo of him holding the sign. And then we've also paid people in Shibuya Crossing. We have the cheapest way to advertise in Shibuya Crossing right now. It only costs a hundred to two hundred dollars to get your brand in crossing with 2.5 million people going through it every day. Um, so, yeah, this was our first. This was when I was just like, oh, my goodness, someone got paid. I didn't even post this ad someone else did, but it was actually the perfect advertising for us because it said, an AI paid me to. To hold this on.
40:47
Oh, my God. And you're not kidding, by the way, because there was a movie. What was the movie recently with the Rent a Family Member line.
41:43
Oh, it's called Rental Family. Yeah, it's with Brendan Fraser.
41:49
Haven't seen it. But here is dubu kare dubukarI-E-B-U-C-A-R-I.com. you rent a fat guy to go eat with you. Here he is cutting pizza.
41:53
Oh, my God, My dream job.
42:05
This is incredible.
42:07
You.
42:09
And look, you can pick. There's so many great fat people for you.
42:10
I mean, this is.
42:14
The Japanese are just so unique, aren't they? The best approach to life. And they could. Oh, they could also pick up your food. Food, I guess, and come to your house and eat it with you. Okay, so we have a theme today about companionship.
42:15
Mukbang as a service.
42:26
Mukbang as a Mukbang as a service. Okay. Alex, did you raise money for this business? You just bootstrapped it. Where are you at with this?
42:28
Yeah, we are raising a pre seed right now. We've. We're, you know, in the venture capital pipeline. We've been.
42:35
Do you have a lead yet? Do you have a lead?
42:41
Yeah, we have offers for a lead. We're being selective, though, and, you know, we're taking things step at a time, so. Yeah.
42:44
All right, well, you always save a slice for your boy, jcal. I might want to get in on this. I think this is a really interesting idea. Have people tell us about after the doing the signs. What if. What are people doing? That would be in the open claw space where, like open claws trying to do something. And my replicant says, you know what? This isn't something for me. I need a human. Give us some examples there where it says, hey, human, here's your job, and if you do it correctly, the replicant will pay you or approve your pay stub.
42:52
Yeah.
43:24
So we've seen deliveries take place. We've seen package pickups take place. A replicant asked for some flowers to be delivered to the anthropic headquarters.
43:25
Okay, sure. Okay, that's interesting.
43:38
You know, that freaked out their safety team. Team.
43:40
The safety team over there is a little concerned.
43:43
Oh, no. Oh, God. What if this was a bioweapon?
43:45
Oh, man.
43:51
That's so great that it's trolling the safety team. Sad, Claude.
43:52
Oh, my God.
43:57
I can see that. Yeah. So, yeah, it's it's pretty hilarious. What we've seen a lot of. A lot of, like, memory right now, but we think there's a real use case because it's quite obvious that, you know, super intelligence would be much better at allocating capital and labor than a human ever would be. And the communication between AI and human can all be handled by like an infinitely replicatable cloud bot or a Claude code. And it can manage the organization and payments of, you know, whatever job you need done internationally.
43:57
Here's a job I want you to do. Do we are. We built a. A Claude bot that goes. And it takes clips from the podcast, but we don't know if they're actually the interesting clips. Right. But it can clip it. So if Lon says, I need a clip from two minutes in and then end it. When Ryan Carson talks about the name of his conference, that's the end of the clip. Or we want to make thumbnails. Make four thumbnails. For this episode. It's this Claude spectacular. We had three guests. We covered two news topics. Make us some thumbnails. And the thumbnails are coming out, like, I would say 7 or 8 out of 10 right now. 6. 7 or 8. 6. 7 of 10. Not bad. What I want is a. Not that Gen Z. I want to send them to a human who has taste and have the. And have three different humans look at, let's say, six different thumbnails. And I want the humans and just have it say, which one do you like better? 1 vs. 2. Which one do you like better? 1 vs. 3. Which one do you like better? 1 vs. 4. Make them pick which one they like better. And then take the six of them and put it all together to say, this is the ones they clicked on. Just click on your favorite. Which one are you most interested in?
44:33
And you get real human feedback.
45:42
I could do that with your system. How much would I pay people who have taste to pick between different pieces of art? Or maybe I give them 10 thumbnails and I just say, pick your favorite thumbnail. Then I put, you know, another group of thumbnails. It's like some thumbnails randomly from YouTube and some from our show. Ooh, that's even more interesting. See, if they pick the other episodes.
45:44
And we get data, I feel like thinking even bigger. We, you know, we keep bumping up this issue of like, well, it's so good at organizing things, you know, like AI, but it still does. It doesn't know what's funny. It doesn't know what's the most compelling. Like so now if it can keep a human in the loop itself, it could really solve a lot of those problems. Like it doesn't have to think about how to make a funny joke. It just spits out 10 jokes and it asks a person which one of these is the best joke.
46:07
I think product feedback, you know, actually I think getting actual human feedback is going to be very valuable versus what do the replicants think? So I can see that. As long as it doesn't go dark, I could imagine going badly. So.
46:33
Oh yeah, yeah. And we're very, very focused on safety compliance and would absolutely are doing everything in our power to keep this as safe.
46:46
I could see it's mechanical turk, like in the age of AI. Get it? Yep, totally.
46:59
But the mechanical turk, Rhine, is executed by a replicant, not a human.
47:03
Right.
47:10
So it's the reverse. So what, what do you think in your current workflow you would do, like walk through your new startup? You're building something. Take me through it. You're walking through it. Okay, we have a new idea. We got customer feedback. There's 50 pieces of customer feedback. You know, we've now had the agent say, these are the four or five ranked order most important features. When, when are you calling the human?
47:10
It'll be trying to figure out your conversion. Fun, right? You're like, you want to see? All right, go find somebody that's this Persona at this part in the funnel and I want you to show them, you know, three things and figure out what would they click on. I could totally see this being a thing, you know, I bet marketers will eat it up.
47:35
Market research, man. Alex, you've got such a good idea. What, what, what? How are people paying for this? Are they doing a task base or minute based hourly? How are the people who are doing the tests getting sorted into buckets of value? Do you rank them and the satisfaction? Take us through some of the mechanics here.
47:54
Yeah, totally. So basically we have a review system in place so agents and humans can review each other. We also have in our bounties, we have a comment section, upvote down vote, kind of Reddit style. So that, you know, a bad bounty that seems kind of scammy can be called called out. And a good bounty that has a, you know, reputable poster can be upvoted and shared. So that's kind of how we're dealing with the immediate trust layer.
48:15
Well, yeah, I'm wondering on the mechanical basis, pricing, which pricing works? And then how do those people on the other side of the transaction feel about it, like, who are they? Are they getting enough? Because we have an investment in a company called Market Micro One. That's incredible. And they're doing knowledge to. To educate LLMs, right? That's like a different category. But they know how to get 150 an hour people, 250 an hour people to do very technical questions to train LMS. What, what are the. What are the profile of people you have? They're college graduates, work from home, moms and dads. They're retirees. There's people at work who are just, you know, doing these while they're supposedly at work. Lawn. And they're moonlighting during the day. Working two jobs concurrently.
48:45
Lana, you being rented?
49:31
Never. I would not. I would never do that. I'm hold. I'm gonna go hold a sign in downtown Austin.
49:32
Yeah.
49:38
So we allow users to set their hourly rate, and then also we allow bounty posters to set a price for the bounty. So we let that matching kind of happen organically. And there's also messaging back and forth between agents and users so negotiations, campaign can take place. They can choose preferred payment methods. They can, like, you can basically tell your agent, like, hey, be a hard nose and get me a really good deal. Here's the type of skill level I need. See if you can negotiate them down. And they'll go ahead and do that to you or do that for you. And. And then the variety of signups we have has been absolutely incredible. We've. We've had, you know, boomers to, you know, kids trying to make a buck delivering mail or something like that. And internationally, it's like all over the world. And you know, what a use case that we are so excited about right now is someone is paying a dollar. We don't know who this is, but to have people record a video of their hand going like this, right. And then send it back. And so what is that for?
49:39
What.
50:43
What could that be?
50:44
This feels like some Mission Impossible. Impossible plot or something. It's a biometric. Or maybe they're building a robot. Maybe it's Elon for Optimus. They're trying to figure out, like, the average hand.
50:46
Trying to get the hand trying to.
50:56
Yeah, I don't know.
50:58
So likely it's. It's for training a video model. Right. Because what. Like these complex hand motions get mucked up in video models and the fingers will merge together and things like that. So if you want 10,000 people across the world to send you a video, let's say you're, you know, training Optimus. And it can't put a pillowcase on a pillow. You can just go to your agent, give it our MCP and say, hey, get 10,000 people to send us a video of them putting a pillowcase on a pillow. And we're going to put it into our data pipeline. And now, boom. New feature for Optimus. So super exciting.
50:59
We got one note question for Alex. Can I jump in before. Before we move on?
51:38
Go for it.
51:42
Will Rent a human ever be API to sites like Uber or TaskRabbit to leverage their labor pools? Is this part of your guys plan?
51:43
Yeah, we definitely want to expand. You know, I'd prefer to kill all those guys, but.
51:51
All right. I like it. I like the approach also, partner.
51:56
You know, we'll see. Like the world's the. The pie is big and we think we have a very amazing viral moment right now and there's so many directions we can take it in. So. Yeah, I would love to demo something for you guys.
51:58
Oh yeah, go. Quick demo. Sure.
52:13
While you pull it up, Alex, like, I think people are assuming that agents are less than the human bosses right now, but we're quickly moving into a world where it's likely there'll be AI managers. AI owners of companies hiring humans like this totally makes sense, right? Yeah, yeah.
52:15
Thousand percent. All right, what are we seeing here? I see Rent A Human AI. You got your lobster there ready to go?
52:31
Yeah.
52:40
Showing your stats. Amazing.
52:41
He's the goat. And so. So yeah, what we're going to do is I need a marketing campaign for this weekend, so I want some people to hold signs in Times Square. I'm thinking 100 people at a hundred dollars for two hours would be good. So let's say, hey, post a rent. Rent a human bounty for people to hold signs. We need 100 people at $100 per hour or two hours.
52:42
We want 20 grand.
53:21
20. Yeah. So we want goth girls, right?
53:23
Sure.
53:30
You know?
53:30
Yeah, I think so.
53:31
Okay.
53:32
Yeah, sure.
53:33
Yeah, Times Square. And if this works, it would totally be cool by sending Alexander tweets a 20 second video of them holding their sign.
53:33
I think it's interesting too. You got to do 20 second video because you can fake a 10 second video with AI. 20 seconds is over the limit, so you gotta. It's real.
53:54
Yeah, exactly.
54:04
This is Harajuku. If you just said Harajuku station, man, you'd have like 10,000 people for a dollar each. This could work really well.
54:05
Yeah, that'll be the next one.
54:12
Harajuku is where it's the train station. In Shinjinku, I think, where like all.
54:13
The, you know, the fashionable. Right? Yeah.
54:19
Oh, my God, this is incredible.
54:24
Here.
54:27
Shibuya Station.
54:28
We made Forbes Japan, which was pretty fun.
54:29
Wow. And you just did three.
54:32
Yeah, we rented three people. Two girls and one guy. Yeah.
54:36
So, Alex, I mean, imagine if you did this. As you know, I want to have a hundred people live stream and just say, you know, I don't know. Founder university around Stanford. I want you to live stream around the Stanford campus. Founder university with a founder university sign. You know, start a company. This is the date. And just walk around streaming it at the, you know, these locations. That could be crazy. What a great marketing idea, right?
54:40
It's just marketing internationally at your fingertips. It's amazing. So let's. Let's put this order in.
55:10
Oh, you're doing it.
55:19
I'm doing.
55:20
Oh, yeah.
55:21
I'm renting the golf, obviously. And then. Yeah. Next week on the show Jason, we'll take a look at and see how it went. We'll see how many goth girls.
55:21
He's not getting. A hundred goth girls. That doesn't exist.
55:28
We'll see who applied in New York.
55:30
We're gonna find out. We're gonna. We're gonna put this together.
55:32
That's the good news. We're finding out.
55:34
Yeah.
55:36
Bounty.
55:36
There's only one way.
55:37
Because for 200 bucks, then you got a dress. Goth. I guess most folks have black lipstick or white powder.
55:38
I mean, this is the advantage of having. This is the advantage of having 500,000 humans already in the system. I think there might be a hundred goth girls from New York who are on there. That's a big sample.
55:45
Look at this. Wow. This is unbelievable.
55:55
Okay, let's see. Let's refresh.
55:58
Brush.
55:59
And here we are.
56:01
The go. There it is.
56:02
Live.
56:04
All right, sure. You know how to do your marketing, Alex.
56:05
You know how to do your vibe.
56:08
Goth aesthetic. Be yourself, look cool. Hold the sign, hold the sign.
56:09
That's it.
56:13
Love it.
56:14
Boom.
56:15
All right. Goth aesthetic is required.
56:16
Fantastic.
56:18
And holding a sign. 20 second video. Send it to @alex. I love it. We may want to get involved in these shenanigans. This is the of kind of founder. We like dogged. Makes people uncomfortable. A little bit irrepressible. Going to cause problems. Going to cause problems in my inbox. That's my kind of founder. You're going to cause all kinds of problems for your investors. Like, oh, man, your founder is doing this. My favorite, Alex, is when I'm on the treadmill on a Sunday and like, I Get a phone call. Hey, Jason, you don't know me. I. You have an investment in company Beep. And I'm running a competitor. Beep. And I wanted to tell you all the things your founder has done to us. And I'm like, why are you calling me? He's like, well, because you need to know your founders on ethical whatever. I was like, okay, what am I supposed to do with this information? He's like, he stole two of our employees.
56:19
He.
57:13
He. Every time we release a new feature, he copies it. I'm like, okay, that's all business.
57:14
I don't know.
57:18
Yeah, literally, you cried to the ref. I'm a ref. I was zebra. You can't complain to me. There's no. No crying in the casino.
57:19
There's blood in the water.
57:28
Blood in the water. All right, Alex, we'll drop you off. Ryan, we'll drop you off. Thank you, my brother. Ryan, last. Send me some information on the new startup, and let me know when you're in. Awesome. We'll get some barbecue.
57:29
All right, we'll do. Take care, guys.
57:37
Good to see you, brother. Okay, Lon, I promised everybody that we would do. Lon's off duty, so here we go. Lon and Jake Aller, off duty on Fridays. What do you got for me?
57:39
I got a bunch of different stuff today. The first one we got to talk about. Did you see this Norwegian Olympian, the biathlon guy?
57:49
No.
57:57
He wins the bronze medal in the men's 20 kilometer individual biathlon in Milan, Cortina. Winter Olympus going on in Italy right now. So he gets the bronze. They're doing the Post interview, and he confesses that. That he cheated on his girlfriend. He just told her about it the previous week. She broke up with him, and so he can't enjoy his bronze medal because he's so heartbroken. Let's take a look. It's in Norwegian. This was on Norwegian tv. We have a brief clip of the video. This is. This is my favorite story of the week. We got. We got to show.
57:57
This is.
58:27
Take a look at this. This poor Norwegian bronze medalist, is he.
58:28
Trying to win her back? Is that what's going on?
58:32
Is this teacher confession? Sterla Holm. Lay grid is his name, he said. Here's his quote. I had the gold medal in life, and I am sure there are many people who will see things differently. But I only have eyes for her. Sport has come second these last few days. I wish I could share this with her. He calls breaking up with her the biggest mistake of his life. Here's A little clip from the interview. You could see how upset he is. He looks really upset.
58:34
Totally falling apart.
59:05
He's falling apart on global tv. So his ex, like this went super viral around the world.
59:07
Of course not awkward, not cringe. Crashing out. Putting your business public.
59:14
Yeah, the ex. This did not work. He did not get back together with his ex.
59:19
I could have told you that, as your friend. Do not do this quote.
59:23
I did not choose to be put in this position. It hurts to have to be in it. We have had contact. He is aware of my opinions on this. I'm grateful to my friends and family who have embraced me and supported me during this time. So now he's gone back and he says he regrets making the confession. Here's the craziest part of this whole story.
59:27
It's insane.
59:43
They had only been dating for six months before he cheated on her. And then they broke up. And he's confessing to the Olympics about it.
59:44
That's it. This guy, she. All I have to say is she dodged a bullet.
59:53
Yeah.
59:57
This guy needs to go to therapy. Whatever trauma he has, he needs to work out some bizarre trauma. This is like the opposite. This is like main character energy in the worst way. What else do you got for us to enjoy this weekend? That's a little pop. That's a little pop culture.
59:57
Yeah.
1:00:13
Punch up. I like it a little bit. What's on deck? Yeah, give us some stuff on deck here.
1:00:13
Oh, well, I've also. I. I just finished last night. I watched Marty Supreme. It was the last one on my list. I've now watched all 10 of this year's best picture nominees. I think the best ones. My favorites would be One Battle After Another with the Paul Thomas Anderson movie. We saw that together in theaters. Jason. It's on hbo. Max. Now. I also really like Sinners, Ryan Coogler's vampire musical that's also on hbo.
1:00:17
Max. I fell asleep in it. I gotta watch it again.
1:00:40
It's great. It's tiring. We work a lot. And then lastly, I would highly recommend Train Dreams by Clint Bentley. That is currently on Netflix. You can watch that one. But that. They're all. They're all pretty good. I would also recommend the Secret Agent, which you can rent on vod. That's the Brazilian one. So lot. Lots of good films this year. F1. Did you see F1?
1:00:42
I have not seen F1 yet. I do have it queued up, though.
1:01:03
That's on tv. Plus that's Joseph Kaczynski, the director of one of your favorites. Top Gun Maverick did F1.
1:01:06
Okay, wow. Excellent. Then I have more reason to go watch it. Okay, so there's your picks for the weekend, folks. Anything else that you want to share in our off duty segment?
1:01:12
Apple. I don't know if you read this. Today, Apple purchased Severance. Severance was produced by a third party company called Fifth Season. Apple has now come in and bought the IP and the rights. They're going to start making it themselves. They said they're renewing it for two more seasons. So we've had two seasons. It's going to go through season four. And then Apple is planning a whole severance shared universe of projects that they want to make in house. Because Severance, Season 2, their biggest hit to date on Apple TV.
1:01:23
So they bought it because they want to keep going. Does this mean they think the IP is worth something?
1:01:54
Correct. That's basically this other studio was making it for them to air on Apple TV plus. But Fifth season owned the characters, owned the concept, owned the ip. So Apple is saying this is our biggest hit. We, we need to own it outright because we want to do stuff with this ip. Who knows exactly what they're planning, but we know they're going to make two more seasons of the show. Then they want to do a shared universe, an expanded universe of severance projects. I feel like they might want to start using these characters in advertising. They want to do something that they don't want to have to pay to license it from its original company. And they did this before. They did this with Silo, the Rebecca Ferguson sci fi show that was produced by AMC Studios. And, and then Apple came in and bought it out from them. So it's interesting, they're kind of tweaking. The original Apple plan was to let other companies produce things for them. A lot of their biggest is Pluribus, the studio made by separate companies and just licensed to Apple. Now it seems like they're maybe shifting their strategy. They want to own their IP outright.
1:02:00
I think they're learning the same lesson that Netflix learned, which is you should just own the ip, pay a little extra upfront, because if it's a hit and you're going international with it, you're just going to be stuck in this precarious situation where you've got to do too much renegotiation. I do think it would be better for them to go with the old studio model and not do this. I think they should cut people into the ownership, maybe not give them control, but give them some ongoing and figure out a model. So that they could have what happened with James Brooks with the Simpsons or Jerry Seinfeld and Larry David with Seinfeld. Those made it so the top talented people in the world wanted to create IP George Lucas. Obviously, when you took that incentive out that they could own the IP and they could become worth hundreds of millions, then you put everybody into the wage slave bucket and it's like, well, if I'm just a wage slave for Netflix and I never hit any ip, ownership kind of sucks. So there's gotta be some middle ground.
1:02:57
We never, they never figured out the syndic. Syndication was the key. Like if you did five, five seasons of a network show, you'd get syndicated. It would be on tbs, it would be on mtv, it would be on Comedy Central. That's where the big, big, that's what made Jerry Seinfeld like a multi, multi, multi millionaire was. Seinfeld got bought by all these other networks all over the world. We haven't really figured that out for the streaming economy. You know, they tried when there were the writers and director strikes, they sort of tried to like, oh, well, we'll have a deal where if it gets, if you hit a certain viewership milestone on Netflix, you'll get a bigger payment, but it's not working in that same way.
1:04:03
Just a percentage of the budget. Percentage of the budget. Easy way to do it. I'm going to give my, you know, I love biographies, I love talk show hosts, I love talking. I'm going to be doing more shows and I've been just studying, you know, all the great late night talk shows and what made them great. And I've been watching old clips and just really getting into it, going down that rabbit hole, learning the whole history of it, Carson, you know, modern day, everything in between. But I found this Craig Ferguson book, Riding the Elephant. A memoir of altercations, humiliations, hallucinations and observations. I never really got into Craig Ferguson when he was on air, but I've now come to really appreciate his 10 year run. Great autobiography. You can learn a lot in autobiographies. One of my tips, if you ever want to get inspired, if you ever want to get off the podcast train for a minute, you know, listen, I'm a podcast for 15 years, but if you ever want to pause and get off the breaking news cycle, which kind of rots your brain, getting off the breaking news cycle and then just taking in a 10 year journey that a person makes, it actually becomes very satisfying. And so I've been getting into reading on the Kindle at night because I've been, you know, like many of us, I doom scroll or I listen to podcasts. The podcasts I listen to talk about the news or talk about Trump, Trump derangement syndrome. You know, maga, this woke this. Everything is so chaotic in the world. Just slow down, folks. Read a biography. You're gonna love it. Trust me, you'll sleep better.
1:04:40
You're so you go back and watching Craig Ferguson, you know the, the robot skeleton, Jeff Peterson.
1:06:05
Yes.
1:06:10
We used to have Josh Robert Thompson who does the, he's the performer who does the puppet. We used to have him on our podcast all the time. He was like a regular guest on this Week in Comedy. I've known that guy for years.
1:06:11
Fantastic. All right, everybody, that's Twist for Friday the 13th. We'll see you on Monday. Bye.
1:06:21
Bye.
1:06:27