00:18:15 · Molly O'Shea
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00:19:52 · Jaimin Rangwalla
[00:19:52] S0: So if you think about your initial chat GPT interaction, you would ask it a question. It would think for some amount of time, depending on the complexity of the question, and then it would come back to you with an answer, or not even a lot of times an answer, maybe it comes back with an intermediate step of, okay, I searched all of X, Y, Z. I did this. Am I on the right track? Do you want me to go more in detail? Do you want me to do less? And it was a lot of human in the loop. An agent now, when you give it a problem, like the amazing part of Opus 4.5 when it launched at the end of last year was that an agent can now spawn its own agents and that can increase the depth of work, the time of work, and the quality of the work. And so all of those things, that was a huge model unlock. Agents launching agents, I think, is one of the most underappreciated unlocks that has happened because you can give an agent a project now and you can just go away. And you can come back and it has done, if not all of it, really, really far along. And the amazing thing is you can also, when you instruct it and prompt it initially, you can say, go do this, launch as many agents as you want, and then launch another 10 agents to check all of these agents' work. So not only like it's so collaborative and and iterative now where the human is almost out of the loop. And if you think about it, the human was almost a limiting factor in how much work the agents could do because before, one agent or one chatbot would interact with one human, but it would always constantly stop. A third of the way it stops to check-in and be like, did I do this right? Do want me to do this again? And then two thirds of the way it stops. So the human is still limiting how much work that can be done. Now the human just has to prompt it, and all of the work gets done on its own. And now what we're doing, I use Claude too, I don't just ask it one prompt or one problem. I go and say, Okay, I want this done. And I open a new one, and say, I want this done. And I open a new one, I want this done. And so they're all working concurrently, and so you're able to launch agents, and then you're able to launch multiple pools of agents that also launch multiple agents below. And so to me, it's just the sheer power of exponential growth of the number of agents and the amount of work that's being done.
00:21:51 · Molly O'Shea
[00:21:51] S1: Yeah, we definitely saw that in the Open Claw slide. That was crazy. So what was their growth rate?
00:21:58 · Jaimin Rangwalla
[00:21:58] S0: So I think the Open Claw phenomenon is actually really interesting. I think most people maybe don't understand and appreciate it. What OpenCLaw is, it is a form of a harness. Harness is like the fancy word for how a person interacts with a model. Before, you're interacting with a model with just the ChatGPT interface. And then even if you have a terminal, maybe you're interacting in the clawed code terminal. But now a harness allows you to interact. You can be on another computer just typing to your claw and having it control a computer in a different location or a virtual computer and actually taking actions on your behalf. You can WhatsApp message it and say, you know, while I'm in the office, like we have analysts that are using it and testing it for us. He'll have his home open call. He'll message it and say, oh, book me a reservation on Friday at this restaurant, send the calendar invite to Jaemon, and then also make sure that we have a car service set up to take us there and back, and then send him the confirmation email and make a calendar appointment, do all that stuff. It is able to do all of that in the background, and it'll just come back to you with a message and say, okay, I did this and here it is. And so it's almost like the ability to interact has changed with the clause setup. And so now you can use a terminal to interact. You can have it in your pocket like the phone. We have a slide in our deck that just talks about the phone's almost like a remote now. It's a remote for your agents. Which agents do you have working on what? Which agents do you have doing this for you? And you can also launch multiple agents. And so I think that OpenClaw, you're seeing the trajectory, just the number of people that are using it and programming for it and trying to figure out how to incorporate it. Even in China, every one of the big internet companies has their own claw concept. ByteDance has one, Tencent has one, Alibaba has one. It's amazing how quick this has taken off, I don't think people fully appreciate it. But to me, it's just an intermittent state. I don't think that you're going to have it where you've got to go home, you've to hook up all these connections to your cloud, because today you still have to give it access to Gmail and this and that. There's going to be a big opportunity for someone to just say, Oh, here's your phone.
00:23:57 · Jaimin Rangwalla, Molly O'Shea
Here's the app, this is your super app. This now allows you to connect to everything that you have, and you can just ask this app questions and it is going to be the super app for you. [00:24:06] S1: Did you see the clip of Nat Freeman at Stripe sessions? [00:24:10] S0: I did not. [00:24:12] S1: So, he has Open Claw deployed on his phone, think maybe his laptop too, and so his Open Claw saw that he was dehydrated, and so it was like, Oh, go grab a glass of water. So he went to the kitchen, he grabbed a glass of water, he drank it, or maybe it was a bottle, and Open Claw took a picture of him and goes, nice job. And then he was also driving in his car, and they were like, you need magnesium. And so the car then rerouted to Whole Foods to get them magnesium. Was pretty crazy. [00:24:44] S0: Yeah, I mean, we're just at the beginning of what's going to be possible. [00:24:49] S1: So you mentioned that memory per person is exploding. Can you talk through the TAM of that? Yeah.
00:24:56 · Jaimin Rangwalla
[00:24:56] S0: So historically, you think about it, memory was tied to smartphones, memory is tied to computers. Everyone has a smartphone, everyone has a computer, and so you can just say over time, as people started adding more technology devices, individual might have eight gigs of RAM on a computer, you have eight to 16 gigs of RAM on a phone. And so you've seen like a natural growth of that just over time as you've seen penetration of phones, penetration of the computers, and then the density within each device also increases over time. But now if you think about it, if you or me in a year or two, we're going have a claw that's running hundreds of agents at all time. I'm going to have a similar impact at work. I'm going to have hundreds, maybe thousands of agents running at all time. All those agents require CPUs, GPUs, memory. Now it's persistent memory because it's not running twenty four hours a day. Some will run for some amount of time, some are less, you get the kind of a general direction of where this is going, which is your footprint, your like semiconductor or technology footprint as an individual is about to expand by like 10x because you used to have a couple of devices. Maybe you're someone who has an iPad too, you have x, a little more, but like three or four devices is about to go to thousands of virtual devices on top of, and the virtual devices are the agents, and each agent requires, you know, semiconductor content. So it is hard to like fathom a world where like we're all having this like big semiconductor footprint, but that's what's happening underneath the hood, right? And if we're all gonna be users and we're all gonna be using hundreds and thousands of agents at a time, that is where we're going. Like, on our call, we had Boris, Cherny, who's former CodeTwo alum, but also the founder of Claude Code, And he was saying that, you know, he runs, you know, some number of agents during the day, but when he goes home, he's running or on on his way out, he's has a thousands of agents running to kinda do work all through the night before he comes back in the morning. So just imagine, like if we're all going be doing things like that, where we're all going to be having periods where we're running hundreds of agents, and it can be simple tasks.