← This Week in AI
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- [00:00]
Jason Calacanis
If Dario keeps saying you're going to lose all your jobs and Elon says work will be optional and we'll have universal, high basic income people seem to be spiraling here in their predictions. Why were these kids who are the AI generation booing it?
- [00:16]
Jeffrey Cannell
We told everyone that like the knowledge work of the white collar was the pinnacle of achievement in society. You know, scaled up this thing that said, oops, actually, sorry, maybe that wasn't the contract that we're going to live under anymore. That knowledge work is this, you know, the pinnacle of what you need to
- [00:30]
Russ Dasa
be working on if you leverage these tools. Like, what are we really preparing people for? I really think that like these AI agents are just going to automate away a lot of the entry level work. So I think that that's creating this almost like disconnect between like what college is trying to preparing you for. Like, the job market is also like tightening on the other side. So everyone's getting squeezed.
- [00:49]
Stephen Berlin Johnson
Yes, the job. We don't know what's going to happen in the job market, but those skills will be valuable in whatever market ends up.
- [00:56]
Jason Calacanis
Thanks to our friends at PayPal, the exclusive sponsor for. For this week in AI try the payment and growth platform that's trusted by millions of customers worldwide. PayPal open start growing today@paypalopen.com all right, everybody, welcome back to this Week in AI episode 17. We're cooking with oil this Week in AI AI. If you want to sign up for the email or get quick links to our YouTube, Spotify, Apple Podcasts, all that good stuff, follow us on x.com formerly known as Twitter This week, the letter N AI. We dropped the I because somebody else had squatted on the name. Got a lot to talk about today, lots of the news and three great roundtable participants to walk us through everything. Jeffrey Cannell is from News Research. N O not N E W S. They do. They're an AI research lab creating open source AI. Something I keep asking for. And they are famous for creating the Hermes agent, which is getting very popular. How is Ermes agent doing? I understand you may have just passed Open Claw and openclaw is getting a little rusty. Dusty.
- [02:13]
Jeffrey Cannell
Yeah, I mean, you know, we prefer to focus on our, on our own thing. So. I won't, I won't, you know, I won't hit on the lobster too hard. No, yeah, Hermes agent probably. I think it's like number one on open router now, so seen a lot of growth. We just put out a desktop app a couple days ago too. It's just been sort of like a whirlwind over the last three months. You know, we sort of had this, you know, it started with cloud code and openclaw where suddenly like the, all of a sudden both the, the models were good enough and when you paired them with an agent, you know, you got this emergent behavior that sort of is like taking over the world, these agentic harnesses. So yeah, it's been a lot of fun to just head along with the ride and try to keep open source AI out there at the forefront.
- [02:52]
Jason Calacanis
Yeah, and I mean, listen, you may not want to talk about the competitor, but you guys are contemporaries. Let's just call it that. You're contemporaries. And it feels like the fit, the finish, the polish on Ermes agent has won you a lot of fans is that part of the explicit strategy is, hey, we're open clause a little rough around the edges. We're going to make this a little bit more polished on the UI ux. And that's the early win.
- [03:17]
Jeffrey Cannell
Yeah, I mean we really started out as building this for ourselves. We actually had a version of it before Open Claw came out. It was our internal tool that we use to help our, our, our model researchers like automate some of their work. So it really came from like this obsession with using it all the time. Like if you're using it all the time and you love the product, we just have a class of people at Noose who would be doing this if they weren't getting paid for it. Like it's what they love. And so sort of that obsession with the product and loving it so much, you know, made it so that made it into this thing that was really easy to use. And we do, you know, make an attempt to keep an eye towards the aesthetic as well. You know, it's something that I think can get lost a little bit in the tech spaces. But like, you know, we are people too. We're not just lines of text on a computer. Like we have all of our senses so we try to like engage people across like all that, that whole spectrum too. So we do spend a lot making sure that like the touch and the feel is good and just you know, making sure that it doesn't break. No matter what, you know, you update, it always works to the point that we have finally, I felt like with these agents have sort of like broken out into like, I guess you could call it like normieville. You know, like there's a lot of like non AI tech people who are finally seeing who the agentic harnesses let them see AI as something more than what it was before, which is kind of just like Google with, you know, like Google search on crackers, you know, I mean it was just like asking questions like the agentic harnesses when you, when presented in the right way, people kind of like, oh, now I see why you guys are so excited about AI. It can like do all this, you know, actual interesting, useful stuff.
- [04:48]
Jason Calacanis
Yeah. And there's something with that persistent memory and the skills building that really resonates with the hacker crew with us again, my old friend, and I mean that in both senses of the word. We both got old and we've known
- [05:01]
Stephen Berlin Johnson
each other since 90s
- [05:05]
Jason Calacanis
ancient. Stephen Brilliant Johnson is of course the editorial director of Google Labs and the co founder of Notebook lm, which was the og. I don't know how to describe it, but just a great application for projects is the way I think about it. When you're working on a project and you want a big context window, NotebookLM is just like the nuts. How do you describe it today? Because, man, you've had this thing out for I think close to two years and you were so early. Now there's a lot of people now, Stephen, who you're contemporaries with a lot of people, including Ermey's Agent and openclaw and Claude Cowork and Perplexity Computer. There's a lot of options now. Where does the product stand in your mind in terms of the playing field?
- [05:53]
Stephen Berlin Johnson
Yeah, I mean, what we've tried to do with Notebook is, you know, from the beginning it was predicated on this idea, which was pretty novel at the time of like a source grounded experience with AI. So you're giving it the knowledge you need to do whatever project you're working on, whether you're a student trying to study for a class or whether you're doing a startup and you have all these documents you're trying to deal with. So the idea was that the AI would always be grounded in that experience in those documents so that you had a sense of trust. And we had kind of state of the art citation system so you could always go back and read the original passage that was important to you. And then we rolled out audio overviews about two years ago where you could take the knowledge in those documents and turn it into an AI podcast, which was kind of our crazy viral moment, which is really fun. So it's really a tool for anything that involves a complex knowledge base that you are trying to understand and do things with. And increasingly we have gotten more and More agentic in the kinds of things that you can do with that knowledge base, including the big announcement yesterday. That is kind of the most significant change to the product. But we see a lot of people using it in research mode. I mean it's heavily used by students, number one user base. But anybody like a lawyer that has to manage information and make sense of information and transform information that's scattered across potentially hundreds of documents. Notebook, we think is is the best tool, the best surface, the best application for that kind of project.
- [07:23]
Jason Calacanis
It's really fascinating. I've got. I wanted to get your take on this. We might as well do it now and go around the horn. I want to get your take. I'll introduce our other panelists, but think about this one. I want to get all your takes on why AI got booed at commencement speeches when young people were the ones who are applying this technology more than anyone. So just keep that in mind while I introduce Russia. Russ Dasa, of course, is the CEO of Live Kit. That's the open source real time voice and video infrastructure company. Been around for a while and they are the transport layer behind ChatGPT's voice mode and many other people. I don't know if you can. And you were of course on this Week in AI back in April. I'm not sure what episode number, but tell us how the business is going and you have some other high profile customers. Do they want people to know that you're powering their voice or do you have to keep that quiet?
- [08:18]
Russ Dasa
Russ, For a lot of them we have to keep it quiet, but there's definitely some that we talk about externally. So Spotify uses us, they build agents on top of us. Also Tesla, all of like Tesla support center, service centers, roadside assistance and Robo taxis, Grok Voice, all of that stuff built on top of Live Kit as well. Um, what are some other ones I can talk about?
- [08:44]
Jason Calacanis
Be careful here. Do they pay two different prices? If the. If they want it private, that costs more. If they want to be public, it costs less. Or is it just their choice?
- [08:53]
Russ Dasa
Yeah, we give some discounts if, if they allow us to kind of tell the story. But you know, the most of them. I wouldn't say that there's like reticence to have it be known that Live Kit is powering it. But like, I mean in other examples, like we power all of Agent Force Voice for Salesforce.
- [09:10]
Jason Calacanis
Oh, nice.
- [09:11]
Russ Dasa
SAP just launched Joule, you know, their platform and application. A few weeks ago we were in Orlando for that because we're powering voice for, for them as well. So lots of really large enterprises and thousands and thousands of smaller startups as well, all building these voice AI based applications, you know, so you can interact with the, you can interact with the AI like you interact with the person. I think that that's the real big novel kind of unlock that has happened here.
- [09:37]
Jason Calacanis
It's certainly become less annoying. I literally, on Sunday, my old Tesla Roadster, the original one, I opened the door and the battery was down to 20 miles and I had been on vacation or traveling for a week or so and you know, we're supposed to check it every week but somebody forgot to check it and I was like, oh my God. I went into a full scale panic. My, my battery's going to break. I call the service center. And I had a delightful conversation with an AI. It was so obviously an AI, but it was so much better than talking to a human because a human feels the obligation to do like little small talk and warm you up and how are you doing? And da da da. And just, it was so efficient and it actually worked. Like if you interrupted it, it worked. Which has always been the problem with these voice jail systems. Press one, press two, da da da. Just get to the point. But are you also the CRM level for them or you just provide the voice layer and then it goes into whatever CRM they're using? Because it does seem like some people are bundling this voice level with a CRM, with a gosh, what's the name of the famous, oh, Zendesk or something like that. People use those kind of tools. So are you in competition with those people? Coopetition with them and the lines getting blurred. How do you think about that?
- [10:50]
Russ Dasa
No, yeah, I'd say I don't think we're in competition. I think we're just at different layers of the stack. So folks like Zendesk, there's other ones out there too. Even Agentforce from Salesforce has a product here. And what they kind of build within a vertical. Right. So customer support, it's not technically a vertical, but it's kind of like an area where they have integrations with CRM and other types of tools. Like what we really build is
- [11:18]
Jason Calacanis
a
- [11:18]
Russ Dasa
platform that allows you, it's effectively the agentic framework or the harness I think is a word that a lot of people are using, but I think people are mostly using harness. In the way that Jeffrey describes. Harness are effectively like the software layer that wraps the LLM that allows it to do work autonomously on its own or the Software layer that wraps the LLM that allows you to have a interaction using your voice and computer vision with that LLM. Right. So handling things like turn detection, understanding when you're done speaking and when the AI can start speaking, handling interruptions automatically, letting you use any model for stt, speech to text, LLM or tts, being able to expose tools. So what an agent force would do is they would build the agent on our platform using our framework and software, and then they would wire it up to tools that they have on their. Their side. So CRM or another product, you know, that agent force wants to integrate, and then the other. And then. Yeah, so you build it and then we're the cloud platform where you can run it as well.
- [12:17]
Jason Calacanis
So just amazing that there are like so many companies, Stephen, going after each vertical and solving each of these very granular problems. It was like the early days of Web 1.0, where there were just so many cruft and little, little nooks and crannies that needed to be polished, and then we just take them all for granted today.
- [12:36]
Stephen Berlin Johnson
I do think of those times a lot, Jason, but it's different in the sense that there's obviously, there's so much more attention. Like, we were able to kind of develop the web in somewhat secrecy for a while. Like, it was an insider kind of experience. And you would have many conversations with people where they would be like, hey, I don't even know what this Internet thing is, or I don't know what the web is. And you have to explain it to them. Whereas now, to your point about, you know, the boos at the college graduations, everyone at least has an opinion about AI right now.
- [13:05]
Jason Calacanis
Yeah, yeah. And there's 3 billion people using it. 3 billion people using it. And I think when you last used it and how deeply you integrated, how deep you went, forms your opinion, for better or worse. Because if you use this 612 months ago for 3 days, your opinion is completely based on outdated, an outdated experience. But unpack for me, Stephen, what you think happened at those graduations. Why were these kids who are, let's face it, the AI generation, this is the first generation who used AI in school, right? It was three or four years of ChatGPT. They were using it, their teachers were using it, but they're booing it. What was your take? And then.
- [13:54]
Stephen Berlin Johnson
Yeah, Jeffrey, I think there. I think there are a lot of things at work there, Jason. I think on the one hand, there is the concern that generation has about the impact of this on the job market.
- [14:05]
Russ Dasa
Right.
- [14:06]
Stephen Berlin Johnson
That they're worried that this is, you know, there are kind of leaders of some of these companies who are saying this is going to eliminate X number of white collar jobs in the next five years. Right. So we have that concern, like, are there is their future being put at risk at this? The other side of that, which is something I've been. I just wrote a piece about this actually called cognitive uploading, which is this idea that we've focused so much on the ways in which AI helps you kind of bypass getting a good education and helps you potentially have the AI write the paper for you one click instead of actually doing the hard work of thinking and processing. And I think we haven't spent nearly enough time, and it's on us as well as other people to really walk through the ways in which actually, if you use it properly, AI can actually help you become a deeper thinker and expand your understanding of the material you're trying to work with. And so for me, the way that I use it all the time is I'm constantly going in and saying, give me something new to think about here. Here's a problem that I'm trying to understand and here's a piece that I'm trying to write. Help me go find the information that I need to understand it and then help me explore that information, make new connections. And so I feel like it's an extraordinary kind of amplifier of my cognitive processes. Right. Like, I of course convinced I'm a richer kind of deeper thinker, but I think the public discussion of it, and also to your point about people basing their kind of model of what it's capable of doing on ChatGPT circa 2023.
- [15:40]
Jason Calacanis
Yes.
- [15:42]
Stephen Berlin Johnson
That they're just like, oh, this is a tool for plagiarism and cheating. And it's just, you know, it could be used in that way. But of course, there's also all these other ways in which it can be used to really enhance education. And I think we just need to do a better job of walking through what would be the ideal engagement for a student. Say yes. More out of it. Yeah. And that's incredibly, what we try to do at Notebook is build a scaffolding that actually encourages learning rather than allows the student to kind of bypass learning.
- [16:11]
Jason Calacanis
Yeah. And you mentioned Berkeley has like their rule set for AI. And it was essentially when I, when I read the first half of your piece, right before I got on air, one of the producers sent it to me and I'll finish it after I get off. But essentially they are saying, like, don't use it. Yeah, basically, maybe you could talk about what Berkeley said and what they got right or wrong.
- [16:36]
Stephen Berlin Johnson
And so there was an interesting contrast between the Berkeley law. This is Berkeley law and then our old friend Larry Lessig at Harvard Law, who had let Larry integrate. He's teaching a constitutional law class, and everyone had to use a notebook. Like, he put all the cases that they were studying, like 115 cases that they're studying in this class, and they made a notebook for each of those cases. And then the students would add additional knowledge. And it was just a way of, like, diving deeper into the thing they were trying to understand. And on the other side of the country, Berkeley, literally, their default policy is that the only way you're allowed to use AI in any form is to help you find sources. You are not allowed to upload documents or sources, as in some kind of research partner mode. You're not allowed to write with AI. You're not allowed to get, you know, outlining or brainstorming with AI. Individual professors can choose to opt out of that, but it's a very kind of blanket policy.
- [17:33]
Jason Calacanis
So one person is framing it as the card catalog. The other one is framing it as your researcher who is at your beck and call at any moment to quickly go run and use the Dewey decimal system, bring you back stuff and brainstorm with you. Hey, maybe these are some angles, Jeffrey, when you look at the framing of AI and the young people booing, obviously. Yeah. If Dario keeps saying you're going to lose all your jobs and Elon says work will be optional and we'll have universal high basic income, I think maybe. And Sam's talking about UBI and maybe giving half of OpenAI to Trump and to the government. I mean, people seem to be spiraling here in their predictions, and then the reality seems slightly different. But I don't know if these kids are being precocious and think it's funny to troll AI or if they have a legitimate fear or disgust with it. Because I kind of got the vibe that they were like, chatgpt kind of ruined my college experience. It wasn't organic. It wasn't like I'm the first generation to lose college. I don't know. That was just my projection into their thinking. But what do you think, Jeffrey?
- [18:47]
Jeffrey Cannell
Well, I mean, certainly there is always the argument between your stated and revealed preferences. Right. Like, people will, you know, college is a great place to be loud and have, you know, loud opinions and speak truth to power and so on and so forth. What Are they actually doing, you know, what are they doing in their, in their personal lives? So there's probably a bit of that going on. But I mean, obviously, you know, this is a question that I think, you know, if you only view people through economic terms, right, which is where we stand today in a lot of society, and then you introduce them to this new thing that says, you know, for the last 40 years, what was the plan? It was go to college, knowledge work, you know, learn how to code. Remember 10 years ago, 15 years ago, coding boot camp, you know, we told everyone that like, the knowledge work of the white collar was the pinnacle of achievement in society. Right? Yeah. And, you know, within, you know, two to three, you know, really within the last six to nine months, if you want like the truth. But the timelines are a bit longer to people who aren't paying attention. You know, we basically, you know, scaled up this thing that said, oops, actually, sorry, maybe that wasn't the contract that we're going to live under anymore. That knowledge work is this, you know, the pinnacle of what you need to be working on. And it, you know, it doesn't surprise me that if you tell people that their worth is, you know, where they go to school, what job they can get, how much money they make, and then you create this new thing that says, I can do all that better than you, that, you know, there, it's natural to imagine there'll be some sort of social pushback. So I think that is just a natural, a natural outcome. But we need to really, you know, there are people, for example, like Jensen at Nvidia who like, pushes very strongly back on this, like, unemployment is coming kind of like argument that, you know, work is going to be optional. And so because. And his argument is basically just every time humans have had sort of these step unlocks of technology, whether you start from the printing press all the way through the industrial revolution, even the Internet, like, we've always just found more ways to do more work. Right? Like you never.
- [20:44]
Jason Calacanis
Monkeys like tools. We are monkeys given a new set of tools. Monkeys will use tools to entertain and themselves and solve problems and murder each other on the margins. It's just basic monkey behavior. Russ, what was your take as we go around the horn here before we get into our Siri 17.0 discussion?
- [21:05]
Russ Dasa
Yeah, yeah, my take, I think there's a few different dots a little bit scattered, but I think the Jensen take, I think is maybe right for this current era of AI. But the line has to end somewhere. It can't just be that every single phase shift there will always be new jobs, there's some end of the line at some point. Is that for this current era? I don't think so personally, but this is one thought. The second is that college is kind of like this almost connective tissue between when you finish college, it's supposed to prepare you for the world out there to get a job. I think that was at least when we were probably all in college. That was the promise of it. And so I think to for with this new technology we have to think about like, how do we assess what college is preparing you for? Like what is the success criteria when you finish college? I think today that hasn't really changed much and we suddenly have like a TI83. But for thinking it's like, I mean, I remember when I was in high school, you take the SAT 2 math and like the entire test can be done on a graphing calculator. But that didn't stop people from continuing to do math or anything like that. Right. It just, the calculator could handle the mechanics of it. But you still have to think. And I think with LLMs it's something similar that it can help you refine ideas. But ultimately I think it's not the final polish. Right. I think that humans are still doing that. And at least when I use LLMs I'm not letting it kind of just generate the thing and spit it out and that's the final product. I always go through a review, even programmers go through review on all the code that is generated for the most part. Well, at least we do. And so I think you have to assess like what are students doing in these colleges and if you leverage these tools, what are we really preparing people for?
- [23:02]
Jason Calacanis
I think yeah.
- [23:04]
Russ Dasa
On the other side of this, my partner, she has two younger brothers who are like 23 years old and 25 years old and you know, they're just graduating and they're out in the job market and they're having a hard time. Like, yeah, insanely hard for them to find jobs. I think they've been looking for over a year, you know, different industries, but it's for the entry level work. I think like a lot of companies are kind of looking down the road and thinking, okay, well you know what, I'm just going to stop hiring or slow down hiring because I really think that like these AI agents are just going to automate away a lot of the entry level work. So I think that that's creating this almost like disconnect between what college is trying to preparing you for. Maybe it's preparing you for the same stuff from 15 years ago that it was preparing us for. And then the job market is also tightening on the other side. So everyone's getting squeezed at that age.
- [23:54]
Jason Calacanis
Stephen, just summarizing everybody's views here and working it out in my own mind, there seems to be a tension between what is the point of college? Is it to actually prepare you for a job or is it to teach you, hey, to find what you're passionate about, to learn how to learn to get those last couple of years of maturation before you leave the nest. If you viewed it in that latter as opposed to the former, you're like, okay, that's a good use of time, right? You're just learning how to learn. You're getting well rounded, bit of a luxury. It's kind of like a luxury vacation. If it's costing you 50 or 100,000 a year. It does seem like kind of crazy to spend that amount on your last couple years of maturation unless you can afford it. But if you look at it like it's there to prepare you for a job and the first two rungs of the ladder have been removed, now it's an even bigger gap, right?
- [24:47]
Stephen Berlin Johnson
Yeah, I think that's right. To me, one of the things I came back to in writing that piece that kind of shows up in the second half, which maybe you'll get to read, Jason, after this is over.
- [24:59]
Jason Calacanis
I will, absolutely.
- [25:01]
Stephen Berlin Johnson
Is kind of building on what Russ was saying, which is like, there's a kind of easy rule of thumb I think, that students could take to figure out to feel good about the AI experience that they're getting in school, which is fundamentally to just imagine that you have a world class tutor, editor and researcher at your side and just treat that AI editor, AI researcher like you would a human, right? If you had a great tutor, you wouldn't sit down with your tutor and say, please write my paper form, right? Like, you just wouldn't do that. But you would say, like, hey, here's some ideas I have. Like, let's brainstorm how I can make this a better thing. If you had a great editor, you'd be like, take a look at this paragraph. Like, how could I do this a little bit? I do that all the time with editors, right? I get so much out of the dialogue I have that I'm lucky enough to have access to actual human world class editors. Am I cheating when the editor gives me feedback and improves my writing? Like, no. That's an incredible like blessing that I have because I get to be a professional writer. So I think if we have that as the kind of common sense framework that ask the AI to do the things that you would ask a valuable, knowledgeable assistant to do for you, but still do the thinking yourself, you will at least get that kind of learning how to learn, learning how to think, learning how to engage with the world deeply. And then, yes, the job. We don't know what's going to happen in the job market, but those skills will be valuable in whatever market ends up emerging.
- [26:25]
Jason Calacanis
Yeah, I think this speaks to Jeffrey. Self reliance, radical self reliance as opposed to I'm part of a machine and I get funneled from high school based on my performance into whatever college is best for my degree slash ability. Then I get funneled to whatever training program at Goldman Sachs or go to Google and then they take me along the road. You're on your own. But the good news is, even though you're on your own, you have an unlimited number of career counselors, coaches, mentors and researchers at your fingertips. It's stunning to me how people, certain folks ask me questions like people who work for me, how do I do this before they're asking Claude and Gemini and Grok and perplexity. I'm asking those tools. What questions am I not asking here? Give me some blind spots. I literally type that in. Tell me what blind spots I have about this health issue, about this business issue. An interesting moment in time for rugged individualism and self reliance. Yeah, Jeff.
- [27:36]
Jeffrey Cannell
Yeah. I mean, I think AI should make you better today than yesterday and better tomorrow than today. And if, if it can do that, then it's serving its purpose well in the world.
- [27:46]
Jason Calacanis
Yeah, it should be inspiring. All right, let's get to the news and the docket. Apple has been MIA when it comes to AI. But at Tim Cook's final keynote. Finally, Tim Cook is done. It's not personal. I just want to see some innovative products come out of Cupertino as opposed to the end of Steve Jobs roadmap and squeezing out every last nickel out of it. Apple unveiled a rebuilt Siri AI. It's a dedicated standalone app. Should have done that a long time ago. It's conversational, it's powered by Google's models and it's shipping later this year. Has the ability to perform cross app actions, that is it has the ability to use the things on your phone, which it doesn't even know how to spell my last name. After a 20 year relationship and tens of thousands of dollars of iPhones bought Apple bolted Google's models onto the iPhone instead of building their own AI. I don't say bolting, but integrated. They're paying Google roughly a billion dollars annually to customize for a custom 1.2 trillion parameter. Gemini model Craig Federighi accuses rivals of quote, pursuing AI for the sake of AI without clear regard for the people it's ultimately meant to serve. So I guess playing into our previous discussion there about being, you know, a victim of AI versus being empowered by AI, they introduced Apple Intelligence back in 2024. It was completely a dud. So here we are. And, you know, obviously there's the capex discussion to add to this. Russ, what was your take when you saw Siri AI, the original agent, along with Alexa from Amazon? Both of those are disgraceful shells of what we see in the modern era and completely worthless and disgraceful products coming from those two great companies. That's my opinion. What do you think, Russ?
- [29:55]
Russ Dasa
Yeah, I don't, I don't disagree with you. I think that even now I watched the keynote and I think it suffers from the same fundamental user experience problem. So look, the voice has gotten better. They had these two sliders, they had pace at which this voice can be customized to talk, and then they had expressiveness or emotion or something like that, but they didn't move the emotion slider at all in the demo. And I'm like, huh, I wonder, maybe that part's not ready, but not shipped yet. Let's say, give them benefit of the doubt. They have a voice that feels more emotional, feels more human, like, so that's cool. And capability wise, I think building on top of the stuff that the Gemini folks are working on is awesome. It's like a level up in the capabilities now by partnering with Google on that. I still think though, that there's a UX disconnect. And it's been like this ever since, like the 2010 or 2011 launch of like Siri slash Alexa. And it's that you don't exactly know what you can use the thing for, right? Like, so all of their demos were demos. They're kind of in a vacuum. And, you know, like one of the examples that Rockwell had was like, he said, oh, okay, like there's like a lottery for some tickets to this event. And then that was it. And it wasn't like, well, how do you know? Can you ask the agent, can you put me in the lottery? Right? Can you go and do that for me so I don't have to go and open the website and fill out a form and all of that stuff like can the agent just go and do this via computer use or some other facility like that that wasn't shown. And it's also like if it was available you wouldn't know it. And so what's punishing about that experience is as soon as you ask, and it was like this in 2010 too, or 2011, when you ask Siri to do something and then it's like, oh, I have a bunch of web pages I can show you to do this thing.
- [31:57]
Jason Calacanis
And it's like so one dimensional and useless.
- [31:59]
Russ Dasa
Forget this thing.
- [32:00]
Jason Calacanis
Yeah, it's literally slower and more cumbersome to use Siri than to use a browser.
- [32:07]
Russ Dasa
And I think the other problem is that it doesn't feel human like to interact with, at least in the demos. It still feels like this transactional thing where I like ask the thing to do something. I wait, it goes and does something and then comes back at the response. I'm like, oh, okay. The next thing, it doesn't feel like a conversation with another person like a lot of the other kind of like voice based AI systems do nowadays.
- [32:28]
Jason Calacanis
Yeah, they're definitely behind Steven. Obviously you work at Google, but you don't speak for Google in all ways. But this does seem to be partnership because when I use Gemini, I speak specifically route any travel, local flights, you know, there are certain maps, there are certain categories of things I just associate with Google doing a great job. Obviously Google Maps, obviously Google Local, obviously Google flights, Google travel, all that stuff is dynamite. And it's integrated extremely well into Gemini. Now it wasn't always like a year or two ago it wasn't. The hooks weren't there, but it seems like the hooks and what web services and what data services you can get to from your voice agent is the new paradigm. Not having to route through a phone in an app. So it's almost like you're forcing. I'm trying to think of an analogy here like putting airbags and three point seat belts onto a horse in a buggy. You're better at these analogies, but the previous paradigm of apps doesn't work in an AI era anyway. So that seems to be a blocker. How would you frame what needs to happen here to make a Siri or an Alexa or okay, Google work really well for customers.
- [33:52]
Stephen Berlin Johnson
It's so funny, Jason, I actually had almost the exact opposite take on it in a way.
- [33:57]
Jason Calacanis
Okay, here we go.
- [33:58]
Stephen Berlin Johnson
Which is. Which is that the thing that. And I didn't watch the very closely but the thing that caught my eye, that I was excited about, and this is maybe more about my long history as a. As a fan of Apple and as a customer of Apple's, sure that I was happy they made a Siri app. And the reason I say that is I feel like Apple has a great history of making new, you know, pathbreaking, like, applications in different spaces. Like, and, you know, going back to HyperCard, which changed my life in 1987. But, like, think about what GarageBand was like. Like, it was such a revelation of, like, what you could do with music, music production. ITunes was kind of like that. These were both apps that were kind of modified from things that they'd acquired. But they, you know, they have a great history of making new paradigms for what applications can be. And I continue to think that there are, like, new application types that are going to be possible because of AI. That's what, that's what we started with with NotebookLM. It's like there's going to be a new, you know, there are going to be a whole new kind of visual metaphors we're going to have and whole new frameworks for how we think about information. If, you know that there's at the center of it. We're not just adding AI to a word processor. Like, we're building something from scratch. It's genuinely new. And so the fact that they're, like, introducing this thing that maybe could become more than just a standard issue, like Chatbot. It didn't kind of look like a Chatbot in the screens that I saw. I don't know, it just. I was excited because I want to see them playing in that space. Like, they do make. They have a history of making.
- [35:27]
Jason Calacanis
As a fanboy, you want to see them in the game. Not like they're not making the playoffs. Like Apple not making the playoffs. It's like the Knicks not making. Making the playoffs.
- [35:36]
Stephen Berlin Johnson
Yeah, they didn't even make. They sat out two seasons, Jason. They didn't even play. I mean, on some level, like, I hate to say it, but, like, there wasn't a product that was there. And so, and I know there's such creative people there, like, and, you know, like, we, I think at Google, at DeepMind, the Notebook team, the Gemini team, like, we're inspired by things that Anthropic is doing. We're inspired by things that OpenAI is doing. We like to see ideas circulating and, like, we just weren't getting anything out of Google. For Tito, in terms of the consumer
- [36:09]
Jason Calacanis
products, it's kind of A bummer, right? You want them in the game.
- [36:12]
Russ Dasa
I like that.
- [36:12]
Stephen Berlin Johnson
I like to see them creating.
- [36:15]
Russ Dasa
I'll tell you what the coolest thing was, in my opinion, that they showed in terms of like a new kind of interaction model was the Siri integration on the Vision Pro. You don't actually have to say anything to engage it. It's just always floating there. And then you just look at the thing and you just start talking to it. And it understands when you're looking at it because of the eye tracking, and it just engages. And so that felt really cool as an interaction to kind of see happening right there.
- [36:41]
Jason Calacanis
Here's what I want to do, Jeffrey. I want to. And this would be against all privacy and all of Apple's ethos, I think at the moment. But hear me out. This could work. They get the iPhone to the level with the Apple silicon and the amount of memory in it that it can run. Let's assume they this Google relationship, which is now, you know, a very old relationship with surge or whatever, they get Gamma on the phone and I can tell it record everything on my phone, and they already have like a little box that says Apple Intelligence. And you can flip it for different apps. And I guess theoretically it's learning and everything that occurs in its learning is encrypted on my device. And then, you know, obviously you can put it in my icloud, but it's encrypted. If it's. They get asked to crack it or give it to the government. It's just like the San Bernardino shooting where they're like, yeah, we don't have the keys. It's. You're going to have to go find somebody to crack the keys for you. We're not capable of doing that. This would be amazing if it recorded everything I did on my phone and understood like, okay, yeah, I play chess during these time periods. I have this many open games. These are my weaknesses. I have these flights coming up. I use this app. I used Hotel Tonight when I was in Los Angeles. But I opened Conde Nast Traveler in my browser and I bookmarked three or four things like the insights it would have, combining my desktop with my phone, with my watch, with my habits in Apple music and icloud my photos. Man, it could be a truly powerful assistant, but I would have to give it access to everything. And you know all about that, Jeffrey, running Hermes, where people do have that concern, et cetera. So what's your take on what would make Siri extraordinary as Stephen wants it to be as an Apple fanboy.
- [38:37]
Jeffrey Cannell
Well, it certainly has something to do with like, the end user product experience, right? Like, that's the one thing that we know that they've been able to consistently deliver. You know, I will comment as a side note before I answer. You know, it has been interesting when you talked about how they set out to two. Two rounds of like the AI race, you know. You know, people kind of, you have to wonder, like, was this either like the world's greatest bag fumble or are they like, playing 10D chess and like, really understood that, like, there wasn't like, because what would have been the standard playbook, right? Everyone was like, we got to go, you know, we have to train our own models too. We got to go spend, you know, raise a trillion dollars, you know, to go build all these data centers. And like, did you need to be a fourth or fifth player? You know, some business people say, well, we need that. We need that intelligence in ourselves. Like, we have to be able to do it ourselves. We can't rely on an external partner. But maybe, you know, as, you know, sort of these, the model costs for training these frontier models just continues to get higher and higher. You know, it's possible that Apple was like, you know, has made the. Made the right choice by sitting out there, is not going to play. We're not going to play that game.
- [39:37]
Jason Calacanis
There is some historical context here, you know, you remember, I don't know if you're old enough, Jeffrey, but Bill Gates was running around when he was CEO of Microsoft with a tablet, with a stylist with a pen showing off a touchscreen Windows device that crashed. And then they had their little Windows HP personal assistant. What was that called, Stephen? The Windows on that? Personal assistant? Windows ce, maybe.
- [40:03]
Jeffrey Cannell
Windows CE was the mobile platform.
- [40:04]
Jason Calacanis
That was it. Okay, great. So, Jeffrey, you are old enough. Either that or you're a student of history.
- [40:08]
Jeffrey Cannell
I'm 38. I'm old.
- [40:11]
Jason Calacanis
So you were like 8 years old when this all went down. But anyway, putting it aside, maybe you are playing with Windows CE at 8 years old. Steve Jobs was like, you know what? I'm chill. There it is. I mean, put it back up on the screen for a second. Let's all just ponder what we're looking for.
- [40:28]
Stephen Berlin Johnson
Why was that not a gigantic hit? I mean, it.
- [40:30]
Jeffrey Cannell
Just look at it.
- [40:32]
Jason Calacanis
I mean, I feel like. I feel like I'm in the army and I'm setting up, calling it a nuclear strike area. Yeah, the Newton as well. Look at those Chiclet keyboard. Oh, my God, those were brutal to touch. Those keys, it took like three or four times to get a space in that space bar. What a disgraceful product. But Steve Jobs saw that and he was like, yeah, not ready. And then all of a sudden he's like, yeah, you know what, congratulations on your, you know, all your special books and tablets. I'm going to come out with a tiny one called the iPhone. Shout out BlackBerry, shout out Nokia, which were N95. All that stuff's great. But yeah, he sat it out for four or five years and then boom. IPhone, perfect. That could be the play. Here is their partnership with Google gives them access to lots of compute. And they did the same thing with search, right. They're like, we don't need to be in the search engine business. We can just have a great partnership. And they become a key player in driving distribution.
- [41:33]
Jeffrey Cannell
Yeah, they do. They so distribution, great. They actually are also, you know, focused somewhat on the open source side a bit with their MLX platform with the Max, which basically is their own platform for running local models on Apple Silicon. So there's, they have invested in the open source side somewhat. You know, there's, there's always this question about, you know, can you run stuff like this totally in the cloud or like, is the latency requirements going to essentially dictate that a lot of things move onto the device and so it'll be interesting to see which way it goes. But certainly the open source models right now aren't in a space where they could record everything and have all your context. But as we've seen in the space, it's legitimately only a matter of time. Right.
- [42:18]
Jason Calacanis
Where does your project and Siri conflict overlap and how do you think about it? Because I would look at what you're building with Hermes or openclaw as the most open extensible platform for what Siri and Alexa should have been. Sure, a little more complicated, but when I introduced you on the program, hey, fit and finish and polish is something you're working on. So how do you think about getting Ermes Agent onto iPhones and beating Siri? How do you beat Siri from taking your business, Jeffrey?
- [42:54]
Jeffrey Cannell
That's a good question. Now Apple has made it clear that if they want to win, they will win because they own the device and they'll make the final call. Right?
- [43:02]
Jason Calacanis
You're saying they'll ankle your product.
- [43:05]
Jeffrey Cannell
So really I think a lot of it is just about where we're framing. We look more on the desktop application power user side right now as sort of like self modification. So for example, one Thing that we put forward is the agent able to change itself dynamically where it's actually able to modify its own code, change features like that, and something that probably doesn't fit within like a pure customer user, you know, like a full iPhone experience. So I think they can be complimentary for now, but certainly the thing that they showed off about it, like controlling all your apps, that's something that we're. Desktop and computer usage is something that we're working extremely hard on. Because if you think about it like we spent the last 15 or 20 years forcing all of the white collar economy into these that can fit onto a screen, right. Like everyone does their whole job just through a laptop screen essentially. Right. So theoretically, you know, all the tools are there on your computer to like do everything that people could say to you to be valuable. Right. So I think that, you know, we're going to be entering into this new era where we have the scaffolding of the, of the apps and the, all the old programs, the websites that were meant for humans to use. Right. And the scaffolding has been built up and now the, the agents will be using this scaffolding for some period of time. But it may be that this is not like the final form factor. And I do think there's going to be an incredible amount of, of innovation on the UX side. And I didn't even see the keynote, like for example, what you guys mentioned about, you know, just looking at the agent, you know, looking at a specific piece, part of the screen and that like engaging it. That's like the kind of out of the box thinking that I think can drive new, can, can not only like make AI more, it makes AI more useful to people because it gets them into the funnel without having this sort of janky experience that we're used to.
- [44:41]
Jason Calacanis
Ross, who's going to win this agent race? Is it going to be a third party who crosses across all platforms, doesn't own the platform, like OpenClaw, Claude Code, you know, pick your favorite agent. Hermes, obviously. Or do you think Apple winds up winning? Or maybe people have both. You know, they use Google Office, Microsoft Office. And Apple has an offering. I don't know what it's called, I'm sure.
- [45:08]
Russ Dasa
Well, you know, I think like I
- [45:09]
Jason Calacanis
have a, some people use it. Apple Write. What is the Apple word processor called?
- [45:15]
Stephen Berlin Johnson
Pages.
- [45:16]
Russ Dasa
Pages. Pages. Pages, yeah. Yeah, that's right.
- [45:18]
Jason Calacanis
I think there's one person on this call who still uses Pages. Do you write your books in pages, Stephen?
- [45:23]
Stephen Berlin Johnson
I know I'm writing them in NotebookLM now, actually. But that's a whole other thing.
- [45:26]
Jason Calacanis
Fascinating. I'm gonna double click on that later. Apple pages.
- [45:30]
Jeffrey Cannell
Go ahead, Russ.
- [45:30]
Russ Dasa
Who's gonna. I, I have a. I don't know if it's a controversial take, but I have a take.
- [45:35]
Jason Calacanis
Take.
- [45:35]
Russ Dasa
All right, so here's my take. It's a bit higher level, though. I think that the one that transcends devices for agents is going to win. Not the device specific. In Apple's case, they're incentivized to be device specific because they got to sell devices. That's like their bread and butter and that's their cash cow. But so here's my take. Let's say that the goal of this current era of AI continues to get better and better is to automate jobs that we don't want to do. Right. Let's just imagine for talking purposes, that's what the ultimate goal is. Agentic AI. So digital workers want AI agents that are confined to the digital world. They run inside computers, they can use computers. All of that stuff, the jobs to be done there, to be automated, are all related to work. All the things that humans don't want to do is all this work stuff.
- [46:31]
Jason Calacanis
And then
- [46:33]
Russ Dasa
in your personal life, on the consumer side, the work that you don't want to do are like the dishes and like folding laundry.
- [46:40]
Jason Calacanis
Chores.
- [46:41]
Russ Dasa
You're referring to chores, right? Like the rest of your time in your personal life is mostly just entertainment. Apple builds amazing devices for consumption of content for entertainment. Right. But like it really boils down to agentic AI is really for the workplace and the enterprise and all of that. And then physical AI or embodied AI in the form of humanoid robots is what's going to automate all of the work in the physical world in your personal life. And that's where I think the two big, call it economic value drivers, they're going to kind of accrete to those two specific buckets. And so in that world, if that is true, then I actually don't think that Apple really has a play here because they're not really focused on the enterprise from a Gentec AI perspective and they're not even really focused on robots from a kind of like personal life chore automation perspective.
- [47:32]
Jason Calacanis
And so that would be the ultimate mind blowing win, huh? Stephen Berlin Johnson, if the new CEO forgot his name of Apple, who is a real hardware engineer.
- [47:44]
Stephen Berlin Johnson
Hardware guy. Yeah, yeah.
- [47:45]
Jason Calacanis
He just said, yo, by the way, we're making a robot. We're in the game. You're going to go to the app you're going to go to the Apple store and there's going to be robots walking around selling you watches and you can walk out with one.
- [47:58]
Russ Dasa
Maybe that's why they're slow playing AI so much. Right? Like the AI agent stuff. They don't really care. They're in the lab working on the robot already.
- [48:04]
Jason Calacanis
Who understands consumers better, Steven? Like for chores. If we take Russ's framing as like, these things are great for chores you don't want to do. Will Apple get into the human robotics space? And who would you rather buy a human robot from? Is there a brand you would rather like have a Samsung or a Toyota or a Tesla?
- [48:24]
Stephen Berlin Johnson
You were really excited about Elon's robot.
- [48:27]
Jason Calacanis
I'm excited about all the robots, frankly, because I have a ranch and there's a lot of work on the robots
- [48:32]
Stephen Berlin Johnson
and there's a lot of brush to clear.
- [48:34]
Jason Calacanis
Literally I was out there cutting the grass, which I love doing.
- [48:37]
Stephen Berlin Johnson
It's cool.
- [48:37]
Jason Calacanis
You're like Reagan mowing therapy. No, no. You're going to find this hysterical as the Brooklyn Grinder now living on a horse ranch out in Texas. I love getting on my ride on mower and just riding around and cutting the grass and making a Hank Hill Life, huh? Oh, I love it, I love it. It's therapy.
- [48:57]
Russ Dasa
You could ruminate and go to travel time.
- [48:59]
Stephen Berlin Johnson
Travel back to 25 year old Jason
- [49:02]
Jason Calacanis
in black at coffee shop at price.
- [49:04]
Stephen Berlin Johnson
This is your future, man.
- [49:07]
Jason Calacanis
It's just literally like I'd be like, what? That's some corny shit.
- [49:10]
Stephen Berlin Johnson
I think you're confused.
- [49:12]
Jason Calacanis
I'm so confused. Take us home on this one with agents. Are agents just WYSIWYG boxes and web pages and, you know, just a commodity. And we're so enamored with this concept that we're thinking somebody has to win it, when in fact it could just be like, like I said, a WYSIWYG editor. Every product has one and it's a commodity and they all work relatively well.
- [49:35]
Stephen Berlin Johnson
Yeah, I guess I was kind of leaning in that direction, Jason, when you were asking like who's gonna win the agent thing, it's like, it's a bit like asking like who's gonna win the website thing. Yeah, like they're going to be everywhere. Like we. So I tell you how we're thinking about it in terms of notebooks. So we just rolled out this thing I mentioned earlier yesterday, which is like the biggest change to how the product works and effectively. Before we had kind of three agents, right? We had an agent that was really Good at, like, looking at your sources, helping you understand your sources, finding the information you need, summarizing, explaining. We had an agent that was great at making things like audio overviews and slide decks and things like that. And then you had a research agent. We had a deep research agent that would go off and research. But the problem was they were three separate things and they didn't really talk to each other. And so we've integrated them all into kind of a single agent that you can experience in the chat. This is, as of yesterday, just for Ultra users, but we're coming to more users, but basically. So now the agent knows your whole chat history and what you've researched and all your sources and the artifacts you've made. And so it lets you do precisely the thing you were talking about before, Jason, about asking about blind spots. I can go in there when I'm in research mode, and I can be like, hey, okay, I'm trying to figure out this problem. What are we missing here? What's the thing I haven't thought of yet? Because it knows weeks and weeks of our conversation on the chapter I'm trying to write, or because it knows the sources that I've already assembled and what I've done, It's able to actually help me see around those blind spots and find the precise thing that I need, which is the fact that you can do that kind of negative search. Like, I'm searching not for a keyword, but I'm searching for a topic. I'm searching for a thing that I can't tell you what it is because I don't know what it is, and it actually is able to fill in those gaps for you, like, just as a researcher alone. That is such an incredible Godsign. It's like some eugenic work is so, so exciting to me.
- [51:25]
Jason Calacanis
It's super exciting because it's like having a. A personal coach or a professional coach who's like, yeah, you're getting better at chess, but here's some heuristic. It's not even in your mind. Let me blow your mind by telling you how to think about the openings, for example, in chunks, right? And the great chess players are not thinking three moves ahead, they're thinking three chunks ahead. Okay, we're going to exchange these pawns. Then that's going to unleash the rooks. Then that's going to unleash this pin that I've got blocked. And they're thinking in those chunks of heuristics, that's like, what's going to happen? With these agents, they're just like, hey, you're thinking about this in a very ABC way of playing poker. Let me explain to you. Poker is even the better analogy because you learn it by losing money, et cetera. Just what am I not thinking about? In some ways, it's almost like what super intelligence would be. Jeffrey, if we define AGI as, like, being like, I don't know, the smartest human at Google, the smartest human, you know, at news. Okay, great. You're the smartest human here. Congratulations. Everybody hates you, or people think you're weird, fine. But being so super intelligent that human intelligence is not comparable to what you're doing. In other words, we can't comprehend how you're looking at the field that's kind of upon us now. I think we're starting to emerge this year.
- [52:48]
Jeffrey Cannell
Yes, I would say certainly we are. Like, what I would. I tell people we're at, like, a functional AGI level. It's unevenly distributed among the tasks. But on certain tasks, like, it's as good as the best, you know, people that there are. And you only have to look at, you know, the people who actually are at the top, who are, you know, your Terry Towers and stuff like that, who turn around and say, like, look, I'm the best there is. And I'm telling you, this thing is as good as I am. You know, like, you sort of have to have that level of, like, cache for people listening. But. But, I mean, personally myself, you know, I'm like mentioned earlier, I'm 38 years old. I started writing BASIC when I was like, eight is what I did all day, every day for the last 25, 30 years of my life. It was what I centered around, my own professional identity on everything that I did. And only within the last three to six months, I no longer really write code in the same way that I used to. And that's because it finally got as good as I am. But the thing is, rather than viewing that as like, this defeatist moment of like, oh, my gosh, what are you do now? I get to be like, an even better version of myself because now I can do 10 projects when I used to only be able to focus on one. And so, like, rather than viewing it as, like, it's like I get to rewind the clock and be eight or nine again, you know, and I get to start over. So I just think people need to come at it from that way. But speaking, Stephen, about what you said, you know, I do think it's interesting because, like, all of that is just an emergent property of the model. Like, we're, we're the agent harnesses. We do are kind of like, you know, we're putting some stuff around it, but all of it is completely pointless if the model itself can actually do it. And so many of these, like, new use cases just sort of silently get unlocked as the models get better. Like, there's no, like, specific spot, but all of a sudden it's good enough to notice what it is that you haven't said. And it has, you know, I'm sure, functionally a million window context length. So it actually can take everything in. Whereas, like two years ago, you know, you had your 32k context length, if you were lucky, so you had to do all these other like, you know, hacks and stuff. And just things sort of like frog boiled to the point that we are functionally at AGI at several categories. And yet it's interesting because, like, the world is different, but it hasn't completely broken either. Right? And, you know, maybe, you know, we actually are in like a trajectory where it's all going to be okay, even with the hyper ASI sort of things coming.
- [54:56]
Jason Calacanis
Feels like it's going to be okay. Russ this week, and I went down the rabbit hole of building apps and I was just thinking all the things I had asked people to do two or three years ago and was like, yeah, we don't have the time or budget or team to allocate towards that web interface, agent, researcher, sdr, et cetera. And I just, with my pedal, which I have a pedal under both of my desks here, and whisper, I just started talking stream of consciousness into Perplexity Computer and Claude Cowork would cut one into the other and just said, build me these. And then I looked at the two outputs and I put like three or four jobs into each. I'm paying for the two or $300 version of both. I put two or three jobs into each. I queued up a bunch of things. I looked at the output and I was like, oh my God, I was considering spending a quarter million dollars building this piece of software or hiring two people, which would also be a quarter million million dollars. And I just built it all and it's running in the background. Whoa. And it's actually working. And when we tried this with OpenClaw in January, February, March, it sometimes worked, but was brittle and broke. Something's happened, I think, in this year, very clearly in the first half of this year, where this stuff went from brittle to brilliant.
- [56:20]
Russ Dasa
Oh, yeah. Boris Czerny talks about this, the Claude code creator. The first chasm was sometime in the summer of 2025. But then when 4.5 opus 4.5 hit is like when he started to write significantly less code. And then I think 4.6, I don't think he's writing any code anymore at all. He's been doing these interviews where he's been talking about that. It's interesting with your pedal, if you think about it, you have this early version of jarvis that's kind of how you're interacting with the computer now, where you're just telling the thing, literally speaking to it and saying, hey, build me this thing. And it's just generating the thing after a few minutes. And then you go in and you can refine it. You can fine tune it. You could even look at the code that it generates if you want to. But this is the very early version of Jarvis. In 10 years. Just imagine what it's going to feel like to create things. It's just. It's going to be this incredible experience.
- [57:20]
Jason Calacanis
Here's the tweet from boris. I use Opus 4:5 with thinking for everything. It's the best coding model I've ever used. And even though it's bigger and slower than Sonnet, since you have to steer it less and it's better at tool use, it's almost always faster than using a small model. That was 1-2-5.
- [57:38]
Jeffrey Cannell
Like, before you even said it, I was going to jump in and say 4.5. Was it like that was the line where suddenly, you know, it's. It's funny because if it's. If it's even like 2 or 3% less good than me, well, why would I have it make something not but like, once it's even like 1% better than what then, like, why would I ever do any, you know, why would I ever do anything myself at all? So. And it just kind of four or five is when they cross that line and it's just been gas. And I think now we have maybe Fable out now today. We'll see. So it's going to get even. Only gonna get even crazier.
- [58:05]
Russ Dasa
Jeff, I think it'll be. Yeah, I was gonna say Jeff, I think it'd be interesting, like, you know, with Fable out, like how your harness evolves too, just because, you know, one of the other things that Anthropic talks about with harness design is that as the models get better, you just keep kicking stuff out of the harness. Like, it just all kind of like, you know, becomes more and more the purview of the model versus the harness itself.
- [58:27]
Jeffrey Cannell
Yeah, I mean, I think obviously, like there's going to be places for the harness to be useful in the sense of connecting it to the quote unquote, real world. The real world being like, you know, the digital actual world. You know, I think there's certainly there is a future. Like, if you asked me 15 years from now, there is no reason why we couldn't have full model architectures that can speak and read TCP IP packets. They're multimodal. They literally could be the entire brain. That's probably. We're still a few generations away from when we get to there. But obviously, yes, everything else was sort of like the scaffolding to pick up where the model's emergent capabilities left off and you can just kind of delete more. Let me give you a per. For example, suppose now fable is still a million contact context length. Suppose we got like 10 million context length and it was like 10 times cheaper, right? You had 10 million context and like 10 times cheaper. Then you'd be like, well, why even, why even. Like just record everything that's ever been. Like you said, you get into this, record everything that's ever been said and just that is your context. And you know, we don't even need to like have sessions and you know, be clearing all the do compaction and all these other stuff that we still have to kind of, you know, pick up a little bit. So certainly it's only going to get less and less handholding as the models get better. And like I said, 10 years from now, I imagine there will actually be like the final, the final boss to be defeated of the old guard is the operating system. Right?
- [59:44]
Jason Calacanis
Like, oh, that's interesting.
- [59:46]
Jeffrey Cannell
Yeah.
- [59:46]
Jason Calacanis
Can you get down to the operating system level and just take a hardware platform?
- [59:52]
Jeffrey Cannell
Yeah, yeah. And it would need to be fully multimodal. Like I said, it has to be able to be able to speak TCP packets, render video at real time. You know, all of these need to write 60 frames per second, 4K video real time. All these things sound crazy except for the fact that we have, you know, quality, we have human level hyperintelligence of coding. When eight years ago, you know, you had the XKCD comic about we can't tell what, you know, what bird colors are. So it's like, there's not, it's not crazy to project that far out 10 years and be like, it might actually
- [60:20]
Jason Calacanis
as a way to frame this, Stephen, if you took everything we did in Web 1.0, you know, just take the top 200 websites and you gave it to one person with unlimited tokens. Right. Now I would say every hour they could rebuild every one of those sites, which means in but four or five weeks they could have rebuilt every innovation for the first, I don't know, five, six, seven years of the Internet. Then you fast forward a year from now. What would it be capable of doing? To Jeffrey's point, maybe you could just build the operating system, take out an old laptop and say, hey, make me a new operating system here on this laptop and I'm going to compete with Windows and Linux. I mean, it's kind of a weird moment to frame it that way.
- [61:06]
Stephen Berlin Johnson
Yeah, well, also on the UI level too, Jason, I would say, yeah, the underlying operating system. But what is the kind of basic visual metaphor? Like it's something I've been obsessed with forever. I wrote a whole book about computer interfaces and we've kind of been like, okay, we're going to standardize around these particular models. There's a browser and hypertext model, there's a like Windows model and stuff like that. But maybe the future AI kind of will just spin up the perfect UI for you. Given the project you're working on that looks like nothing that's ever come before, but because it knows that you are actually working on this kind of project with these competing needs and you have these tasks that you're trying to do, like it will invent a whole new service for you on the fly. Like that's, you know, to Jeffrey's point, that's imaginable now, you know, whether we want that, whether people want to have standards and a traditional way that they use a computer so that they feel comfortable or whether they want that open ended space, probably they want both.
- [62:05]
Jason Calacanis
Wow. Yeah. The interface is adapting in real time to your need. All right, let's talk a little bit about token maxing. Jeffrey. People are going wild. Uber decided Andrew McDonald, I think their CFO president was like, oh no. President was like, you know what, you used up all your tokens in month four. We're going to ration them now. You blew out the budget. Supposedly there was some report of Amazon potentially blowing through like hundreds of millions of tokens and somebody forgot to close the faucet in this metaphor. And then some people just saying, hey, the amount we're spending is not equaling the actual output. What's your take, Jeffrey, on the value of token maxing? And if you should just, just YOLO it or people need to be more thoughtful about it.
- [62:56]
Jeffrey Cannell
Well, I think, you know, in a corporate environment, especially at a large corporate environment, you know, there is sort of a failure case. And I think we're starting to see this failure case, which is if you have a, you know, you have an employee and now you give them an unlimited budget, they'll do their entire job with that budget. Because it's just easier to say to the computer, hey, do the thing. Hey, do the thing. Hey, do the thing. Keep saying, hey, do the thing until it does the thing. And if the output you get is just replacing what that worker previously was going to be doing, you know, like, you're getting the same output, but now it costs twice as much because you have to pay their salary for them to sit and turn on the computer and say, hey, do the thing. Hey, do the thing. Like, what have we actually got here? You know, so there's affiliate case where if people can just be lazy, like, you know, water goes downhill, right? And, like, there's a lot of that. That if you enable it in an irresponsible way, it will go downhill and people will. You'll get maybe like the same output for twice the cost. And that's certainly not what you want. So I think what's important is to be identifying the. You know, what we do at Noose is we have budgets for people, but there are people who are worthy of 10x the budget. You know what I mean? Like, and how do you determine that?
- [64:02]
Jason Calacanis
How do you determine that?
- [64:03]
Jeffrey Cannell
Yeah, I mean, I don't know how you do it at scale, to be honest with you. We do it at Noose because we have 40 employees. I know all of them. You know, I can. I can do it. So, you know, a couple of like, like Technium, who's like the lead maintainer on hermes agent, spends 10 times his salary on tokens, and it's worth millions
- [64:20]
Jason Calacanis
of dollars on tokens a year.
- [64:22]
Jeffrey Cannell
Well, we're pretty lean shops. I wouldn't say millions, but let's say around a million dollars on tokens, maybe annualized, and it's totally worth it. Totally worth it. Would spend it again in a heartbeat, right? But now if we have a junior developer who is, you know, spending, you know, three days to just, you know, center a div on a thing, and they're just telling, you know, opus, move the file. You know, instead of copying, you know, opening up a browser and copying it themselves, then, like, we got a problem here, right? So how you tell, I think is still an open question at scale, but it's certainly something that I think is a problem that will need to be solved.
- [64:58]
Stephen Berlin Johnson
Russ Jason, one thing to just quickly jump in kind of brings us back in a way to your original question about the booing and the. And the AI backlash and the booing at the graduations, in the sense that the reason I think these things are connected is that in that backlash, there is a conception, largely among people who haven't been using the technology recently that the tech companies are foisting this unwanted AI technology on the public and spending all this money on data centers and all this kind of stuff when nobody actually wants to use this thing. And that's, you know, this is not something you would hear in this podcast, but, like, if you go outside of the tech bubble, you hear that all the time from people. I hear that from my New York friends all the time. And I think what hasn't been explained enough is that the reason that these data centers need to be built is largely because there is so much demand. Like, there is so much demand for these things. Whether it's the extreme of token maxing or just people like, we at Notebook are just, we have so much more demand. And so people want to use these tools. And that's why there is this incredible increase in spend. It's not because we're inventing a fictitious market that doesn't exist.
- [66:08]
Jason Calacanis
In some ways, I look at this like water, Steven. In America, I invested in a company that did water monitoring and it failed. And then I had another one and it failed. And I was like, but water is this incredibly precious resource and everybody wants to save water. And we're constantly talking about it and hand wringing. And then I realized it's a tragedy of the commons type situation. We actually don't. Nobody even knows what their water bill is. If you get to the point where you know what your water bill is because you're a golf course or you're planting almonds, you then go bribe some politician to get a special dispensation so you no longer have to worry about the cost of the water and what we really need to be doing. And I think it's the whoever had the water runs downhill. I think that was you, Jeffrey, analogy. It reminds me exactly of that if you go to somebody who owns a golf course, they just let the sprinklers run because they're not. They got some dispensation for their golf course. If you talk to anybody in the almond business, they're like, well, we don't pay what you pay for water. So Effort. We're going to make almonds. Is it almonds that use all of the water?
- [67:19]
Russ Dasa
Yeah.
- [67:20]
Jason Calacanis
By the way, almonds are a completely mid nut. Like cashews.
- [67:24]
Russ Dasa
Very mid.
- [67:24]
Jason Calacanis
Much better. I'll take a peanut. I love a good peanut in dark chocolate. I mean, I could give you 20 nuts with macadamia.
- [67:33]
Stephen Berlin Johnson
Let's just rank our favorite nuts, I think.
- [67:34]
Jason Calacanis
What do you got? Macadamia, cashew. Where are you at? I'm a pistachio guy.
- [67:39]
Russ Dasa
Pistachio is great. Macadamia is up there for me.
- [67:42]
Jason Calacanis
I mean, there's so many better nuts that are more water efficient. And these with the almonds. Sorry, bleep that out. They're just so selfish. They're like, yeah, we're just gonna use all the water and then we're gonna complain about a closed loop data center water. It's just absurd. Russ, your thoughts? And first, I need to know your favorite nuts.
- [68:00]
Russ Dasa
Yeah, macadamia is probably my number one, but super fatty, so I don't eat them very much. I think similar thoughts with Jeffrey. I mean, we have budgets, but then there are folks on the team who we kind of let them do whatever they want. And I think the general feeling is this. I think for the line of work that we do, the value of the token is so high. Right? Like just the output that, you know, an amazing engineer can have. They, you know, they have that whole like 10x engineer. It's like it turns them into a thousandx engineer or whatever when they. When they have AI kind of at their back. And so I think that it's. It's one of those things where we don't really, for the best engineers on our team, we don't. We don't really care. Like, they can, you know, spend whatever they want.
- [68:49]
Jason Calacanis
What's the max somebody spent in a. Must be in a month? Be honest, Russ, because you got the bill. Yeah. One person max spend.
- [68:56]
Russ Dasa
It's not that bad.
- [68:56]
Jason Calacanis
Bad.
- [68:57]
Russ Dasa
Maybe like 10 to 15k. It's not that bad.
- [68:59]
Jason Calacanis
Oh, that's it. Okay. Yeah, yeah. That's like, you know, whatever, 150k a year. Yeah.
- [69:06]
Russ Dasa
It's not terrible.
- [69:07]
Jason Calacanis
It's not terrible, but I think this is. Have any of you experimented with running local models and just saying, you know what? We're going to spend $5,000, $10,000 on a workstation, which is like a fancy way of saying a beefy PC. I was having this conversation with Michael Dell and with Jensen from Nvidia. Dropped two names at once in the same sentence. But I was Talking to both of them about this concept of like, isn't this your opportunity to sell everybody a $20,000 desktop running a local model so they can token max without looking at the register. How close are we to that possibility, Russ?
- [69:45]
Russ Dasa
Well, I think maybe Jeffrey has more in depth thoughts on this just because I think he's probably closer to having played with all of these models. But my general take is that the local or smaller parameter models are just not that good in their quality. Let's talk about for coding agents. I just don't think that they generate the same value of token for these smaller models. I do think that they have their place. Like I'll give you an example as it pertains to Voice. All of the Frontier Labs now, you know, coding agents is the most lucrative type of agent. Voice is actually second after that. But coding is the number one. And all the Frontier Lab models are in favor of like having better, higher quality tokens through more thinking. They're kind of sacrificing time to first byte. So the speed at which you can generate that token. And for a voice based interaction, you actually want something that favors speed to a degree as well as quality. And so these smaller models, like a Gemma 4 or 31B have pretty solid quality on the conversational side, but also a much better time to first bite, which is important for speech, but then again for coding agents, I don't know if that's true for these local models.
- [71:02]
Jeffrey Cannell
Yeah, I think for the coding things, people kind of, I look at it, I want my engineers using the best. Right. And you know, the second fable come out, I'm telling our best guys to switch to that. Right? So like, it's already like expensive as it is. It hasn't like sucked out that like, I still would be willing to spend more if it could be better. So.
- [71:21]
Jason Calacanis
And you spent a million with one person, you spent a hundred thousand in a month with one developer.
- [71:25]
Jeffrey Cannell
Yeah.
- [71:26]
Jason Calacanis
And you're willing to spend more?
- [71:27]
Jeffrey Cannell
I'd be willing to spend more for him. Yeah, I'd be willing to spend more for him. And so, so for that, you know, I think it's the local story is a little bit different. You know, it's about finding who's that person who would spend $20,000 but wouldn't spend, you know, more than that. It's a little bit difficult. And the real thing is we're still scaling. That's the problem, you know, is that like we're still making the models. We make the models bigger and they just still get better. The bigger we make them and we throw more debt. So, like, if we'd hit like some sort of plateau and we could have a compression event, maybe. But like, we're talking in the era of, you know, the next. The Vera Rubin chips that are coming out, you know, they're, they're designed for 10 trillion parameter models, basically, just like the current gen were designed for trillion parameter models. You know, we're setting it up for 10 trillion parameters to the next. And I'm. I'm guessing five minutes will be for 100 trillion parameter models. So, like, at that scale, until we hit some scaling wall, it's a little bit difficult to see how this train doesn't keep going in the direction it is.
- [72:24]
Jason Calacanis
Is. Yeah, it feels like it's heading there. All right, let's. Let's wrap with bad VC stories. This is like the crazy trending topic on Twitter. And I, I don't know. I think it started with Greg Eisenberg describing a GP falling asleep. And then Mark Pinkus had a VC fall asleep. I had John Dorf fall asleep, famously, actually in a meeting with me, but it was actually when I was doing Mahalo Human Powered search. He had gotten in a biking accident in Woodside that morning, flew off the front of his handlebars. He had his arm in a sling, scraped down his face with a bandage, and I guess he had taken some kind of painkiller and he nodded off during the meeting. His partner subsequently came to me and said, john fell off his bike. That's a. You know, and he's just very sorry. And I'm like, why did John Doerr show up for this meeting if he fell off a bike? He's like, he's going to the emergency room after the meeting. He didn't want to insult you by not showing up for the meeting. I was like, wow, that's a great one. But I'm curious, you know, you've run companies before, Stephen, and obviously Jeffrey and Russ, you're in the game right now. Any crazy VC stories that could top the ones we're seeing right now?
- [73:45]
Stephen Berlin Johnson
Most of my VC interactions, my main VC outside in the company was Fred Wilson. So I have only great stories about Fred Wilson, who.
- [73:52]
Jason Calacanis
He's awesome. He could be a little spicy, though.
- [73:53]
Stephen Berlin Johnson
He could be spicy, but he was
- [73:55]
Jason Calacanis
give us a spicy Fred story.
- [73:59]
Stephen Berlin Johnson
I just was reminded of another story that Biz Stone told me that I love, which for co founder of Twitter. And he was raising money for this thing he did called Jelly. And it was this dream where Bono from U2 was like, affiliated with, like, Elevate or some kind of partners. Like, so he was like, briefly a VC as well as an international.
- [74:16]
Jason Calacanis
And Al Gore was a vc. This was the age of the celebrity Ted vc.
- [74:20]
Stephen Berlin Johnson
So Biz told me this story about how he was pitching Botto, like, on a voice call. And Botto's like, okay, Biz, lay it on me, man. Lay it on me. And he's like, wait, Biz, I want to lie down so I can listen to it while I'm lying on the floor so that your ID will wash over me. He's like, I'm lying on the floor, Biz, I'm lying on the floor. Lay it on me now.
- [74:40]
Jason Calacanis
Just pour it over me. Like, oh, man. Wow. Yeah. The age of the, like, a list. Celebrity VC kind of good that it's over. I think in some ways now. A B level. No disrespect to Ashton Kutcher. He's not A list. I'm D list. He's probably B plus. Like, he's been in a couple of movies, but he's not a leading man. But on a TV show, maybe would be the leading man. That's perfect because they're hungry and they're going to do the work. But if you're a Bono or like Al Gore, you're like, hey, let it wash over me. Russ, you can abstract these stories. Yeah, Stephen, I want a spicy Fred Wilson story. He can get spicy, but I definitely
- [75:23]
Russ Dasa
won't name any names other than I've pitched Ashton before and he was great. You know, he took the meeting, taking his kid to. To a summer camp, and his kid was wearing, like, a bear suit. I don't remember why, but that was fun. But he was great. He rallied, joined that meeting. So nothing bad to say about Ashton, but yeah, one, I got a few
- [75:47]
Jason Calacanis
of these, but no, the one that you're just. I could see when you look down as a poker player, you're considering, should I go all in with this story or not? No, I'm going to give you permission to go all in. Don't say the name. Name abstract.
- [76:00]
Russ Dasa
Yeah, I'm not going to say the name, but all top funds but one that I pitched. I remember it was just the worst. This was for a previous company I worked on maybe 10, 15 years ago. And so I go in there and sit down, they ask for a meeting with us and the investor shows up late. And then he shows up wearing this super tight, like, tank top, like, wife beater thing. And then he's got, like, A blender bottle in his hand. And so like he's like, I'm so sorry I'm late. Was doing a workout. He's kind of sweaty. And then like sits down and like, you know, get the deck going, start the pitching. And the dude, he's got like the blender bottle with like the metal thing inside. And he just starts shaking this thing
- [76:47]
Jason Calacanis
while shaking his protein. Shaking his protein.
- [76:50]
Russ Dasa
Yeah. And then like popping it back, drinking, shaking it up. I'm like doing the whole pitch. He's still shaking. It's like just the we experience I've ever had.
- [77:00]
Jason Calacanis
That was a good one.
- [77:01]
Russ Dasa
You definitely know the person, but I won't say their name.
- [77:04]
Jason Calacanis
I mean, I'm sure I do, but that's a kind of. That would be Keith. Raboy is a workout addict.
- [77:11]
Russ Dasa
But it's not Keith.
- [77:12]
Jason Calacanis
It's not Keith.
- [77:13]
Russ Dasa
Not Keith, no.
- [77:15]
Jason Calacanis
Keith would say something spicy, but he wouldn't be late. Being late for the meeting. Ruloff and I. Roelof had a rule when he was running Sequoia where if you were late, it was $100 bill and you had to keep hundred dollar bills on you. I was taping all in at the Sequoia offices last week, and I brought my latest accelerator class there to meet Ruloff. I'm trying to get off the call. Chamat's got to. And Sacks has got to get his. One more thing. One more thing. I gotta finish. I gotta get the last word. And I'm like. And Ruloff walks up to the conference room. I'm in, smiling, going like this. Because it's, you know, it's 205. And he knows I got to pull out a hundred dollar bill. I give him the hundred. I have to autograph it. I have an autographed hundred dollar bill from him when he was late one time. But that is just the tableside manner that you just have to have if you want to be in these deals. Jeffrey. Are you based in France, by the way? What's the whole thing? No, I'm Detroit search. Yeah, you're from Detroit, but you're a Franken file. Explain to me what's going on here with Frank.
- [78:18]
Jeffrey Cannell
The word noose is actually not the French word. It's the Greek word noose, which means mind or intellect. So there's Greek have like. It's same thing with like the word love. They've got like four words that all get translated.
- [78:28]
Jason Calacanis
No, no, the French is all derivative from the Greeks. We know that. So it's.
- [78:31]
Jeffrey Cannell
It's it's the word. It's the Greek word. I'm. You know, I've pitched a bunch of people, too. I don't have any, like, crazy stories other than. I just love the. The pretense of, like, the. The come sit you down in the boardroom and we're all sitting and talking to you. In my experience, and having pitched a lot of people, the best ones are the people who are just real and honest. The best calls I've ever taken are with one guy who's just on his iPhone just talking to you and being real versus, you know, we're going to fly you to New York and set you in the boardroom and do all that. There's a place you don't like the
- [79:00]
Jason Calacanis
pompous circumstances I think you represent.
- [79:02]
Jeffrey Cannell
Yeah. Is just, come on, what are we doing here?
- [79:05]
Jason Calacanis
It's performative. It's intended to either intimidate or impress. And a real founder will see straight through that. That and Peter Thiel or I should say. Yeah, see, that was me. It was okay, truth be told. This is why you did take a picture of it, Russ.
- [79:21]
Russ Dasa
This is why I didn't want.
- [79:22]
Jason Calacanis
I passed on investing. It's true. This is when I was a little bit thinner and I was more like,
- [79:27]
Jeffrey Cannell
I was less bulk.
- [79:29]
Stephen Berlin Johnson
Really.
- [79:29]
Jason Calacanis
Yeah. This is when I was thinning out, actually. I was going to a competition. I did show up a little late in the wife beater. It was.
- [79:35]
Russ Dasa
Yeah. I forgive you, Jason. It's all right, man.
- [79:37]
Jason Calacanis
Are we. Are we good? Good.
- [79:38]
Stephen Berlin Johnson
Yeah.
- [79:39]
Russ Dasa
We're still buddies. Yeah. You have me on this show twice. It's all good.
- [79:42]
Jason Calacanis
Yeah. I'm just trying to make up for my mistakes.
- [79:44]
Russ Dasa
Right. Yeah.
- [79:47]
Jason Calacanis
So what I did in constructing this, having been on the other side of this, I told another one where more davidow. I named them. Found out I got a term sheet from Sequoia. They used like two or three people around me to beg me to do a meeting with them because they had famously, I believe, passed on Google and they saw mahalo in the Valley. Did as like, well, maybe Jake Al could figure this out because he's good with content and, you know, he did blogging. And so this feels like that a human powered search engine would be like wiki plus blogs plus a search engine. Right. And even Marissa Mayer and Sergey and Larry were like, this is a pretty good idea that, you know, this is before AI could do what it does. And it was 10 blue links. So, like, one of my really good friends begs me to take this meeting, even though I have the term sheet. I'm like, fine. I got to go to Sequoia anyway. More David Dalles next week. Guy cancels the meeting on me. I'm flying up from la. I get up at five, I get the six o' clock flight. I'm coming up for four or five hours. I rent the car. On the way there, my phone goes ding, ding, ding. Like messages. The guy sends me a voicemail. Hey, the meeting's been canceled. I couldn't get my partners around it. Now he knows I'm flying up. He leaves the message while I'm on the plane. So I said, you know me, Stephen. I was full contact in my younger days. Days, for better or worse, you were. I was full contact. So I'm like this guy, I'm going to his office and I'm presenting. So I show up, the partner meetings occurring in a glass fishbowl. He sees me, he turns white and I look at him. I give him one of those. He comes out. Did you get my message? Oh, I got your message.
- [81:23]
Stephen Berlin Johnson
Wow.
- [81:24]
Jason Calacanis
I got your message when I. After I got my rent a car and came here. It's like, well, I'll make it up to whatever I said. Let me explain something to you and how unsuccessful you're going to be in your career as a vc. You're the stupidest human being I've met. Not just the stupidest vc, but the stupidest human being I ever met. You're going to be the biggest failure in the history of venture capital because you could have let me pitch, told me it was a brilliant idea and then said, oh, we had a conflict in our portfolio or I couldn't get the partnership around it. But we want to look at the series, baby. You had 100 options of how not to be a dipshit insult an insane founder. And you know I'm insane cuz you could type Calacanis asshole into Google and find innumerable stories of me acting like a lunatic. I'm going to say bad things about more David Dow for the next 20 years. And here we are 20 years later and I'm still not over it.
- [82:14]
Stephen Berlin Johnson
Funny, because he has an insane founder story and it's the same story.
- [82:18]
Jason Calacanis
Weirdly, it's the same story.
- [82:19]
Jeffrey Cannell
So we're all crazy.
- [82:22]
Jason Calacanis
But I am of the school that these stories all become legendary because there's so little at stake. You know, that's the reason this is so contentious is because there's so little at stake. Like, just move on, folks. Get the next vc. If your founder is acting insane Just move on. Right? But you have to have great bedside manner and be of service as a vc. So this is my public service announcement. I'll just end on this. I studied this and I realized founders don't want their time wasted. So we're going to offer them a first call, an introductory call where they share with us for 10 minutes what they're working on. We ask two or three thoughtful questions for five minutes, and then they ask whatever other questions they want for five minutes. If they want to extend the call, they can. Or if they want to schedule another call for a second call, they can do that as well. And at the end of every call, I came up with a sentence that I say to every founder. Let me try it on you, Russ. Russ, thanks so much for sharing your vision for Live Kit. May I repeat it back to you so I make sure that I didn't miss anything? You say yes.
- [83:27]
Jeffrey Cannell
Love it.
- [83:28]
Jason Calacanis
I repeat back to you my understanding of your business, and then after I repeat it back, I hope I got that right. Is there anything I missed? And then you go, holy cow, he paid attention. He wants to get it right. He's human, so he knows he's fallible. He wants to just have that last moment to understand the business. We started doing that. Our scores went up with founders. I told my team we're going to score every call. They kind of fought me on it. They would do it every three months. We would send something. Now I have it programmatic. 72 hours after somebody on my team meets with you, you get this email from me, from my personal account. This is an automated message from Jason. You met with this member of my team. I would be really helpful if you could score how the call went so we can get better at these. And of course, if you hit reply, you'll get me and I'll reply back. As a human, man, our scores went off the charts. And then anytime anybody has a seven or less, we then do some relationship maintenance and we rewatch the call, because we record the call now that it's on Zoom. And we, we rewatch. We have the person who did the call rewatch the call if it's a 7 or less. And man, our scores went off the
- [84:37]
Russ Dasa
charts in terms of so many. Yeah, I think I just don't understand, like, VCs. They should know that all the founders talk, right? Like, and, you know, we are always like, oh, should I race from this guy? What do you think of this firm? Can I get an intro to these guys? And for some where I've had a really terrible experience. You know, it's. It's like, don't race from them. Here's why you don't want to do it. And so, you know, I just think, like, the reputation matters so much. How you treat people matters so much. Even if it's not. If it's a no, that's fine. Right? But you gotta be respectful and set the expectation properly.
- [85:10]
Jason Calacanis
Okay? We've learned a lot here today. To summarize, Stephen wants a dynamic interface, and here's the. This is the AI Slop roundup. Stephen wants a beautiful interface. There he is. Minority Report. Looking good, looking good. You're well fed in this photo. I see you getting a little. Yeah, you got a little punch there. Maybe, you know, a little extra ramen never hurts. Jeffrey, we learned that you're not in competition with Open Claw. You're not in. You don't consider yourself in competition with Open Claw, but perhaps, Jeffrey, you're not in competition with Open Claw because you cooked them. There it is.
- [85:50]
Jeffrey Cannell
You said it, not me.
- [85:52]
Stephen Berlin Johnson
Okay.
- [85:52]
Russ Dasa
I actually had to do that once, by the way. I actually had to put a lobster into boiling water when I was 12 years old. My mom dropped a live lobster on the floor in the kitchen and didn't know what to do. Yeah.
- [86:01]
Jason Calacanis
Anyway, there's a much better thing to do. What you do is a lot of chefs who know how terrorizing it is to do this to a lobster. You just take a knife, bang, one shot on the skull, the big sleep without the boiling torture. And yeah, Russ, we know you want your Apple human robot, so you picked yours up. I see. There it is. This is the Apple App Store experience with this new CEO, the engineer CEO. All right, everybody, another amazing episode of this week in AI. If you haven't used Erme's agent, where should they go?
- [86:39]
Jeffrey Cannell
Jeff, to get started, nooseresearch.com, n ousresearch.com.
- [86:44]
Jason Calacanis
okay, you couldn't have Hermes AI. You just gotta make people just. Here's. Here's a piece of advice. Rename the company Hermes.
- [86:51]
Jeffrey Cannell
Yeah.
- [86:52]
Stephen Berlin Johnson
Yeah.
- [86:52]
Jeffrey Cannell
Unfortunately, someone has.
- [86:54]
Jason Calacanis
That doesn't matter. You just put get or Go Hermes in the front of it, and then you negotiate with them. And when you negotiate with them for the domain, all you have to do is say, jeffrey, we don't believe domains are important. We have Go Hermes, and, like, everybody just finds us by searching Google. But we'd love to have the domain just. Just for simplicity and make sure somebody else happens. I'd be happy to give you 250k for it. That's the way you present it. You just put get or go in front of it. Russ, where can people, developers obviously and people building products. Find out more. Do you have a startup program?
- [87:30]
Russ Dasa
We do have a startup program. Hit me up for that. I'm on Twitter live kit, GitHub, geez x.com DSA if you want to get in the startup program can hook you up with a discount there or some credit. But yeah, you can find out more@livekit.com
- [87:50]
Jason Calacanis
all right, well done, Stephen. Where can people find more about the latest agentic version?
- [87:56]
Stephen Berlin Johnson
Yeah, notebooklm.google.com that's obviously the site and yeah, a bunch of folks the Notebook LM handle has a bunch of tweets about it as of yesterday and links to some of the other folks talking about what what's possible with it. Lots more to come on that too.
- [88:14]
Jason Calacanis
I wanted to ask you, can you set up like a custom domain and publish your notebook for mass consumption yet
- [88:20]
Stephen Berlin Johnson
you can create public notebooks? People are doing. We have a crazy number of public notebooks have been created. They're still all at Google domain so far but we would like to explore that.
- [88:32]
Jason Calacanis
Yeah, I think that's like a killer thing that substack did and I think you could do where like if I had a knowledge base about something, I do angel investing, whatever, love to publish it to like Angelthebook.com and just make a notebook my website. So anyway, put that in your feature request.
- [88:48]
Stephen Berlin Johnson
We'll come back to you for that.
- [88:50]
Jason Calacanis
Okay, sounds good. We'll see you all next time. Bye bye.