SCALE AI

“It depends like where you sit in the stack, right? Like um, now for Meta, it's like all it's all like creatives. Um, a lot of people are going to cycle into like AI creatives and then that's going to burn out. And then it'll be the next thing. Might be UGC creative uh, creatives again. Maybe affiliates. But it really like any good marketer uh, is going to figure out what the next arb is and they're going to maximize it. So, if you're like a real marketer, not just like one shot one shot wonder to understand Meta, then yeah, you're going to be able to you're going to be able to sell and you're going to be able to sell a lot faster in this new era.”

“I really think the most significant fact in this whole thing is how small it is. We're in the very rare and harder position amongst robotics and AI companies of actually having rapidly declining capital needs. And it's a testament, I think, to the strength of the core business, the demand for these products, having a really elite team that's capable of operating extremely efficiently, that we actually don't need that money to keep scaling and even make more and more aggressive bets in building new products.”

“The other thing that presents challenges for Apple, their commitment to privacy. Apple has a ton of personal data on its users, but company policy prohibits them from using it. And you talk to people inside Apple, that's actually frustrating for them, because there's a lot of stuff they'd like to be able to do, but they don't have access, right? Your stuff's encrypted, they have to jump through lots of hoops to get permission to do anything with data, to train a model.”

“Tony Tether, who had been a door to door salesman in his use definitely has that flare in that way of thinking, says, let's have a contest. Let's see who can put all of these ingredients that we've developed together into a proper self driving car. His original idea is we'll drive him down the Las Vegas Strip that's almost immediately next because it's insane.”

“This year, the spend has just skyrocketed, and it really started in late December with Opus. ... We signed an enterprise contract with Anthropic, and it's gone to the point where now I think when I last talked to you, it was 5,000,000 spend rate. It's actually 7,000,000 spend rate now. ... We're north of 25% of spend on cloud code as a percentage of salary. And if this trajectory continues, then, you know, we'll spend more than a 100% by the end of the year, which is a bit terrifying.”

“I saw that all the teams treated this like a hardware problem. They looked at this and say, we have to build a bigger wheels and bigger chassis and so on. And I looked at this and said, about wait a minute. The challenge really is to build a self driving car. They can drive for the desert. I can get a rental car. They can do it just fine, provided as a person insight and the challenges we need to take the person out of the driver's seat and replace it by computer. That is not a problem with bigger tires. That's actually be a software problem.”

“Part of our defensive strategy was how do we do something that is so crazy? No one would be crazy enough, I don't think, to run seven marathons on all seven continents in one week and make a documentary about it and go through all of the production headache of that. Or call the FAA 300 times to get permission to hang off the side of a military plane to recreate the Mission Impossible stunt. It's almost like the things that feel so untouchable instantly become opportunities for story, because it's a great story to try and overcome that. And also, the second mover scenario will at least take them so long to catch up to us to get there.”

“SAP is the market leader in enterprise, software applications and platforms. It has 400,000 enterprise customers. Usually, I just running their finance, HR, and supply chain, manufacturing, execution, logistics, warehouse management, and then of course everything on the customer side, sales services, commerce, procurement, you name it. End-to-end, like SAP, we always say we have the broadest portfolio in terms of end-to-end running the business end-to-end. This is where SAP started with, giving real-time insight. Usually, I really describe this as it's not just software in itself, it's kind of the operating system of a company essentially.”

“Transformers that were originally successful for large language models started to have an impact on self-driving technology and robotics. There were breakthroughs in end-to-end deep learning, where you can now take lots of data and you can train these models to actually control these systems in a way that wasn't possible before. That was the moment when we actually decided to really enter the self-driving space ourselves.”

“The rise of the forward deployed engineers tells us a lot about how AI adoption is actually going to happen in the enterprise. It’s not just about shipping code; it’s about having engineers who sit with the customer to understand the specific edge cases of their business. We are applying that same philosophy to IT services, where the AI handles the standard stuff and our best people focus on the complex, bespoke problems.”

“What hasn't changed is what customers are seeking for, which is outcomes, right? Outcomes and return on their investment in order to get the things done, right? And of course, now AI is an amazing technology that again helps to get more things done in the enterprise, right? And then that is actually what SAP is standing for, right? And so what we are really doing is in given, of course, also the breadth of the portfolio and the customers is, of course, to help customers to achieve more by deeply embedding AI, AI agents, and of course, transforming now the user interface.”

“John Ternes will take over as CEO of Apple on September 1st. He's been at the company for 25 years. John Ternes is a 50-year-old hardware engineer, mechanical engineer by training. He's been with Apple since 2001. He's an Apple lifer. Four years after he graduated, he came to Apple and steadily rose up the ranks. He's central casting for corporate CEO, just to look at the guy, tall, thin, good looking.”

“Crypto allows us to do that entirely programmatically. And so that's very efficient. If it's just humans, it's great. It makes it more efficient. If it's machines, it's essential. Because a machine can't go through the court system. It can't operate through those human world trust mechanisms. It needs programmatic trust mechanisms. And so crypto becomes essential if you start swapping in machines for humans in those interactions.”

“With AI, the same is happening. It is happening on three levels. It happens, of course, on the UI side. The time is clearly over where you design software, where the dump software that requires the intelligence to sit in front of the computer. Then the second one is, of course, the business processes... a rather rigid process, like the standard operating procedure of a company. But now, of course, with these agents, we can blend the structured and unstructured world more seemingly. And then, of course, below that, you have the whole data layer.”

“Now we're in a position to use that core technology to apply it to different form factors and use cases. And that's where the indoor drone comes into place, because a lot of dangerous work happens indoors. It's where the fixed wing drone that can cover much longer ranges comes into play. And it's a very exciting, fun time to basically take these mature technology building blocks to be able to pretty quickly assemble them into a fundamentally new capability.”

“And the quadrant I identify with the most is ruinous empathy, which is the idea of you are so nice to everyone around you, that when you need to give critical feedback to someone, they might leave the meeting feeling like, wait, am I actually doing great? I don't know, because you're sandwiching complements or downplaying the critique and you're not direct enough. And so transforming that into radical candor is about being more direct with feedback. And so some of the things that Kim has helped me very applicably work through are workshopping, giving critical feedback to people.”

“We reach a point where the machines are autonomous to be able to make their own decisions. They have their own on chain identities. They have the ability to update their own objective functions and reward models, which in combination with crypto economic property rights basically makes them sovereign economic actors. All this will be coming in the next twelve months. At that point, you have this completely Darwinian market for intelligence, and we don't know what happens next.”

“Everybody will give you advice. It always comes from a certain context that that person has, and that context is not your context. As a founder, you have the absolute maximum information about the thing that you're doing. You can't give all of that information to somebody else to give you advice. And so advice realistically is just a data point that you should ingest. If you actually take advice itself, you're almost all of the time gonna be doing the wrong thing in my opinion.”

“What used to matter a lot was execution was very, very fucking difficult, and ideas were cheap. Now ideas are cheap and plentiful, but execution is very easy. So, really, only the good ideas are the ones that can justify the spend on super cheap implementation. ... If implementation costs continue to tank, which they are, we don't even have Meetos yet. ... What now comes to the world, it's a complete reordering of how economies work.”

“So, what I have done at every step in my life is try to find who are the best people to put around myself to continually challenge me, whether it's business, personal, relationships, content, story, and assembling that team is really important to me. Those are the people who help me decide how do I spend each minute of a calendar day. I really thrive in that environment. And being a business owner is such an oppositional to that, because now you are both the coach and the athlete at the same time.”

“I think one of the things that was certainly true at Apple then is just this insistence on their leaders being exceptional engineers themselves. I remember a conversation that made a big impression on me. I was talking to one of our advisors who was a key senior executive at Apple at the time of like, how do you think about prioritizing sort of like management and leadership skills versus technical ability? And he just said, you need both. Like, you can't compromise. The best people are able to do both.”

“I think there will be a large scale protest against Anthropic and end up at AI. People hate AI. AI is less popular than ICE, less popular than politicians. With Anthropic adding so much revenue, that's gonna start causing business changes downstream. People are gonna get more and more scared of AI. They'll start blaming more and more of their own problems and things that are global, have been deep seated problems for a long time. Those will bubble up and be blamed on AI.”

“None of that incremental capacity really gets here until the second that they've decided to do in addition to the typical 20 to 30%. They can stretch a little bit, but, really, the true incremental supply doesn't come till '28, which is a very unique thing. Even if they wanted to build as fast as possible, it doesn't come till '28, late twenty seven at best. So the result is memory prices have gone through the roof. And guess what? They're gonna double and triple again, at least on DRAM, especially.”

“Yeah, so we're very excited to be announcing our Series F. This was $110 million fundraise, $4.4 billion post-money valuation led by insider investors. And I really think the most significant fact in this whole thing is how small it is. We're in the very rare and harder position amongst robotics and AI companies of actually having rapidly declining capital needs. It's a testament to the strength of the core business, the demand for these products, having a really elite team that's capable of operating extremely efficiently, that we actually don't need that money to keep scaling.”

“It’s becoming a little bit less important now to be, let's say, a specialist software engineer in a given field because the AI tools, they can turn you into a specialist much more quickly. But you need to be an expert in the AI tool use itself. And that is a real skill. And so we test for this hard now. We're looking for people who are just really, really good at using the AI tools.”

“Open claw is an autonomous agent, and a lot of people talk about it. And open claw is great for being the execution. Okay. You want it to be your arms. You want Hermes to be your brain. And the cool thing is you could have each of them hold each other in check.”

“I mean, for the most part, SAP software is seed-based, licensed today, with a few exceptions. But very clearly, with AI, it was very clear for us that step by step, it will go towards this consumptive world, first consumptive, and then maybe in the next step, once we have more verifiability in the system, then also towards maybe an outcome-based license model. But the reality is also, it is today for us, it's a hybrid model. It's consumptive, but it still has a certain element of seats in there.”

“The other thing that presents challenges for Apple, their commitment to privacy. Apple has a ton of personal data on its users, but company policy prohibits them from using it. And you talk to people inside Apple, that's actually frustrating for them, because there's a lot of stuff they'd like to be able to do, but they don't have access, right? Your stuff's encrypted, they have to jump through lots of hoops to get permission to do anything with data, to train a model.”

“But SAP and these large customers, right? They always have a problem of scale. Okay, what do you know with 100 documents? Well, it becomes a little harder. A thousand documents becomes a deeper engineering challenge. Last year, everybody could build an MCP server. It was so super simple to hook up your MCP server and do amazing things with it. But that becomes like for 10 APIs, not an issue, 100 because you'll get already context bloat and all these challenges. But we have 20,000 APIs, right? So it becomes just like because it's so huge.”

“Jobs was the iconic technology CEO. He had defined the way humans interact with computing devices for 30 years almost, maybe more. So that was quite a legacy for Tim to match. And he didn't try. He didn't try to be the innovative product visionary that Jobs was. He handed that off to others, and he really focused on operations.”

“SAP is the market leader in enterprise, software applications and platforms. It has 400,000 enterprise customers. Usually, I just running their finance, HR, and supply chain, manufacturing, execution, logistics, warehouse management, and then of course everything on the customer side. End-to-end, like SAP, we always say we have the broadest portfolio in terms of end-to-end running the business end-to-end. This is where SAP started with, giving real-time insight. Usually, I really describe this as it's not just software in itself, it's kind of the operating system of a company essentially.”

“Jobs was the iconic technology CEO. He had defined the way humans interact with computing devices for 30 years almost, maybe more. So that was quite a legacy for Tim to match. And he didn't try. He didn't try to be the innovative product visionary that Jobs was. He handed that off to others, and he really focused on operations.”

“There's people who have argued GPU's full lives are less than five years. Complete nonsense. There are clusters now resigning. Three or four year old Hopper clusters resigning for three or four more years. There's a 100 clusters that are resigning for another couple years. So the useful life is clearly not five years. It's maybe even seven or eight years, arguably. We don't know yet. We'll see when Hopper gets there, but it's clearly not five years. So useful life is extending, and the prices are going up on that renewal.”

“And yet, if you look at what the virtual guy did, because I was trying and wanted to get involved in tech, and then ultimately angel investing, where was I? I was in the Bay Area for 17 years. If I had not done that, I think my success would have had a 0% likelihood. I mean, literally 0%. If I look at how a lot of the ultimately best advising or investing relationships came together, they almost all started with chance encounters at the equivalent of a kebab shop. I go to a barbecue at someone's house and accidentally bump into someone and spill their drink and start a conversation.”

“But once you have Obsidian added in, it makes it easier to manage everything. So, look, it obviously can't be all sunshine and rainbows. Right? So there are some things there are some limitations here.”

“When he took over, this was a company that was worth $300 billion. As of today, it's worth $4 trillion, which is a monumental increase in market capitalization. Well, I mean, gosh, the hardest thing for him is how do you increase value for a company that's already trading at $4 trillion? Stepping into the shoes of these two predecessors is got to be tough.”

“From a product perspective, I think the course that we're charting is towards our drones being like flying agentic AI, just like you have an agent that you interact with on your computer or in the cloud, this thing is an agent that can move and do more for you in the physical world and you should interact with it in similar ways. Like it should have the intelligence and domain expertise to be useful to you in that way.”

“A lot of the money is moving out of software into fiscal goods. So, I'm like pretty bullish on physical products right now. Unlike software, there's like software really has no moat right now. I've seen Jackie Vibecode like absolute trash. Um, Yo, chill. If and if Jackie can do it and if I can do it, uh, there's going to be like a like 10 million other degenerates that are going to code up the same [ __ ] So, I think like at least for venture and like private equity and growth equity firms to invest in software is going to be very challenging moving forward. It's an unknown space and money's going to money's going to rotate to the fiscal.”

“The number one constraint we're facing right now is building more drones faster. The demand for these products has really just exploded over the last couple of years. We a couple of weeks ago announced a $50 million, 3,000 drone order from the US Army. That size of contract is actually not that much of an outlier for us these days. So it's a good problem to have, but we will be tripling production over the course of this year.”

“For me, it was always very clear. I mean, for the most part, SAP software is seat-based, licensed today, with a few exceptions, like Concur or Fieldglass, for example, or the business network. But very clearly, with AI, it was very clear for us that step by step, it will go towards this consumptive world, first consumptive, and then maybe in the next step, once we have more verifiability in the system, then also towards maybe an outcome-based license model to, for example, what Sierra is doing and so on and so forth.”

“Most recently, he ran hardware engineering for all of Apple's products. Historically, Apple has the people who design the products, who wanted to have a certain look and feel, and it has the hardware guys who figure out how to make the design team's dreams come true. He's the one who makes the products come alive on that team. He solves problems, you know, they go to the meeting, he keeps it focused, let's not waste time, he gets to a solution.”

“I would say managing your energy, not your time. I think people get wrapped up in thinking about how much time they're spending working, and it's the wrong thing to focus on. If you genuinely are holistically as an individual aligned with what you're doing and want to achieve long term, the best thing you can do is the amount of energy you can put into things. Just, like, stopping staring at a laptop screen, going outside for, like, two straight hours and just walking gets you through far more work as, like, real work than you would sitting in front of that laptop screen just grinding out what would be seen kind of normally as work.”

“I would say that the open models are are pretty limited. So, you know, even us when when we try to optimize with our, like, our DGX Sparks, for example, and we try to put them on open models, you know, they're they're getting better, but they're not quite the best. Right? And so just know that when it comes to really strategic work, you're probably gonna be wanting to run on the Frontier models, which are going to cost you money.”

“We are seeing a shift where the best founders are no longer looking for just a check; they are looking for a megaphone. If you can provide the distribution and the capital, you are playing a completely different game than the legacy firms that only offer money. We've built our entire model around the idea that being a creator and an investor are now the same job if you want to win at the highest level.”

“Now we call it agent mining because we record all these decision traces, these contexts, what the users are entering into the system. And then you can either use it to say like, hey, wait a minute, this is actually an anomaly. The folks in, I don't know, in UK from our company or the folks in Australia shouldn't do this because the standard operating procedure is this. Or you say like, oh, that's actually a very good improvement. And then you can elevate this to be the new standard operating procedure, maybe not just for Australia, but maybe for the rest of the world.”

“Capital has become a commodity, but attention is the new gold. I can do more for a company in 30 seconds with a story post than a traditional VC can do in a year of board meetings because I have the direct line to the consumer that they simply cannot buy. In today's world, if you don't have the eyeballs, you don't have the power, regardless of how much cash is in your bank account.”

“I'm actually personally bullish right now on um, like one-person agencies. Like if if if I had to make my first freaking 10k a month, I'd just be one guy with AI, armed with AI, probably like a Claude Max. And then just try to figure it out from there. Um, and I'd post every day on socials, like one shorts one short a day, and just go that that route. It's probably cuz I know that route. Like I know that method pretty well, so I feel like I'm I could run it up. Like I don't know, gun to my head type of thing.”

“The hypothesis is that, of course, once the hardware matures in the quantum space, there are certain problems that you can address that are hard to address today. What we are focusing on is the optimization domains, obviously, and then if you go into things like logistics, traveling salesman problems, knapsack problems, like all these kind of usual hard problems in computer science, these are interesting problems where we believe that could be interesting for the future, for maybe a different kind of computing paradigm to solve for.”

“Four point eight million Americans drive for a living. It's one of the most common jobs we have, and these workers do not plan to surrender to the California tech companies. They're doing this because they stand to make an unfathomable amount of money if they eliminate driving jobs for working class of people. These drivers are represented by unions backed by politicians and in cities across America blue cities. They're organizing. So far they're winning.”

“Now we're in a position to use that core technology to apply it to different form factors and use cases. And that's where the indoor drone comes into place, because a lot of dangerous work happens indoors. It's where the fixed wing drone that can cover much longer ranges comes into play. And it's a very exciting, fun time to basically take these mature technology building blocks to be able to pretty quickly assemble them into a fundamentally new capability.”

“I think marketers are primed to win the biggest in this space. Cuz developers are obviously clapped. Um, to give you guys some insight, we recently stumbled upon a tech walk in Vancouver. And half these guys are looking for a job. The other half is saying they like to think with their brain um, rather than use AI tokens. And I think I think Tony said something like if you're thinking, you're not using tokens, which is like NGMI, like automatically, right? Um, Yeah, I mean, there's a there's a thinking machine for us. Like why use that type of like deep thought, deep thinking?”

“Vertical integration is really the secret sauce when you are trying to disrupt a legacy services industry. By owning the full stack—from the software that routes the tickets to the technicians who actually fix the servers—you eliminate the finger-pointing that happens between vendors. This allows us to capture the full economic benefit of the automation we build, rather than just selling a license and hoping someone uses it correctly.”

“The reason I’ve been able to build these businesses and these fights into massive multi-million dollar events is because I understand the arc of a story. You have to give people a reason to tune in, a reason to care, and a reason to buy, and that starts with the narrative and the conflict. If you can't tell a story that captures the zeitgeist, you are just another commodity business waiting to be disrupted.”

“One area Apple has also lagged in is artificial intelligence. While other tech giants like Google and Facebook have spent billions of dollars building AI models, Apple hasn't. Siri, you know, look at the modern chatbots. They are, if they are human, then Siri's a Neanderthal. She's pretty, yeah, not very smart. And they're trying to update that, but they're playing from behind.”

“When he took over, this was a company that was worth $300 billion. As of today, it's worth $4 trillion, which is a monumental increase in market capitalization. Well, I mean, gosh, the hardest thing for him is how do you increase value for a company that's already trading at $4 trillion? Stepping into the shoes of these two predecessors is got to be tough.”

“The time is clearly over where you design software, where the dump software that requires the intelligence to sit in front of the computer. If you look at classical software, what did you do? You decide to use an interface. This is over. It's now, we call this Generative UI. The UIs get dynamically generated. If you have analytical questions, for example, or if you want to do your deep research, not just the deep research you find on perplexity or the usual chatbots, but deeply rooted, let's say tariffs are being introduced or new taxes or the straight-o-formals, what does this mean for my supply chain?”

“Yeah, so we're very excited to be announcing our Series F. This was $110 million fundraise, $4.4 billion post-money valuation led by insider investors. And I really think the most significant fact in this whole thing is how small it is. We're in the very rare and harder position amongst robotics and AI companies of actually having rapidly declining capital needs. It's a testament to the strength of the core business, the demand for these products, having a really elite team that's capable of operating extremely efficiently, that we actually don't need that money to keep scaling.”

“I think one of the things that was certainly true at Apple then is just this insistence on their leaders being exceptional engineers themselves. I remember a conversation that made a big impression on me. I was talking to one of our advisors who was a key senior executive at Apple at the time of like, how do you think about prioritizing sort of like management and leadership skills versus technical ability? And he just said, you need both. Like, you can't compromise. The best people are able to do both.”

“A lot of people like to say, oh, it's Hermes versus OpenClaw. It's OpenClaw versus Hermes. No. You wanna have both because there's a a chain of accountability that wasn't there previously. And now if you have this on your agent fleet, things are gonna run a lot more smoothly.”

“I had experiences of losing people in my life to traffic accidents, and I felt we lost over the million people in the world to traffic accidents. Wouldn't it be amazing if Dabok invented something that would save a million lives a year.”

“Challenge Accepted at its core originally began by me taking a whiteboard, writing all of my fears out, and then connecting each fear to a circumstance that would cause me to address it. Not just as a, like, personal self-help type of thing, because I am a very anxious person internally, but more specifically because it makes for a better story. We realized very early on showing the vulnerability, showing the fear, that's a key part of Snyder's Beats of storytelling. So starting with the all-is-lost moment of the story led us to unlock really, really fascinating episodes.”

“I think there will be a large scale protest against Anthropic and end up at AI. People hate AI. AI is less popular than ICE, less popular than politicians. With Anthropic adding so much revenue, that's gonna start causing business changes downstream. People are gonna get more and more scared of AI. They'll start blaming more and more of their own problems and things that are global, have been deep seated problems for a long time. Those will bubble up and be blamed on AI.”

“None of that incremental capacity really gets here until the second that they've decided to do in addition to the typical 20 to 30%. They can stretch a little bit, but, really, the true incremental supply doesn't come till '28, which is a very unique thing. Even if they wanted to build as fast as possible, it doesn't come till '28, late twenty seven at best. So the result is memory prices have gone through the roof. And guess what? They're gonna double and triple again, at least on DRAM, especially.”

“Without a doubt, our customers look at the fact that we've been around for nearly 10 years, our crazy claim to fame that we've never spent the money we've ever raised. We're not using our capital to pay payroll and things like that. For a customer who wants to have this long-term relationship, that's really confidence-inspiring.”

“LLMs, unstructured world, that's all good, right? But most of the time, if you want to plan forward, if you want to make good decisions in a company, you need predictions. Now, the problem is, of course, still today, if we look at these predictive questions... large language models are not made for this, right? In a way, how they generate just one token after another essentially in a sequence to sequence modeling, I mean, they're language models, right? And they do this phenomenally well. But if you still want to do these predictors where you have to go back to these classical machine learning approaches.”

“A year and a half ago, we had the great honor of being sanctioned by the Chinese government. And it was a pretty aggressive action. They announced the sanctions, and then they showed up at the suppliers that we still had in China, shut them down, stop them from doing business with us, really tried to kill us. So that was a fun adventure for our supply chain team. They've done incredible work, and we've been able to maintain supply. And I think the good news piece of this is that we now have by far the most secure drone supply chain in the world, independent from China.”

“The first paragraph is one sentence about who you are and your legitimacy has to be encompassed in one sentence. Hi, my name is Michelle Khare. I'm a content creator with this many followers, and I've done this, this, and this. It's very succinctly proving your value. Second sentence of that first paragraph. What are you asking for or offering to the other person? And ideally, you're doing both. You're offering something. Second sentence of that email to the FBI would be, I'm reaching out to Inquirer about an opportunity to film a collaboration for my channels.”

“If you look at social media, when social media first started rising, we saw it as just this, like, application that we would interact with. We didn't necessarily realize as the wider user base how how much of that was actually just foundational infrastructure for the future of humanity. This idea that we could interact with each other across enormous distances actually isn't necessarily just a product. It's fundamental human infrastructure. And so because we built it as a product, we allowed all of the power to accrue to that small number of companies who built that infrastructure.”

“The Secretary of the Army visited our headquarters and asked if we could do something with an ISV and a Humvee. In 10 days, we had a very small team retrofit our vehicle operating system and our self-driving system onto the vehicles. We showed them a video of these infantry squad vehicles driving autonomously out in a test environment, and then they shipped it off to an army test facility.”

“Most recently, he ran hardware engineering for all of Apple's products. Historically, Apple has the people who design the products, who wanted to have a certain look and feel, and it has the hardware guys who figure out how to make the design team's dreams come true. He's the one who makes the products come alive on that team. He solves problems, you know, they go to the meeting, he keeps it focused, let's not waste time, he gets to a solution.”

“I think a default expectation in five years is if there's an emergency, you call 911, a drone shows up in a few seconds, and that's going to be everywhere in the US, hopefully everywhere in the world. And that's going to change the way policing works. It's going to get better outcomes, you're going to have fewer officer involved shootings, faster response times. And I think you can also do that while protecting privacy and transparency. Like these things are essentially flying body cameras.”

“My Open Claw and Hermes agents don't do any of that. They run every morning before I wake up. They get better every day, and they cost less than one month of a junior hire. Here's why I would take them over the vast majority of marketers I've ever worked with.”

“I think at the end of the day, it's all about adoption and the outcome you bring to the customer. I mean, the technology, look, the reality is for most companies, the technology doesn't matter. I always tell to my developers all the time, our job at SAP is to make the technology disappear. We need to get the outcome in front of the customer. And then try to make sure that we of course, bake the enterprise qualities in and the integration is there. And the customers can turn these capabilities on almost instantaneously.”

“In the last moments of Alane Herzburg's life, the robot spent an indefensible five point six seconds trying and failing to guess the shape in the road there was a human body pushing a bike. Over those five point six seconds, the robot kept reclassifying our whishing an unknown object a vehicle a bicycle. During that time, spent wondering the car did not slow down. Soon after Elaine Hertzberg's death, Uber halted its testing program.”

“The hypothesis is that, of course, once the hardware matures in the quantum space, there are certain problems that you can address that are hard to address today. What we are focusing on is the optimization domains, obviously, and then if you go into things like logistics, traveling salesman problems, knapsack problems, like all these kind of usual hard problems in computer science, these are interesting problems where we believe that could be interesting for the future, for maybe a different kind of computing paradigm to solve for.”

“You could use like a like a drop shipping model to test out an idea first. So, I think the best way to test an idea to see if it works and to see if you have the right unit economics, it's like yeah, drop ship it first, run some ads to it, see what the customer acquisition cost is going to look like. Um, and scale it up. You could you could basically launch a site within like like under a week. You probably depends on how cracked you are. With AI for sure. Like website, you can AI with it. You can get a bunch of like fast creatives, static using AI or or UGC.”

“We're entering an era where AI isn't just a tool, it's potentially a replacement for entire sectors of the workforce. It’s going to redefine what it means to be productive, and if you aren't thinking about how that affects the labor market and the entire human race, you're missing the biggest story of our lifetime. The speed of this transition is what should actually keep people up at night.”

“The best books to read are the old books. So over 25 years, over 50 years because time has filtered all the kind of noise and you really get a lot of signal in you. Just pick the really good ones because what you read does impact your view of the world. And you want to read diverse books that are not just kind of what your friends are telling you to read.”

“Physical AI is very different. The companies are different. The geographies and regulatory environments are different. The machines are different. The cultures are different. And so the diffusion is actually way, way slower. So, time becomes a much more important thing. Staying power becomes important.”

“I think a default expectation in five years is if there's an emergency, you call 911, a drone shows up in a few seconds, and that's going to be everywhere in the US, hopefully everywhere in the world. And that's going to change the way policing works. It's going to get better outcomes, you're going to have fewer officer involved shootings, faster response times. And I think you can also do that while protecting privacy and transparency. Like these things are essentially flying body cameras.”

“SAP and these large customers, right? They always have a problem of scale. Okay, what do you know with 100 documents? Well, it becomes a little harder. A thousand documents becomes a deeper engineering challenge. And now if you go into Julia or Sarah, you're maybe an SAP US employee, right? Of course, if you ask a question, of course, for travel policy, for example, of course you expect a very different answer than me as a German employee would get. So you now need to connect this actually with your master data.”

“I really think the most significant fact in this whole thing is how small it is. We're in the very rare and harder position amongst robotics and AI companies of actually having rapidly declining capital needs. And it's a testament, I think, to the strength of the core business, the demand for these products, having a really elite team that's capable of operating extremely efficiently, that we actually don't need that money to keep scaling and even make more and more aggressive bets in building new products.”

“Methos is potentially the biggest step up in model capabilities in two years. I think that's really, really an important detail that it's so good that they're, like, don't wanna release it even though they already announced the price to their people that they did a selective release for cyber for, and it's 5 or 10 x the token cost. They just don't wanna release it because they're worried about the impact on the world. And they're releasing a worse version, Opus four seven, to us, and they explicitly said on the card, hey. We actually Preferably. Made it worse at cyber.”

“We are very well known in our industry. I think we're more well known in construction and mining in Asia than maybe some bar in the mission. But that directly correlates to where we're going to make money. We opened also in India and UK offices last year. Australia could be one of those countries where we're doing driverless trucks and we're doing a bunch of different ports.”

“At this point in 2026, 2025, we release eight to 10 episodes per year. That's my upload cadence. And so every opportunity is a big bet, but what I have found is that when I did that, something even more special happened. It created something unique. And I have found that defining something unique can be even more valuable than consistency or mass viewership. We're very blessed that Challenge Accepted does get a lot of views and we feel strong about the bets that we make on these episodes.”

“There's a couple different things happening in terms of the services business. First off, the most lucrative that nobody really appreciates is Google Search in the Safari browser. Google pays Apple over $20 billion a year to be the default search in the Safari browser. That's somewhere around a fifth of the company's profits, which is really remarkable when you think about it.”

“The managed service provider market is essentially a hundred billion dollar industry that is stuck a decade behind modern technology. When you look at how most of these MSPs operate today, they are still using legacy ticketing systems and manual processes that haven't changed since the early 2010s. We saw an opportunity to come in and rebuild that stack from the ground up using AI to handle the rote tasks that consume so much human time.”

“The number one constraint we're facing right now is building more drones faster. The demand for these products has really just exploded over the last couple of years. We a couple of weeks ago announced a $50 million, 3,000 drone order from the US Army. That size of contract is actually not that much of an outlier for us these days. So it's a good problem to have, but we will be tripling production over the course of this year.”

“One area Apple has also lagged in is artificial intelligence. While other tech giants like Google and Facebook have spent billions of dollars building AI models, Apple hasn't. Siri, you know, look at the modern chatbots. They are, if they are human, then Siri's a Neanderthal. She's pretty, yeah, not very smart. And they're trying to update that, but they're playing from behind.”

“Now what we do in the past, we call this process mining. Now we call it agent mining because we record all these decision traces, these contexts, what the users are entering into the system. And then you can either use it to say like, hey, wait a minute, this is actually an anomaly... Or you say like, oh, that's actually a very good improvement. And then you can elevate this to be the new standard operating procedure, maybe not just for Australia, but maybe for the rest of the world or more countries to run your company more efficient because now you'll learn something, how the organization behaves.”

“There's a couple different things happening in terms of the services business. First off, the most lucrative that nobody really appreciates is Google Search in the Safari browser. Google pays Apple over $20 billion a year to be the default search in the Safari browser. That's somewhere around a fifth of the company's profits, which is really remarkable when you think about it.”

“More recently, the most kind of interesting wave has been within reinforcement learning post training or just reinforcement learning in general where you basically give the machine an environment and a kind of reward signal to operate with and then you let it explore. This allows us to to use the compute that that machine learning model is using to generate its representations without requiring a human to label every sample. And so it takes away that kind of, like, human effort, shifts it to the creation of an environment, and then just puts it all on the execution of the machine learning model.”

“Pure play software often struggles in these services categories because the friction of adoption is just too high for the end user. You can't just hand a traditional IT shop a new AI tool and expect them to re-engineer their entire workflow overnight. By being the service provider ourselves, we can bake the software directly into the delivery model and prove the value through better margins and faster response times.”

“Weimos says, and I think this is correct, that it's roughly eighty brass safer in terms of crashes are severe enough to turn down an airbag. Crashes severe enough to cause an injury, and also crashes involving vulnerable road users like pedestrians or bicyclists. So far it's been better than human drivers, and so far, I think the case for allowing them they continue. The experiment is very strong.”

“One innovation that is underappreciated by a lot of people outside the industry is Apple Silicon. The chips in the devices are all Apple chips. And that's been true for iPhones for a long time. It wasn't true for Macs. Macs ran on Intel chips until 2020, when they started ripping them out and putting in Apple chips. Apple chips are really great.”

“A year and a half ago, we had the great honor of being sanctioned by the Chinese government. And it was a pretty aggressive action. They announced the sanctions, and then they showed up at the suppliers that we still had in China, shut them down, stop them from doing business with us, really tried to kill us. So that was a fun adventure for our supply chain team. They've done incredible work, and we've been able to maintain supply. And I think the good news piece of this is that we now have by far the most secure drone supply chain in the world, independent from China.”

“If you look at computing as a technology, humans had to learn to interact with a purely deterministic machine. So it's purely imperative. We know exactly what it's gonna do, and we have to interact with it with these formal rules because that's how computers work. Actually, I think historically, we'll look back and that will be a blip. It'll be that we had to do that at the very beginning of computing as a technology because we hadn't figured out how to do it more natively for humans. And actually, we're coming out of that era now, machines are becoming probabilistic.”

“There's people who have argued GPU's full lives are less than five years. Complete nonsense. There are clusters now resigning. Three or four year old Hopper clusters resigning for three or four more years. There's a 100 clusters that are resigning for another couple years. So the useful life is clearly not five years. It's maybe even seven or eight years, arguably. We don't know yet. We'll see when Hopper gets there, but it's clearly not five years. So useful life is extending, and the prices are going up on that renewal.”

“The main difference in their approach is how quickly they want to move. Anthony is very okay with risk. He gets one of these cars and he's driving it back, and he lives in Berkeley, works in Palauto. He's just using this car like the Bay Bridge every day, probably outside the bounds of what the team actually wanted, and he's not necessarily logging data. He's just enjoying his self driving car and taking it all over the place.”

“Most people don't think about data integrity. They don't think about keeping their CRM clean. They don't think about any of this stuff. Okay. And so you're gonna have to keep that clean. The other thing too, is if you don't have good skill dot MD files, meaning that you don't have good processes within your company and you don't pass them over to, like, your Obsidian to have that central memory continue to get better over time in terms of how you make decisions, well, then this is not gonna be that helpful because garbage in garbage out.”

“One innovation that is underappreciated by a lot of people outside the industry is Apple Silicon. The chips in the devices are all Apple chips. And that's been true for iPhones for a long time. It wasn't true for Macs. Macs ran on Intel chips until 2020, when they started ripping them out and putting in Apple chips. Apple chips are really great.”

“Large language models are not made for this, right? In a way, how they generate just one token after another essentially in a sequence to sequence modeling, I mean, they're language models, right? And they do this phenomenally well. But if you still want to do these predictors where you have to go back to these classical machine learning approaches... What we said all the time is, okay, look, we have all this data stored in these tables, right? Thousands of tables, right? Where all this information is stored. Can we not apply the same idea that large language models or multimodal models did for the unstructured world, actually for the structured in order to start predicting things?”

“Sebastian, I think you should build a self diving car that can drive anywhere in the world. And my immediate reaction was, no, taking the technology we build for this empty desert and put it in the middle of Market Street in San Francisco is going to kill somebody. And Larry would come back the next day with the same idea, and I would give them the same answer, and both of us got increasingly more frustrated. God damn it, it can't be done, and eventually came and said, look, Sebastian, OK, care, I get it. You can't do it. I want to explain to Erk Schmidt the CEO at the time and Sergey Britt my cofounder, why it can't be done?”

“This year, the spend has just skyrocketed, and it really started in late December with Opus. ... We signed an enterprise contract with Anthropic, and it's gone to the point where now I think when I last talked to you, it was 5,000,000 spend rate. It's actually 7,000,000 spend rate now. ... We're north of 25% of spend on cloud code as a percentage of salary. And if this trajectory continues, then, you know, we'll spend more than a 100% by the end of the year, which is a bit terrifying.”

“Most companies in the Bay Area are more hobby projects than they are earnest, serious businesses. We wouldn't build a company this way if just making money was the only outcome we wanted. Our relationship to the ecosystem has always been different; we have actively sought that limelight only recently to help with recruiting numbers.”

“I think people think a lot about the AI space right now, and they think about, yeah, this sort of, like, product level, like, the systems they're interacting with, like chat g p t and things like that, but they don't realize how much is actually behind those systems necessarily. And I think the wider world, how much centralization is actually behind those systems. Those systems rely on very small number of companies to run them. To the average user, you sort of know that you're interacting with OpenAI, but you don't actually realize how much is going through their servers and their systems.”

“John Ternes will take over as CEO of Apple on September 1st. He's been at the company for 25 years. John Ternes is a 50-year-old hardware engineer, mechanical engineer by training. He's been with Apple since 2001. He's an Apple lifer. Four years after he graduated, he came to Apple and steadily rose up the ranks. He's central casting for corporate CEO, just to look at the guy, tall, thin, good looking.”

“Now I do wanna emphasize this again. Hermes learns from every session. So imagine this. After 20 to 30 tasks in any one domain, it's going to be measurably better than it was before. OpenClaw doesn't do that.”

“Methos is potentially the biggest step up in model capabilities in two years. I think that's really, really an important detail that it's so good that they're, like, don't wanna release it even though they already announced the price to their people that they did a selective release for cyber for, and it's 5 or 10 x the token cost. They just don't wanna release it because they're worried about the impact on the world. And they're releasing a worse version, Opus four seven, to us, and they explicitly said on the card, hey. We actually Preferably. Made it worse at cyber.”

“I really believe seed investing is for amateurs now because the risk-reward ratio has shifted so dramatically in the current market. We want to be in the businesses that are already proven winners where our massive distribution can act as a force multiplier rather than just betting on a prayer at the earliest stages. It’s about pouring gasoline on an existing fire, not trying to rub two sticks together.”

“Mine's probably like a touch less cerebral, but it's basically, power lifting. If you're lifting a very heavy weight, it has it's a bit like a mental, like, palate cleanser. It's very hard to think about anything else. If you're, like, under, like, a squat bar, for example, like a very heavy weight. It's something I found where sometimes I go into, like, the gym to lift weights, and I'll be, like, you know, thinking about everything that we've just been talking about. And then for, like, the period immediately after it, it does just it's like a reset button.”

“What used to matter a lot was execution was very, very fucking difficult, and ideas were cheap. Now ideas are cheap and plentiful, but execution is very easy. So, really, only the good ideas are the ones that can justify the spend on super cheap implementation. ... If implementation costs continue to tank, which they are, we don't even have Meetos yet. ... What now comes to the world, it's a complete reordering of how economies work.”

“From a product perspective, I think the course that we're charting is towards our drones being like flying agentic AI, just like you have an agent that you interact with on your computer or in the cloud, this thing is an agent that can move and do more for you in the physical world and you should interact with it in similar ways. Like it should have the intelligence and domain expertise to be useful to you in that way.”

“I decided, I'm going to train myself for the worst possible outcome. So I moved into a studio apartment with a roommate. I financially stripped down, I mean, I didn't have much anyways, but stripped as much as I could to simulate, if I'm truly failing at this and having to live in a Hollywood apartment with a bunch of roommates, I'm just going to get used to that. I'm going to get used to it right now. I'm going to cancel all of my memberships and figure out how to stay healthy, with just myself, just myself in this small place.”