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![Just in $AMD Anush "Speed is the moat"|ROCm🎙️ In the race to define the future of AI, what's the one advantage that truly lasts? It's not proprietary tech, argues Anush Elangovan Elangovan, VP of AI Software at AMD , but the sustainable speed of innovation. He explains why AMD is rejecting the "walled garden" model for its open source ROCm stack, betting that an open community flywheel is the key to victory. Listen to understand how this open strategy is designed to out-innovate closed systems by empowering developers to solve everything from frontier-model challenges to the mundane, everyday problems that define the "last mile" of AI. AMD ROCm Software: Part 1 Transcript [00:00:00] Andrew Zigler: Joining me is Anush Elangovan, VP of AI software at AMD. And when people talk about AI compute, the conversation often stops at hardware specs, but it's more than just physical chips that win the game. It's also the software ecosystems supporting them. [00:00:18] Andrew Zigler: The prevailing strategy in the industry has been to build something like a walled garden. You know, something closed, proprietary locks, developers in. But AMD is betting on an entirely different play, open source acceleration, and with rock, their open source AI software stack. AMD is building not just hardware parity, but an innovation flywheel that's powered by the community with interoperability and the freedom to scale without all of that pesky lockin. [00:00:48] Andrew Zigler: And in this world, speed is your moat and how fast you can innovate while your platform remains open, flexible, and standardize across all of its applications. That's what we're gonna explore [00:01:00] today. So Anush, I'm really excited to have you here. Welcome to Dev Interrupted. [00:01:04] Anush Elangovan: Thanks for having me. Uh, super excited to chat about it. [00:01:07] Andrew Zigler: Amazing. Well, let's go ahead and dive right in with kind of what I laid it out with in the beginning, the idea of the moat and it being about speed. I wanna unpack that a bit because that came from you when you and I first spoke. And I, and I want to know, you know, how do you define speed inside of AMD beyond just things like hardware, benchmarks. [00:01:27] Anush Elangovan: Yeah, that's a very good question. So when we typically talk about speed, everyone's like, Hey, hardware benchmark specs, right? Like, uh, memory bandwidth or, or flops. And that is one important part of it, uh, AMD does very well. With that, we do have, a, a very good history of executing on that axis. [00:01:47] Anush Elangovan: But when I say speed is the moat, it is about, uh, how we prepare, how we build the muscle to run the race for a long time and run it fast. And it is [00:02:00] not about a single point in time that you've, you've beat some you know, benchmark and, and you declare victory. It's about building the ability to consistently develop and deliver. [00:02:13] Anush Elangovan: Both hardware and software innovation at scale and do it fast, right? Like, you know, we we're increasingly getting to a point where models come out and they're, uh, you know, a year or two ago it was like, Hey, they work on AMD on day zero, which is great, but now they are performing on AMD the day it releases, right? [00:02:32] Anush Elangovan: So, what does it take to Prefetch where the industry is going? Be prepared to intercept. At that point is what you know, I, I refer to as you know, the, the speed factor in, in creating this mode, right? And the mode is just shed all things that hold you back and run as fast as you can. [00:02:53] Anush Elangovan: Uh, because the pace of innovation that is, uh, being seen in, in AI [00:03:00] industries is just. Amazing. Right? And it's like, it's transformational at at how you generate electricity. It's transformational as at how you build data centers. It's transformational at how you deploy compute, networking. It's transformational at what kind of use cases you, you know, uh, use AI for. [00:03:17] Anush Elangovan: Uh, and for that, you need to be prepared to, see what comes tomorrow and be prepared to run the race tomorrow. [00:03:23] Andrew Zigler: Yeah, it's a really great perspective because it highlights that it's not just like a checkpoint that you run through. I like how you called out, like it's not just hitting that benchmark or being the best in class at that moment, in that snapshot, it's about having a. The throughput and about having that dedication to the idea and continuing to deliver on it. [00:03:43] Andrew Zigler: It's not just crossing the threshold, but it's also being the engine. And that's what, that's what protects a business. That is the moat, because the moat is that innovation layer, the faster and more, uh, future forward. That you can work and think, [00:04:00] you know, the better. Uh, we, we talk a lot about like future forward work styles. [00:04:04] Andrew Zigler: Like what are the things I could be doing right now today that are gonna be like, way more useful tomorrow? Let, let's abandon those, workflows that are older and that kind of like, that translates into. An advantage when you work that way. You know, what kind of things have you learned working with, uh, like across all spectrums of people who would use ROCm, right? [00:04:23] Andrew Zigler: You have like the developers, but then you also have the enterprises and you have this large span of adoptees, right? So what is the, what does that look like that you learn? [00:04:32] Anush Elangovan: Yeah, so, so the way I look at it is there are gonna be pockets of different, uh, you know, cadences, right? Like, so people who are deploying in enterprises, for example, right? The validation and how long it takes for them to deploy an LLM that's secure. It's, with guardrails, et cetera, maybe longer. [00:04:52] Anush Elangovan: but you still have to go through the process and you have to be prepared to like, walk that walk to deploy an enterprises. That doesn't mean it's [00:05:00] not fast, that's as fast as you can do for that industry, right? And if you are deploying AI in healthcare, right, it's, it's got its own, uh, cycle. [00:05:07] Anush Elangovan: but in each one of these, you want to see how, like, go down to the essence of what is it that you actually have to do. And, you know, I, I, I like how you framed it. It's like it's, you shed your prior assumptions of how things are done, right. And, and you kind of build up from a, uh, first principles, uh, approach to say, this is how I could use AI to unlock, whatever I'm doing. [00:05:33] Anush Elangovan: And, and, some of it, you know, it's good to really step back and look at. Just question every part of it, right? Like right now you're getting chat GPT and, Gemini competing for like, math, olympiads and, and, uh, college, uh, reasoning, uh, tests. Right? And, and those are like that, that is amazing and increasingly like complex tasks that they're trying to do. [00:05:58] Anush Elangovan: But there may also be like. [00:06:00] More mundane things that AI could, could get applied to. Right? And, and so when we think about shedding old ways, you wanna shed it not just in like the tip of the spear. It's like, you know, I'm gonna see what's the frontier model. It's also, it could be something as simple as. [00:06:18] Anush Elangovan: How do you choose a, a movie, uh, you know, like a recommendation system, right? Or, or, uh, an automated, uh, flight, uh, rebooking system. So the moment, you know, your flight is late, uh, right now it's a notification, right? It's like, oh, you got a text message saying your flight's late. And I got that like three times this week. [00:06:38] Anush Elangovan: But anyway, uh, and, and, and, and, I was just like, okay, so if I were to rethink this. All this MCPs that we have that should be hooked up into an MCP that says, your flight's delayed. Here are your options. If you want, you know, these are the paid options. Yeah. Here are the free options. This will get you back into your you know, Toronto airport [00:07:00] tonight. [00:07:00] Anush Elangovan: Or if you stay, here's a hotel plus this, plus this, plus. It's just like, go ahead is all I should say. Versus now I'm like, okay, can someone, you know, can I call a travel agent? Can I do this? Can I go online and log into And you know, so we gotta fundamentally rethink even those like small, nuances of, things that we do that can be automated out and AI is really, really good at doing something like this, right? Maybe I just explained an AI startup idea right now. Somebody should just start that. [00:07:29] Andrew Zigler: I think you did. Yeah, you definitely did. Someone, one of our listeners is definitely going to lift that off of you. I, I, I, you know, I hate being on the receiving end of those. You feel a little helpless and then you have to like, follow the whole flow. So I know what you mean. Like I, I like how you called out that the build and this like. [00:07:45] Andrew Zigler: Where speed is your moat and the innovation layer is protecting you, is what makes you better than your competitors. How you scale that and you bring that to market. So by understanding the problems that you're solving, uh, throwing away those older assumptions, but also [00:08:00] recognizing that like. We're building every single day, new things and new ways of using stuff that we're still figuring out the implications of. [00:08:08] Andrew Zigler: And so when you have a lot of velocity and you're introducing a lot of new ideas, and maybe you have that workflow now that automatically rebook your flight off of your late flight text message, and uh, I know I would certainly use it, but you know, what kind of philosophies guide the way that y'all think about building this ecosystem to manage that stability while letting folks. [00:08:29] Andrew Zigler: Play with the speed and the assumptions and the airplane re bookings. [00:08:34] Anush Elangovan: so, so I think, you know, we need to peel one layer down, right? and the philosophy is, Hey, we, we just discovered electricity, right? And you know what we're gonna do? We are gonna make motors, uh, or dynamos, right? Like engines. Uh, sure. We don't know if it's gonna be a Ferrari that you're gonna make, or it's a a a a dump truck. [00:08:57] Anush Elangovan: That's good for doing this. But let's [00:09:00] let, which is also required, right? You need a dump truck. You need a garbage truck. And, [00:09:04] Andrew Zigler: Yeah. You need the [00:09:04] Anush Elangovan: course you need, uh, a Ferrari for a midlife crisis, right? So, [00:09:09] Andrew Zigler: precisely. [00:09:10] Anush Elangovan: But, but my, uh, point is what do we build next? And, uh, and this is what I meant by like, okay, let's, let's take those baby steps to build the. [00:09:20] Anush Elangovan: Infrastructure that's required that we know we'll have to use, right? So, so if I just discovered electricity, okay, great. Now one, how do I save this electricity and how do I use it? So there's battery technology, so you need to do something like that, right? Like so. But then you also want to make it into an actionable thing. [00:09:37] Anush Elangovan: You want to make it for like automobiles, or you wanna use it for, you know, powering, uh, entire cities. So it is that transformational. So, uh, AI is that transformational. So, if you distill down, it'll, it'll come down to how do we think about, what we can do with this this fundamental technology that, We may not be aware of what it [00:10:00] is gonna unlock next, but at least you know the next step is clear, right? It's like a dense fog, you know, it's gonna be like, it, it's the right path. You see the light, but it's kind of like out there and, and the steps you're taking are concrete and you're like, okay, this is good. [00:10:16] Anush Elangovan: I, this is better than where I was or where we were. So we are moving forward. So you can build with the. Intuition from what you see in the short term and a tactical view, but towards what you think the future is gonna be. [00:10:28] Andrew Zigler: Right. You almost like we're all in this like fog of war, right? And like you said, you're reaching out and you're trying to step through it. You could think of it too, as like you're in the dark and your hands are up in front of you and you know that. You're, you're not gonna run your face into a wall because your hands are out in front of you, but you're not gonna maybe do much better than that. [00:10:45] Andrew Zigler: So that's kind of like, I think the eco, the, the industry, the world that we find ourselves in, uh, and we all have to, then this becomes the power of an ecosystem, of a group of people working together to create that layer of, [00:11:00] uh, of establishing the [00:11:01] Anush Elangovan: exactly. And I, I, I just, instead of, you know, saying fog of war I describe it as like, you're in this. Beautiful valley with like a morning, uh, fog that's in. You can smell the flowers. You, you hear the birds. You are like, okay, it's, we are in like, uh, utopian paradise and yes, I just need to like, continue the walk, right? [00:11:24] Anush Elangovan: and then move forward with that, conviction that you're in the right spot. [00:11:27] Andrew Zigler: Yeah. So let's talk about that ecosystem world. This nice, I love how you describe it, this grassy side of a hill in the morning that's covered in some mist and maybe we can't see 30 feet in one direction, but it sure is a beautiful hill and it smells nice. And so we're all here. And why is, in that world, why is. [00:11:44] Andrew Zigler: You know, open source, their strategic advantage that y'all are going for in the AI hardware market. And, and then how does like ROCm turn that into wins for people within that ecosystem? [00:11:56] Anush Elangovan: you know, the, the way we look at it is this, is kind of like how I view [00:12:00] AI and the ecosystem, right? But, but it is for everyone to enjoy. Uh, and so we do want to make sure that. You know, it is, uh, beneficial for everyone. [00:12:09] Anush Elangovan: The ecosystem can come in and, and innovate. It's an open innovation engine. and uh, it is very different from, you know, having a walled garden with, Hey, only I know how to do this and I'm gonna do it and throw it over the fence and you can use it or keep walking, right? So we'd like to be good citizens that way, but also. [00:12:30] Anush Elangovan: Uh, it is self-fulfilling in a way, right? Like it, the, the pace at which we innovate with open source is unmatched. Like, you know, our serving engines are like VLLM and, and sg l. Those things, uh, those frameworks are like super, super aggressive in terms of how fast they come out with features and how fast they can you know, get performant models out. [00:12:52] Anush Elangovan: And that compared with what, uh, you'd get from, you know, the likes of like T-R-T-L-L-M or something is always lagging, right? Because you [00:13:00] just can't keep up with you know, 200 commits a week just on one particular model to get that model really performant [00:13:06] Andrew Zigler: And, and, and in that world where, you know, everyone can enjoy the winds of this, what kind of customer stories or innovation stories have really stood out to you and excite you about building and creating this place for developers? [00:13:19] Anush Elangovan: Yeah. So I think the parts that are super exciting for me are when when we get to see a customer that is first skeptical. Then they start a little like, okay, fine, we'll give you a chance. Uh, we do a simple, uh, POC and then they're like, huh, this seems to work. Yeah, we told you it works. [00:13:42] Anush Elangovan: You don't have to change one line of code. Really? Yes, no need to change one line of code. Okay, let's try a production workload. So then they try it. Oh, you're more performant than the competition. Yes. We're more performant than, than the competition. So how much does it cost? And we're like, oh, it's your TCO is better with, uh, [00:14:00] AMD. [00:14:00] Anush Elangovan: So again, they're like, wow, okay, good. So now how do we deploy at scale? And then we go deploy it at scale. And when they give a thumbs up on that and they say, this is good, right? That's when you know, you, you see it go full circle from like, oh, we, we've never heard about AMD to like actually deploy to tens of thousands of GPUs In the order of a few months, right? It, it, it really is fascinating to see and very exciting and invigorating to [00:14:28] Andrew Zigler: Yeah. At like a great exposure to a lot of interesting problems. And, and then people using the infrastructure, the, the technology available to solve those problems. Really specific problems by the way, that's often why they're bringing their data and AI to it, uh, is because it is really specific and important for them. [00:14:45] Andrew Zigler: And there's a, a lot I think that other engineering orgs can learn and even emulate from AMD's success and, and having this open source ecosystem and it causing this acceleration within. You [00:15:00] know, uh, customers and enterprises that use and adopt the tools and, and, and that creates an advantage. And that goes back to why we're talking and like the real thesis of our conversation today. [00:15:10] Andrew Zigler: So how do you think engineering leaders that are listening to this and obviously tapping into this great success AMD has from an open source flywheel, how do you think other, other folks building in the same space can foster that open, first, that open source oriented culture in order to, you know, accelerate their innovation goals? [00:15:29] Anush Elangovan: Yeah, that's a very good question. So the startup that um, was acquired by AMD we, we built, I mean, we started off doing iot stuff and you know, smart ring and all that, right? But in the, the end of like, uh, and not the end, the last six years of the company was building ML compilers. [00:15:47] Anush Elangovan: And ml, ML compilers are like super, uh, complicated, sophisticated, advanced algorithms, dah, dah, dah. but it was all open source, right? So our VCs were like, wait, what do you mean your core [00:16:00] IP is open source? And um, the speed is the moat applied even then, right? It was just like, yes, if you have an idea that. [00:16:08] Anush Elangovan: Because someone saw this idea that you are, they're gonna be able to catch up, then you probably have the wrong idea anyway. But if they are, you know, you execute and they're gonna catch up, that you should assume they're gonna catch up. Right? So you gotta move forward. So keeping it open source is super important. [00:16:25] Anush Elangovan: But also to your question on like, you know, the learnings from an AMD standpoint, right? If there are, hard problems, I'd say dig in and work through it, right? Like there's no way but through it, right? That should be the simple mentality. And more, uh, frequently than not. you'll see that you'll just make it through in a, in, in good form. [00:16:52] Anush Elangovan: But if you doubt it and you're like, oh, I don't know if I should commit, if I'm, I, you know, what should just commit to do the right thing [00:17:00] every step, right? Every step, and just keep taking one step in front of the other. And in no time you'll see that you'll be running. Right. And, and yes, the first few steps will be like, yeah, everyone's complaining about your software quality. [00:17:15] Anush Elangovan: Everyone's complaining about this and that, and it doesn't work. And, and a few steps in, you know, you get, you get the hang of all the complaints that are coming in. You get the feedback loop. You're like, okay, what, what are you prioritizing again? One step in front of the other, right? You just keep knocking that out and then you get to a point where you're, it just becomes second nature, right? To do the, to do the right thing. And, and then yes, if someone gives you two options, you'll be like, fine. This is, uh, you know, there's always the resource trade off. There's always a human capital trade off, but what's the right thing to do? of course, I, I'm pragmatic about what we choose, but, but if the right thing for your long-term success is dig in, go first, principles, make it [00:18:00] happen. [00:18:00] Anush Elangovan: Well. Then just go for that. There's, there is no shortcut to [00:18:04] Andrew Zigler: acknowledging, you know, how it aligns with your mission, your core company goals, and what you're looking to achieve. And, and I, I love how you rightfully called out that in the open source world and you know, you have your technology that you've built, what you think is your moat upon, right? [00:18:22] Andrew Zigler: It's your code and, and to open source that, or to just make it where anyone could peer in is, you know. Scary in one regard, but two, it just kind of feels like you're handing away your throne room in some kind of sense, a very direct feeling sense. But the ultimately, you were really right to call out, and this is something I think about all the time, that the real power there is still the speed This the speed. [00:18:42] Andrew Zigler: That was the moat at the beginning of our conversation. It's the speed in combination with your. Very specific domain understanding of what you're building and what you're creating, and your new role as the steward of that world and how people plug into it, which [00:19:00] has frankly, a lot more influence and power than lording over a closed. [00:19:04] Andrew Zigler: You know, repository or an ecosystem, and like you said, like throwing things over the wall. Sure. There, there might be people always on the other side of that wall, but you're not gonna have a great connection with them. You're not gonna be able to really clearly understand them. I, I like your metaphor of the side of the field of the mountain a lot more. [00:19:23] Andrew Zigler: But, but in the, in this world, you know, where. That speed is, is the power and, and open source is just one way that you can harness that speed to get really far ahead and to innovate. , There's other parts of this equation that you can be experimenting with too, and I'd love to pick your brain about them as a software leader and, and, and one of them is about looking forward and kind of understanding that future that we're all building towards and beyond today's models and hardware. [00:19:48] Andrew Zigler: You know, what do you see as the next major bottleneck or opportunity in the AI compute space? As, as you know, enterprises and folks start to get a little more mature about what's available to [00:20:00] them. [00:20:00] Anush Elangovan: Yeah, I think, the bottleneck and opportunity is, uh, what I'd call, call walking the last mile of ai. Right. Uh, and like I I, I gave you an example, uh, previously, but, but it's similar to that. It's like there are cases where Humans have so many, uh, things to do in your day. You know, like the, if we sit down and actually had a customer focus like, okay, these customers lives, I'm gonna save four hours of this customer's life. And if you actually sit down and look at all of that, it'll be. Easily automatable, easily you know, uh, applicable, uh, for ai, right? [00:20:39] Anush Elangovan: Like, but then making it happen is gonna take a little bit, right? It's like maybe it's, uh, paying your utility bill, right? Or something like that, right? Or, or, your healthcare explanation of benefits. Uh, like, I'm sure you get an explanation of benefits, and I'm like, I, I don't even know what that thing is. [00:20:55] Anush Elangovan: It's just like EOB and like. [00:20:57] Andrew Zigler: it's a big, a big old PDF. Yeah, [00:21:00] exactly. [00:21:01] Anush Elangovan: Like, like, I'm like great straight to the, uh, shredder, right? And but that could be, you know, automated with the ai, right? It, it, it'd be like, Hey, the summary of this thing is you went and visited this day. Everything is okay. Everything is paid for, so don't worry, it's not a bill. [00:21:17] Anush Elangovan: That again, the same, uh, thing, but the sense of what that information overload is could be. Digested by ai, uh, accumulated over time and retrieved when you need it. Like, I don't, I actually don't even need to know this EOB right now, unless of course, whenever I need to know it, that maybe, you know, like for some benefits I need to figure out what do, what did I do over the past year and how do I apply it? Source:](https://image.24vids.com/tw-1994972575768727743/amplify_video_thumb/1994972220930621440/img/_5CCZJyz89oDfqQJ.jpg)
![[ condition update ] 🐻❄ In short of what happen with me is an inflammation on heart muscle from a virus infection which still cant be identified yet. The symptoms I experience are painful breathing, heart racing, tight chest, difficulty breathing, kinda thing. I’m told not to overwork my heart because it could make the inflammation gets worse. That’s basically in short. As for the details, it was 4-5 days ago, I started feeling uncomfortable in my chest, it felt tight and I had trouble breathing as well. Anytime I did something, like exercising or walking on a treadmill, my body felt hurt, and my heart rate went up way higher than usual. It’s normally around 100, but it went to 150 even when I was just doing little activity. It felt off, so I thought I might have caught some kind of infection. The other day I made a doctor appointment in the hospital as I got some free time. I was told to go to internal medicine doctor and was asked about what I’ve been experiencing. I had fever, waking up found tightness in chest at one night, a nausea, but nothing came out. I just felt like about to vomiting but nothing came out at all, so I thought it was unusual. At that time, my face went all pale and lips went all purple already, which why I decided to go to the hospital. Once I was in the internal medicine, well, they did some screening. I said I have low fever, painful breathing, body and muscle pain, so I was sent to ENT because I experience a ringing in my ear as well, I then sent to do a hearing function test. Right ear was normal, while my left ear was.. what’s it called.. ringing in ear. My left ear hearing function drops down one level. It’s not that serious but since it’s related to inner ear, and it's a part of nervous system, right? If it’s affecting that, the doctor afraid it could lead to permanent hearing function loss. Yeah, that part is concerning. So I was prescribed steroids to be consumed to prevent further inflammation and damage more than this. Not sure if I’m explaining it right, but that’s what I remember. I’m not a doctor, lol. And then, after I got the steroids and back home, I had work to film on the next day. I was like, why I feel so tired going for work at 6 in the morning, why my body feels this exhausting, just bending over to grab something or doing other things made me feel like I was gonna pass out. Thought I was just old lol. But at that time I felt unwell, my chest felt tight, and I felt exhausted. That day, I kept working even though I was exhausted. I felt like I don’t wanna work anymore, it was tiring, even just walking up the stairs, I had to stop and take a break. I couldn’t do it, it felt so tiring. When filming, just stepping my legs already felt tiring that I didn’t want to step my legs anymore. So that day decided to see a doctor, focusing to check my heart as it felt tight and was racing, and I had pain when breathing as well so I decided to see a heart specialist doctor but I arrived there at 2 PM and there was no available appointment anymore. Also, the Echo or ECG machine was all used so I had to schedule an appointment for the next day. I went there in the afternoon. Blood pressure and other test was normal, around 110-160, and it’s normal. Pulse is normal. Blood pressure was okay. And what else, yeah that’s it. I had an ECG, the result came out normal. I’ve also just get physical check up recently and the result were almost the same when compared. But since I still didn’t feel well, I wanted to know what’s wrong with me so I asked for a blood test. It’s a blood test that focusing on troponin and CRP level, which are enzymes in blood cells that indicate heart issues if the levels are high. After my blood test, I waited an hour for the results. When they called me, they said my symptom is serious, it’s a heart disease. Normal troponin levels are below 1 for healthy human, but mine was 3800, which is extremely high, so I had to be admitted. This is an enzyme level in the heart muscle cells. If heart muscle is damaged or its cells break down, the enzyme will mix into the blood and can be detected in the blood indicating a heart problem, so I need to be admitted for further examination with echo. It’s an ultrasound for heart. The result saying that there’s an inflammation in my heart as predicted by the doctors. The heart muscle is really swollen and… [takes deep breath] oh I’m tired already. It's enlarging which makes my heart race and feel tight and uncomfortable. That’s what they said. It’s not working the way it should, which is why I get tired so easily. So it answers everything. After the echo I took a rest and got therapy regimen… as what I understand, consuming steroid can suppress the immune system, right? They help reduce inflammation while the body fights the virus. It’s reducing the inflammation, right? But they said steroids alone weren’t enough because my troponin levels were way too abnormally high, so I got an injection instead. [deep breath] I got injected last night for only three dosage because I had to work today in the morning.asked the doctor to discharge me cause I had to work first. But the decision was taken with condition. I got injected three dosage in the morning and did another blood test which show a result of a decrease in troponin level from 3800 to 1600. Doctor said it was probably 5000 before this and it keeps decreasing to 3800, and to 1600, So if the work isn’t too hard physically, I’m allowed to go, I then go to work. Today at work I was only standing around and talking around. I can stand and talk, but I can’t do any heavy work as it’ll will make my heart work hard and affecting the recovery, I then have to walk slowly. But even so, I can’t even walk fast tho, I get tired easily. Yeah, that’s all. It’s not like I’m completely bedrotting or something, it’s just heart muscle problem, so… fighting ✌🏻](https://image.24vids.com/tw-1897270428084953113/amplify_video_thumb/1897264590565826560/img/jzS4KegPq6tUsXn4.jpg)
!["Tell us this isn't true." "They had a live being out [near Area 51]." "There were human experiments that went on." 👽🛸 Roswell: A Non-Human Craft or a Darker Secret? 🤫😶 (Transcript is shorter than clip. I don't have room to type more in this post so I'll just wait for replies.) ~ Lex Fridman: "In your book on 'Area 51,' you propose an explanation that I think some people have criticized, at the very end. That this might have been a disinformation campaign from, I guess, Stalin, that the Roswell incident was a remotely-piloted plane with a quote 'grotesque, child-sized aviator.' Just looking back at all that now, years later, what's the probability that it's true? What's the probability it's not?" Annie Jacobsen: (AJ): "So, you know, I've never revealed who that source is." Lex: "Yes." AJ: "You know that? Want me to tell you?" Lex: "Okay, who was the source?" AJ: "So, before I say anything on that, let me speak to the question that you asked, right? So, you asked me, 'What's the probability that that is still standing as an idea, 12, 13, 14 years later,' right? So, I continued to work with that source for years, afterwards. We talked about this. Look, I mean, his whole family knew it was him. And I knew his family because I was an integral part of, you know, I was at his house, met all his kids, grandkids." Lex: "And we should say, the source is the main expert advisor behind the story that it was. Maybe you can explain what the story is that your report in the book, that it was a disinformation campaign created by Stalin to cause mass hysteria in the United States. The very kind that we've been speaking about with the CIA and so on." AJ: "Yes! Predicated on the narrative of the 'War of the Worlds,' right? And the 'War of the Worlds,' when it was a radio program in the United States, made people go crazy. 'Oh, my God, we're being invaded by aliens!' Well, the government was always interested in the story and Joseph Stalin was, too. We know that from declassified documents, right? "And so, the source told me that the reason for this program, and that the real Roswell crash remains, were in fact, it was a black-propaganda hoax infiltrated, you know, or rather, predicated at this idea that you were gonna overwhelm America's early-warning, air-defense system, cause mayhem and maybe be able to attack the United States. That was the plan. And Stalin was also messing with the United States, messing with Truman, who sort of, you know, turned his back on him, right? At Potsdam. "And so, this idea, and the reason that the source is important... And unlike, you know, a lot of people, 'I saw this, I saw that, I learned that.' Was, according to the source, once it was determined that this was a hoax and that Stalin was able to get a craft over the United States, and it crashed. And it had, you know, people inside of it, they were people that were sort of deformed and meant...surgically altered to look like aliens. "The United States government decided that it needed to know what on earth that was all about, and if it was possible for us to have the same program. This, according to this source, right? And so, it sounds preposterous, and if it was just someone saying, 'I...,' you might say, 'Well, it's ridiculous, get them onto another subject.' But, the difference was, is this source, who was very well placed, and friends with all of the other 75 people, you know, told me this as a confession, right? A real, tearful confession, because what he said is he was involved in the American program to do the same thing. And people died, because there were human experiments that went on." "And I write about this in the last 12 pages of 'Area 51.' It was an explosive, you know, revelation, and I felt very confident in writing this because the source wanted it written. Why? Because he said, 'I'm dedicated to my country. I know about being committed to national security, and this kind of thing must never happen. And if you give people too much power, they will take advantage of it.' And he wanted it on the record. "And his wife of 60 years did not know until after the book published. Nor did His children, okay? So, after the book published, I was called to his house and sat there with his family. And they said, 'Tell us this isn't true.' And he said, 'It is true,' right? (We need a tape of this confession or...for his family to confirm they heard this from him.) AJ: "Now that source is Al O'Donnell, who is the nuclear-weapons engineer who armed, wired and fired 186 nuclear weapons, okay? So if you wanna talk about someone..." Lex: "Woooooow." AJ: "You're the first person I've told that on the record, but it's kind of about time." Lex: "Woooooow. Well, you received a lot of criticism over this story, and it confused me why, because it's...given the context of everything you've described with the CIA and other intelligence agencies, it is reasonable that such action would be taken. AJ: "And, the source is extraordinarily credible, right? If you wanted to take the position, 'Well, that person isn't very reliable,' then you have to ask yourself, 'Why did they have Top-Secret clearances that are higher than any in the United States whatsoever?' Because he was responsible for arming nuclear bombs. He was called the trigger man. "And by the way, he told me that I could tell the world who he was. There's a lot of details that are really dark, involving that program. And when is it appropriate, right? Well, it feels appropriate now. First of all, because you and I have been talking for several hours. So this is what is truly a long-form conversation and it's the outcome of, you know, a very long time of my reporting, and also being judicious about what, you know, closing the loop on that, right? Because I do think it's important for people to know that sources have revelations." Lex: "And, like you said, the programs, both on the Soviet side, and the American side, conflicting, I think's the term we used previously? Ethically, morally, on all fronts. People have done some horrible things in the name of security. In your book, 'Surprise, Kill Vanish,' you write about the CIA." ~~~ Jeremy Kenyon Lockyer Corbell: "So, today, I want to focus on a really important story that you once told me, that has never been told all the way [from the] beginning, to all the way to the end. And I just think it's just so cool we get to do this today. So, the question I want to ask is: After you got hooked on the UFO thing, with Bob Lazar, and you as a journalist said, 'I'm gonna start getting sources.' Like, 12 people coming at you, people shut down by the government. You can tell that. But you finally, finally got to a credible individual who had direct, firsthand knowledge about UFOs, exploitation, reverse engineering, and beings. And, oh my God, I want the world to hear this story. Tell us the story." George Knapp: "I've shared some of it in very broad strokes over the years- little bits and pieces of it - without ever actually referencing, in my statements, the guy the source. But this will be the first time I've told it in totality. "And it takes me back to when I first started in this. It's 1989 KLAS-TV, we put together, we spent eight months working on this project called 'UFOs: The Best Evidence.' Nine-part series. It airs on television, it's the biggest thing that's ever been produced for local TV, to this date, and still. "And, along the way, as I'm trying to find...telling the story about Bob Lazar, and his allegations about what was out there at S-4, near Area 51 - recovered discs, alien technology being reverse engineered - I'm looking for people who would support that. And I found about two dozen people, witnesses who had worked out there, who had seen bits and pieces, who could corroborate parts of what Bob had said about these kinds of craft being out there in the Nevada desert. But there wasn't anybody big picture who knew as much as Lazar claimed to have known, so I was still looking for them. "In 1990, I started working on a follow-up series to Best Evidence, looking for new witnesses. And I got a hint from an elected official that I had known, I'd covered him in Nevada politics. He says, 'You know, you should talk to my dad one of these days.' 'Your dad?' 'Yeah.' And he told me what the dad's name was and what he had done, what job he had had. And I said, 'Ah.' So I started stalking the guy. I just started showing up at events where I knew he would be. One of those events was a reunion for employees of EG&G." Corbell (JC): "So I'm assuming that this source was working within EG&G in some capacity, which is, by the way, who Bob [Lazar] said, hired him to go out to Site-4, S-4 at Area 51. So you're like, 'Okay, I can now find out if this is bullshit, or if there's an element of truth to it.' Do I have that right?" Knapp (GK): "Pretty much correct, yeah. So, I'm looking for someone whose credentials are impeccable. Unlike Bob, whose credentials were questioned, and people still attack him on where he went to school and where he worked, and was he at Los Alamos? This guy is documentable. There's a paper trail of where he worked, what he did. There's no question that he was in a position to know. He was the first general manager of EG&G in Nevada. His name was Al O'Donnell, and he has a prominent family. "When I heard that EG&G was having a reunion, I went there. We took a camera [and I figured], 'This is a great chance to get him on camera before I start asking him the questions I really want to ask.'" JC: "And when you say he is a general manager, like, does that give him certain roles and responsibilities that would give him insight? Like, he's not a secretary, so what does that mean?" GK: "He's the boss. He was the boss of the Nevada office. And I'll tell you a little bit about EG&G. So, it was a company that was created in Boston, right around the end of World War Two. Al O'Donnell had been in the Navy, serving during the war. He got out of the Navy while the war was still underway and went to work for a company called Raytheon, which became this massive, gigantic defense contractor that's still around today, still in Nevada in fact." JC: Yeah, they've got a big connection to the UFO topic, right? But, when you say Boston, like, where in Boston was it created?" GK: "Well, MIT is where the company was born. Edgerton, Germeshausen and Grier were the three guys, the EG&G in that. They were at MIT. Scientists, engineers, they created this company there. And Al O'Donnell, who had been working for Raytheon, working on the Manhattan Project. He didn't know he was working on the Manhattan Project, but they were building these devices, complex triggers, that allowed them to detonate nuclear weapons. He learned later what he was doing was part of the Manhattan Project. "He goes to MIT, starts working with EG&G. Their company in those days had, I think, 15 employees, Al said. So it was a very small startup. But it suddenly exploded because the American atomic program exploded in those years. In 1950, Harry Truman decides that we need a permanent, nuclear testing site somewhere in the continental U.S., so they looked at a bunch of places, and they settled on Nevada. "Prior to that, Al O'Donnell had been sent out to the Pacific. They had five of these massive, atomic bomb tests out in the Pacific, and they decided to move it into a continental U.S. location and Nevada's Test Site - it was called the Nevada Test Site in those days - was chosen. Al O'Donnell leads the exodus from Boston, out to Nevada. They start hiring engineers and scientists, physicists and other security, spies." JC: "What are they working on at this time when they make that move?" GK: "Atomic bombs. They're building, testing atomic bombs. EG&G was a really precise organization that was created in order to detonate, measure and photograph atomic weapons. If you look in the history of photography, you'll see some of these amazing photos that they took of, you know, water drops dropping in water and...they're pretty famous shots because of these cameras that they developed. And it was perfect for use and testing atomic weapons and documenting what the process was. "So, EG&G comes out to Las Vegas, they are the managers of the Nevada Test Site. They, subsequently, years later, become the managers of Area 51 when it opens in 1955. So Al O'Donnell is the top guy. He oversees the nuclear testing program out there, manages it for EG&G, works with the Atomic Energy Commission. He has a Top-Secret security clearance and he can go anywhere and see anything. There's, basically, no restrictions, nothing that is outside of his ability to find out and see." JC: "So, this is an impeccable resume. This is somebody who was in position to know, and would know if someone like Bob Lazar was telling the truth or not telling the truth. I find it, personally, humorous that EG&G was, its genesis, its seed, came from MIT, right?" GK: "So, late 1990 or early 1991, I'd have to look up the dates. But somewhere in there is this event, this EG&G reunion. I go there, we got a camera, I interview Al O'Donnell, introduce myself, and say, 'Hey, I'm really interested in this, can we continue this conversation?' So he invites me to his home. He says, 'Come on over, we'll arrange to come over on a Saturday or something. We'll sit down, I'll go through my scrapbooks and show you some documents and memorabilia and photos from that era.' I was like, 'Great.' "So I go to his house and meet this wife. And we sit down, he opens up these big scrapbooks, and he starts showing me all the stuff that he had done. Photos that had been taken out in the proximity of these gigantic nuclear tests. They had great stories about the camaraderie that developed among the engineers and scientists. And he's going through all this stuff and showing me all this. And I love it, I loved every bit of it. I've never had a bad day at the Nevada Test Site, by the way. Every time I've gone out there to do a story, it's just a terrific way to spend some time." JC: "Secrets should be kept, secrets are kept, and you are a proponent of keeping secrets when it's that kind of thing." GK: "Sure, absolutely. And I respected the boundaries that they set up for us in doing these kinds of stories. So I did go out to the Nevada Test Site a lot over the next 40 years or so and put together a lot of different stories. And they knew of my interest in that area that's just outside what the Nevada Test Site, a place called Area 51. In 1955, Area 51 was, basically, created and EG&G got the contract to manage Area 51, and had kept it for the next 30, 35 years. So, whatever went on out there, they had an inside knowledge of what was going on." JC: "So, you meet this guy, Al O'Donnell, for the first time when he's at this public thing. You probably say something like, 'Your son told me to talk to you,' or something. Whatever. It ends up, he invites you to his home, and you're going through scrapbooks, and he's showing you all this atomic testing stuff that he was involved in. GK: "Yeah, and I'm telling him, 'Boy, this is really interesting. That's fascinating. I'd love to do a story on it.' And after we're there for maybe two hours, he closes this one big scrapbook and he goes, 'You're not here to talk about this, are ya?' I said, 'Well, not exactly.' He says, 'I know what you're here to talk about. I know what you want to ask about.' And right about that point, his wife walks in and she says, 'Don't start telling them that stuff! Don't even tell him!' And he kind of joked about it.' JC: "What were you there to talk about?" GK: "UFOs, UFOs. Area 51, Bob Lazar, crashed saucers, reverse engineering, to see if he had any knowledge of that, because I'd been led to believe that he did. So he closes that book and he says, 'We'll have we'll get together another time and we'll talk about it in private.' And over the course of the next two years or so, he and I would meet at coffee shops and talk about it. And I would ask him questions, and really, it was like pulling teeth. He wanted to tell me stuff but he made me work at it." (AJ says his family was there for the confession. Knapp has over two years of meetings with him. A bit confusing.) GK: "And the condition was, I couldn't take any notes. I couldn't record it, I couldn't take any notes. So each time I'd meet with him, I'd rush back to my car and start scribbling notes on pieces of paper so I'd remember everything that he said. And the story that he told me, that evolved over those couple of years was pretty fantastic. "He said that they did have a flying saucer that had been recovered from New Mexico. I think he indicated that it had been taken from New Mexico to Wright Patterson Air Force Base, which is... He never said Roswell, but I think it was the Roswell incident is what he [was] talking about. And it confirmed some of the details about what we know, likely, happened with the Roswell craft." JC: "When he's telling you, 'We have recovered a craft,' did he say it like, this is secret, don't tell anybody?" GK: "Yeah, it was just for my knowledge, my background and information. It wasn't a story I could do then. We were negotiating about how, or when, or if I could ever use that information or make it public. He told me the details about this craft. He said that it had been stored at Indian Springs. Indian Springs is an Air Force Base that's been there for a long time. It's now called Creech. Indian Springs existed before Area 51 was made. "But he says it was there, they kept it there. It might have been in an underground facility, I'm not quite sure. But then when Area 51, after it opened in 1955, they moved it to an adjacent facility. He didn't say it was S-4, he didn't say it was Papoose, but I think that's what he's talking about. Papoose Lake is where Bob Lazar said he worked, and where they had built nine hangars underground, disguised to look like the desert, and where they had other recovered craft. "He says they worked on this recovered craft, reverse engineering, trying to figure out how it worked, who built it. Whether or not they could duplicate the technology because, apparently, they thought this was pretty advanced, and they'd like to be able to build more of 'em. "And he says it was a very closed program, very small. It was only, I think, five of them that were aware of it, at least in the early stages, that were working on this project. And it was very hush hush, and they didn't share it with anybody else in the company, or anybody else in the area, or the military. They just kept it to themselves. "So, after we're having these meetings - and I go back and write down all these notes and stuff, details about what he had shared with me - we have another meeting at a coffee shop, and I said, 'Well gosh, you know, aren't you worried that it would get out, that the word would get out?' "And he says to me, 'We were worried It would get out?' That's right. 'I mean, what...it? What do you mean, it?' It. Meaning a live being, they had a live being out there. I go, 'You had a live being, an alien as well?' [O'Donnell said], 'Tell you the truth, we didn't know what it was.' I said, 'You know, maybe it came from millions of miles away, out in space, and you're keeping it in a cage near Area 51?' He said, 'To tell you the truth, we couldn't communicate with it in the beginning. We didn't know what it was, we didn't know where it was from, and we didn't know what to do with it.'" JC: "When Al O'Donnell says to you, 'We had a live alien, a being,' obviously from another world, what was your feeling?" GK: "Well, I was overwhelmed, because it was, in effect, confirmation of things that I had come to believe, because of the reporting we'd already done. And then the evidence of cover ups and lies that had been told to the public. Here's this guy in a high position, with a high security clearance, telling me that it was true. That they really did have a craft and they had a being. "My second feeling was, one of overwhelming sadness for the being, whatever it was, you know, that was kept out there. I asked him, you know, what had happened to it, what became of it? He says, 'I don't know. I don't know whatever happened to it.' But it was out there for a while, alive, and eventually they figured out a way to communicate with it. "And so I asked him, 'Well, what did it look like?' And he made me guess, as he did with all these questions. He made me guess. He said, 'Well, it kinda looks like a certain political candidate.' I said, 'Well, who? A political candidate? Who?' And at the time, Ross Perot was running for president. He said, 'It looks like Ross Perot. A little skinny guy with a big ears and tiny head.' Not a classic Gray-looking alien, but a very odd-looking creature with really big ears, that looked like Ross Perot. And I laughed. "And so we had these conversations for a while, and I was blown away by the information that he shared. I took all these notes. I was hoping that someday, I might be able to get the information out. And I asked him, 'Look, you're getting up there in age. If I can't record something with you, could you record a statement to the effect of telling me the story on camera, and then when you pass on, I can have the tape?' And he said, 'Yeah,' he would do it." JC: "You know, look, I've heard a lot of wild stories that I can't verify. A guy's telling you something, and you get a sense as a journalist, when you go down a road with somebody, and you take your time and you vet it... Did you feel...I mean, is there any world where he's trying to f*ck with ya? Or is there a world where he's trying to, you know, dissuade...kind of put crazy information into your brain? Like, how did you feel when he was telling you this? Was he like, straight with you?" GK: "Yeah, he was very straightforward. And again, this was not information he was giving up, willingly. I mean, I had to really dig and coax and arm twist to get him to cough things up. And it was very slow-going over about a two-year period, maybe a little bit longer. And I know that this...you always have to be wary of people with different agendas and people that just make stuff up. I didn't get that sense from him because of his standing in the community. He had shared this story with members of his own family." JC: "And that's why they came to you, is because they kind of [gave] you a tip. And these members of his family, they're serious people, too." GK: "Yeah. One of his sons is an FBI agent, or was, he's passed on now. One was an elected official in Nevada. That was the one that gave me the tip." JC: So, I just want to nail this [down] so I understand. You were approached because he had shared this with his family, privately, and then you had to kind of coax to get through to him about the story?" GK: "Right." JC: "I think that's important because look, these things don't happen, like, people [don't] just come to us and say, you know, crazy stuff, and we're like, 'Hh, yeah, cool. Sounds good.' Like, the dynamic of that, socially, as a journalist, like getting in there, taking time. You know, we have to verify if what he said is true, and there are some major bombs coming about that. But it's like, that process is so important. "So here you are, you're sitting with him, he tells you now, they have a live alien. And you felt sad because you're an animal-rights activist, you love animals. I know with your cats at home and you've done horse stories and all the stories about like, the inhumane stuff to animals. So it made you personally sad, makes me sad, too now thinking about it." GK: Yeah. Well, we had these series of meetings, and then the last time we met, after he'd agreed to go ahead and record a tape - and give it to me after making an arrangement so I got it after he passed on - he said that he had been told to not talk to me anymore. He said he had been given a warning [and] it was not a good idea for him to talk to me any more about anything. Not just that topic, but anything." JC: "Well, who knows that you're talking? Who would warn him?" GK: "I don't know. I don't know. But you recall, back in those days, there was surveillance. We had our phones tapped at KLAS-TV. There were guys following us around. Me, Bob Lazar, Gene Huff, maybe Robert Bigelow." JC: "People were also coming to your news station, OSI. And they would come in and try to like, get to you and then they'd show you their card...and take it back. And you know your phones are tapped. So it's like, because of this story, all of a sudden you're on high alert. So, anybody could have called him, been watching you, had meetings with the guy. So what you're saying is one day he just said, 'I can't...I'm not allowed to talk to you any more.'" GK: "Yeah, I've been told not to talk to you anymore. I've been told not to."](https://image.24vids.com/tw-2079616298435400152/amplify_video_thumb/2079612656366112768/img/mxq1uM4Cp0iG8pyw.jpg)
![The most epic 13 minute AI rant I've heard in 2026 PS: My parent's heard this when I was playing it in the car and thought Jason ✨👾SaaStr.Ai✨ Lemkin went OFF like Stephen A Smith does on first take PPS: Full transcript below [17:00] Harry Stebbings: I I just wanted to ask Jason, if the people that we want are fundamentally different, the developers that we used to hire, we don't because AI writes the code for us. The marketers we don't want, the sales people we don't want—who who do we want genuinely? Like what is the attractive profile? Because your Anthropic’s and your OpenAIs are hiring, so so what are the people that we want in the companies of the future? [17:18] Jason Lemkin: Look, I know it sounds trite, but but the answer is simple. It's just the expression each year changes. We want folks that are genuinely AI fluent. It's pretty simple. Now you know, maybe last year we called them prompt engineers, right? That used to be a job. I don't know if you remember that actually used to be the hottest job on planet earth. Now no one needs a prompt engineer because it's pretty easy to prompt all these tools. That job died. Okay. Um and now we need go-to-market engineers. Um I think that job's going to die. We need—everyone needs so many forward deployed engineers. Like you can't hire enough forward deployed engineers. But uh you know um but Palantir just announced in whatever their their big their big event—they've gotten their deployment times down over 90% with forward deployed engineers. So that may become—so the this wave of disruption for the titles and the specificity, it's also exhaustingly accelerating. But it's really simple. You meet anyone for any role—sales, marketing, engineering, product, QA—they're they're either they're either they can't keep all of the ways they use AI to accelerate their job from spewing out of their mouth, or they're staring at you. It's there's nowhere in the middle. Like, and the person that comes in and says—it's it's it sounds Captain Obvious—but like, you know, you just had the whatever from Lovable, the the marketing head that was super popular on the show, right? She's just spewing AI-native insights into Lovable, right? It's not that complicated. You hire her, Elena, or whatever it is. You just hire her. It doesn't matter whether she's still in college or a junior or a senior or a middler, a left or right. And honestly, if you interview people, I would say of all even of the best startups I've invested in, maybe 30% of the management team meets this standard at best. 30%. Maybe less. And of the interviews I do in general, it's single-digit percents. It's just and in in that sense, it's the same as ever. Like you either lower the bar in hiring or you hire someone that's actually great. And someone that's actually great is so far ahead of you in how to apply to to employ the efficiencies of AI in their role, your jaw falls on the table. The difference is we used to need warm bodies. That's what's changing. We used to need warm bodies to answer the call, to do QA, to do code review, to to get the blue pixel to go from the upper left to the lower right. You laugh, but you need you literally needed to brute force this with humans. With AI, every day that goes by, the AI—you do not need brute force human beings on your team. And that's another reason they're shrinking. Why are all these new companies so efficient? They're just not brute forcing things with humans. They're just not. They're choosing not to. And so these team—all the brute forcers out there—everyone talks about how bloated teams got in 2021. I don't agree with that. I think they got as big as they needed to be when growth was high and you needed humans to do everything. All you look at these teams that that doubled—well if growth continued at 60% like the rate in early 2021 for 5 years or can help me do the math and every single thing a software company did required a human. You were understaffed by your 2021 headcount. You'd be sitting here in 2026. You every office in SoMa would be triple packed and you there wouldn't be enough humans to staff your company. It's just the world changed. [20:33] Harry Stebbings: Jason, you live on the bleeding edge. I think me and Rory see that and I think the world sees that when they hear you every week in terms of how you run SaaS. For all of the CEOs and execs who listen to the show, what would you advise them in terms of determining whether someone is AI fluent when they meet them for jobs, for talent? [20:51] Jason Lemkin: Here's I realized I was just asked this. I just did a review with a super fast startup growing just crossing 100 million and I was asked this question. And one of my favorite executives, I thought his answer was pretty dated and because he gave me an answer that was about 6 months old. The answer 6 months old is: "I look for folks in my team, I look for you know at what tools they play with." Okay, that was a great answer in like summer of 2025. Okay, I tried Lovable last week. Okay, the answer in 2026 is: "What commercial AI tool have you brought into your organization this month?" That's the test. Anyone that is on the bleeding edge that you would want to hire—now there are so many great products in the market. Okay, there is no excuse in any role to have not brought one tool a month into your organization. Okay, there—now there's going to be better and better tools and better and better products as the year goes on. What's the one you did? And you will see folks with their deer in the headlights to this question. What what sales tool? What marketing tool? What product tool? What engineering tool? What did you bring in? Why did you pick it? How does it working? Because if you're at remotely at the cutting edge, you're all over this. You're looking for the next agentic tools that will radically improve how you do business. This is—you think everyone thinks SaaS is at the bleeding edge, right? You know, you know, all we do is we're just looking for the tools and trying them. Okay? Okay, we're one year ahead of everybody else because we did the simplest thing in the world. Like we tried the tools early and we trained them. We trained them for a month. Okay, I'll give you—want hear a horrible example from this week? Super hot AI company valued at 6 billion. Okay, I'm not going to name it. Um, this week yesterday told us we had to quadruple what we spent on their product. Okay, their agent told us, right? And why did this happen? Okay. Well, at this $6 billion company, no one had trained the agent on its pricing properly. No one had tested it. They said, "Well, well, we've been in beta." And we said, "Well, when did the beta launch? A year ago." Okay, these are people asleep at at the wheel. You want somebody who the instant this comes up, they exactly know what the issue is. And "Hey, when I was at Lovable Replit, we trained the agent. This is how we did it. I brought in this tool. I brought in this tool that that Rory invested in last week. It solved all these issues." That's what you want to hear. And if they haven't brought in a tool in the last 30 days, at least deeply evaluated it. I don't really care whether they bought it, but gone so far down the funnel they can tell you—pick whatever tool: Fixie, Regie, GC, AIGC—I don't care how you went through it, you looked at it, you can tell me the eight ways it would improve the productivity of your business and three you didn't. Just don't hire that person because they're going to run your company to the ground. This is the job today. The job today is not to screw around on ChatGPT and to be a prompt engineer. The job today is to bring the best AI and agentic products into your organization and leverage all the hard work that the engineers have done building those products. That's your job. You don't have to screw around. You don't have to be a prompt engineer anymore. You have to be an agent deployment expert. A—this is the new job we're making up today. An Agentic Deployment Expert. That's your job from C-level to junior. Agentic Deployment Expert. Don't hire anybody else. You're going to regret it. They're going to stare at the camera. He's good. Stare at the camera. He's honorable. We could probably just I could slip away, get a coffee, and come back. No. And I I sound exasperated, Rory. And I—but the reason I am is I can just see I can see my best companies doing it. And I can see some companies I've invested in not doing it. And I want to cry. I just want to cry when they have no ADs on their team. I just—like you're flushing your years of your life down the toilet by not approaching your how you're building this company this way. [24:33] Rory: Yes. And at the risk of being positive, it's worth pointing out two things he didn't say. Well, something implicit why he said—Jason didn't do the only hire, you know, he didn't commit the um employment law, I think it's a civil penalty of saying only employ people below X who get the new new thing because he implicitly said anyone can do it provided you're willing to learn. And I think that's the big aha that's one of the positive statements to make here right? Look and I think it applies—I'm always wary of being "Hey, coming across, hey this this is the things that you all have to do." I think it applies to everyone including investors right? I mean I will say I have found that unless you're willing to invest the time learning these tools you actually shouldn't be investing in them. One of my partners Andy had this expression: "You know, if you decide you want to stop learning new things you probably should retire within 6 to 12 months and never write another check again." Maybe that's down to 3 to 6 months at this stage, right? And I think, you know, it's— [25:27] Harry Stebbings: Yeah, I actually I actually had a meeting with mine and Jason's biggest investor the other day and I—pretend he's not here—I said I think he's the most equipped investor for this generation of investing because I don't think anyone quite sits at the bleeding edge like he does on the investor side. [25:42] Harry Stebbings: Why in terms of using the equip stuff? Yeah. Yeah. In terms of using the stuff, understanding understanding bottlenecks, constraints. For sure. [25:51] Jason Lemkin: But can I just add one point? We can just cuz it's so important if it helps people. Okay, we are—and thank you Harry. We're going through these phases. Okay, and when AI started to blow up for real for us, uh call it early 2024, right? Maybe late '23, I wasn't equipped. It was too technical. I wasn't going to go in and figure out—I wasn't smart enough to figure out how to deal with a massively hallucinating LLM API and turn that and turn that into something magical. Kudos to investors and others that that got it in early '23, '22. I mean I remember I—I guess it was maybe SaaStr Annual '23. I was with David Sacks and I did a Q&A and I said, "How you thinking about AI at Craft?" He's like, "Well we're all in. We want 80% of '23 of investments to be AI." I'm like, "Great but like show me the show me the great ones in market." He's like, "They're all prototypes. We're all they're all they're all proof of concepts but we're all in anyway." That's where you kind of had to be in '23 if you weren't investing at like the LLM level. Okay, I wasn't smart enough. Then we went through this weird-ass prompt engineer era where like you you could torture these products to do something good, right? But you had to torture them. You had to like craft these crazy things that made no sense. Now we are in the era where mere ordinarily smart generalists can make these tools do magical things. And literally I go to these meetings and people be like, "I don't know how to like this is so scary. I don't know how to do this." And we show them our backends. Do you know how to do a workflow generator? Do you know how to do a a decision tree? Like we've been building these since software in the '90s. Okay, if you—I can show you all of our agents. The how they work is novel. They do have to be trained. You can't be lazy and have these agents work. But honestly, the the UI, the UX, the way we interact with them, it's just software. And so my point is: Pick yourself off the ground. This is your time now. If you felt lost in AI era, if you felt like you're behind, you don't understand what all these people are saying on X and Twitter and their Claude and and their and talking about all the 4.6 point Nano point and it's over—like you just it's not your world. This is your time. This is your time for the generalist that knows how to use software tools really really well. And I—this is my last point but it's so important. If ever in your recent life—and this is why you could be all you need to be is young at heart to Rory's point—if in the last three to five years you have successfully deployed a piece of enterprise software of any sort you yourself, not some agency you hired, but if you have deployed it, you can deploy any agentic tool. Any. And you can become the hero in your company and you can become the hero in your functional area. But I watch folks—I'm literally helping a company now that they're adding hundreds of sales folks this year with a new pre-IPO COO—he's not hasn't brought in a single tool, totally scared of it. Okay, it's not that hard. Did you use SalesLoft? Did you use Outreach? Did you use HubSpot? Do you know these tools? If you can deploy these tools, you can deploy a world-changing AI agent. And so this is the time for people like the folks that that were shut out of the AI revolution right now. The generalist folks that are not that know how to deploy software that don't even know how to build software. Like vibe coding for me was folks who knew how to build software, but you didn't have to be an engineer. Now, you just need to know how to deploy software to win with AI agents. That's all you need to know. So many people have these skills and they're petrified of AI. "How did you do that? How did you deploy an AI BDR?" Well, we bought a piece of software, we figured out how it worked for a day, we set it up in an afternoon, and then and then we did spend 30 months training it, which you didn't do with this old software because in the old days, we just had to manually upload all the data, right? And there was no training. The the only non-intuitive part is training these things. And it's it's it's just work. So that's why when I see folks on the management team not doing this, there's no excuse. You do not need to be technical to win with AI agents in Q2 of '26. You do not need to be even 1% technical. Not at all. So it's your time. Or you're going to get laid off. Or you're going to get laid off because you're not going to matter.](https://image.24vids.com/tw-2036795243681423518/amplify_video_thumb/2036794127560613888/img/52_cdbzzL6_foTSI.jpg)