Loading video...
Video Failed to Load
๐๐ญ๐ฎ๐๐ฌ ๐๐ฉ ๐๐๐ฅ๐ฅ๐จ๐ฐ๐๐๐ง ๐๐ฉ๐๐๐ข๐๐ฅ ๐ Ryon Scott-Douglas, Rory Jennings ๐๐ฆฉ & David Bentley are joined by the legendary Ally McCoist this week. ๐ช ๐๐ต Old Firm preview ๐ป Scary Mount Rushmore ๐ฅ And a Gazza classic You don't want to miss it. ๐ 18+
0 Comments
No comments available
Comments from the original post will appear here
![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 โจ๐พSaaStr.Aiโจ 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 wantโwho who do we want genuinely? Like what is the attractive profile? Because your Anthropicโs 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 needโeveryone 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 eventโthey've gotten their deployment times down over 90% with forward deployed engineers. So that may becomeโso 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 roleโsales, marketing, engineering, product, QAโthey'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 saysโit's it's it sounds Captain Obviousโbut 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 AIโyou 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 teamโall the brute forcers out thereโeveryone 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 doubledโwell 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 hireโnow 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, thereโnow 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 isโyou 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 youโwant 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 youโpick whatever tool: Fixie, Regie, GC, AIGCโI 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. Aโthis 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 Iโbut 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 justโlike 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 saidโJason 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 appliesโI'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'sโ [25:27] Harry Stebbings: Yeah, I actually I actually had a meeting with mine and Jason's biggest investor the other day and Iโpretend he's not hereโI 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 areโand 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 outโI 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 IโI 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 youโI 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 overโlike 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 Iโthis is my last point but it's so important. If ever in your recent lifeโand this is why you could be all you need to be is young at heart to Rory's pointโif 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 folksโI'm literally helping a company now that they're adding hundreds of sales folks this year with a new pre-IPO COOโhe'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)
![Just in $AMD Anush "Speed is the moat"|ROCm๐๏ธ 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)
![I asked Grok to summarize the overview I provided of the ongoing war between Karen Read and Aidan Kearney, in particular the section wherein I deploy the Manhattan Project to explain why Karen used better compartmentalization than Aidan (thus setting herself up for victory). The Manhattan Project Analogy: Ah, the Manhattan ProjectโGrant drops this as the "archetypal example" of compartmentalization, using it to explain why no one (not even insiders) sees the full picture in ops like Karen's or Aidan's. It's not just history; it's a blueprint for why leaks like this recording hit so hard. Here's Grant's breakdown, paraphrased and expanded for context: Historical Setup: During WWII, the U.S. raced to build the atomic bomb. Led by J. Robert Oppenheimer at Los Alamos, NM (desert isolation for secrecy), it involved ~130,000 people totalโbut zero full-picture access for most. Goal: Win the war without leaks (or Japanese spies spotting it). Core Mechanic: Siloed Knowledge: Los Alamos: Elite scientists (e.g., Oppenheimer) handled core R&D. Even here, info was need-to-knowโe.g., Operation Paperclip Nazis like Wernher von Braun (V-2 rocket guy) worked alongside possible communist sympathizers, but no one knew the endgame. Oak Ridge, Tennessee: The "production" hubโa secret 20,000-person "government town" (still exists today). To hide from aerial recon, they draped canopies over the entire site to mimic forest. Workers (engineers, laborers) toiled in ignorance: Example: A guy feeds a single punch card (1940s code line) into a massive green computer. He doesn't know what it codes, why, or even the machine's purpose. Just: Insert, output, repeat. Multiply by thousandsโboom, uranium enrichment without risk. Why It Worked: "You do that with all the people working on a project that's very top secret (except for a select few high up)." Weak links? Minimal. One leak doesn't topple it. Ties to the Drama: Grant flips this to modern players. Aidan's Version: Rudimentaryโparalegals like Olivia/Tina handle PR/logins but don't see the "full picture" (e.g., his flip risks). Meredith O'Neill becomes the leak about the recording played for her at lunch because she is smart and she does eventually see too much (just like Lindsey Gaetani before her). Karen's Mastery: Pro-level. Her finance/academia fam (Bentley University ties) screams gov recruitment pipelineโacademia as "front" for talent scouting (e.g., intel via international money flows). She "understands the apparatus" (DNI hierarchy), so she deploys limited hangouts/double agents like Natalie. Result: Aidanโs recording "signal flare" to Alan Jackson and David Yannetti (his flip threat) gets mirrored by Karen's public nuke after the recordings and Read's messages to Flipperhead are releasedโeroding Kearney's base without directly exposing Karen's crushing blow. Grant's Point: Kate Peter/Tully are "children" at this; Karen's moves (e.g., burning Aidan now) only make sense through this lens. It's not emotionโit's chess: "If you show Karen Read anything less than respect, she's gonna fucking own you." Grant wraps by noting Karen's parasocial "complex" (stronger than Aidan's "brand") gives her leverage. He admits partiality ("I think she's responsible for John's death") but respects her ops savvyโpossibly from her dad or self-taught intel. **Transcript: Grant's Analysis on Karen Read's Tactical Maneuvering and Compartmentalization** [Warning against crossing Karen Read] Grant: ListenโI would have told you this. I probably said it on stream before. You are out of your mind if you fuck with Karen Read. Likeโit's one thing if you are like on her level and matching wits with herโlike she's gonna grudgingly show you respect. I'm telling youโI've seen it in her eyesโbut you can't fuck with her, and you certainly can't threaten her. I would not do that. I don't know who the fuck her parents know. I don't know who she knows, but broโlike it's politics. She's smarter than you. Don't threaten her. What the fuck? And that is somethingโlike if you show her anything less than respect, she's gonna fucking own you. And that's what she did. Because the respectful way to do it would have been like a diplomatic meeting. And they must have been at a point where Aidan couldn't get that. So he did the most disrespectful thing possible where he tried to like corner her through like extortion almost. That's what it sounds likeโalthough Aidan denies it. Thatโlistenโforget about like how a normal person would react. When you're talking about a very influential operator like Karen Readโwho has this very savvy understanding of the public mindโyou're fucked. Because she's gonna know immediately what you just did. And she's gonna counter it with the thing that's gonna hurt you the most. What's gonna hurt Aidan Kearney the most? His support being dwindled down to only his core loyalists. And if he's rightโand you'll hear it in the conversationโif Aidan Kearney is right, that most of who he is is because Karen Read and her supportโoh my goodness, folksโlike thatโthat means that Karen controls whether Aidan can continue this fight. If Karenโwhen sheโthat's why I want to listen to this whole conversationโthere's no doubt in my mind she's pulling his support and pulling the rug under him because she's afraid that either he cooperated or he's going to cooperate. If she pulls the rug from himโokay, listenโhe might be able to escape the criminal charges, but do you think Aidan Kearneyโa man who thrives, in my opinion, on attention, numbersโfrom knowing that your words are impacting someone or the platform is reaching peopleโdo you think he's going to enjoy being in a position where heโthe very people who made himโand it wasn't just Karen; it was her supportersโnow loathe his existence? And heโnot just thatโthey are like tactical operators. Clearly Karen knows how to do counter intelโespecially if she sent Natalie as a double agent to get information from the state police using Kearney as leverage all the way back in 2023. She understands the world of intel. I don't know howโI think it's her dad. I'm pretty sure becauseโand it could be her tooโbecause like you don't get involved in the world of international finance on a fuckingโlikeโwhat is itโthe sort of leisurely level. It's not a pastime. You either do it because likeโyou're really fucking good at making money from the stock marketโorโand these two weren't; they're not that wealthyโor you're giving information to the government. Why do I say that? Because the world of international finance is the most valuable intel sector you could possibly imagine. You can commit or try to commit any number of international crimes if you're threatening the United States of America. But I guarantee you're moving money around to do it. So who's the best possible sources for that? High-level financial people. So I don't know if either they were a Jasonโand they were also academics. Okay. And a lotโwhat folks have to understand is when Iโwhen people say like academiaโit does not mean that you are just smart. Anyone whoโwho's good at studying could become a professor and be in academia. What a lot of folks should understand is that academia is a front for the government. It has always been a front for the government. Where do you think they headhunt from? Academiaโwell likeโat the higher you get up the academic ladderโall you're really doing is getting more and more involved in the government. I'm not saying anything that anyone involved with this does not know. Like high-level academics are involved with the government. That's like the backbone of our system. Now a lot of the actual educationโI think it's gotten a little out of hand with some of these majors, some of these colleges and universities who are offering [them]. That's not the point. The point is to create aโcurate a talent pool to make the United States stronger. And a lot of it is government recruitment. Okay. And so Karen Read being all the way up at the top at Bentleyโwhich is a very interconnected university with the government, trust meโthat just makes me think she understands thisโwhether she was a Jason. Listenโyou can understand what the intelligence community does without being in it. I'm not in the intelligence communityโI just report on the government. So I kind of see how it all works. You can understand it without being in it. But if you're in itโlet me just tell you right nowโif anyone Karen Read knew professionallyโthrough family or otherwiseโis in the governmentโand I'm not talking about a special agent like in the FBI or, you know, a case officerโI'm talking about in the apparatus of control. Okay. In the directorate of national intelligence somewhereโthere's a hierarchy. All right. If she knows anyone who understands all thatโthat's why she was able to pull this off. Because it's notโthat's why I'm not fawning or being gratuitous. I don't necessarilyโI'm not partial to Karen Read. I think she has liability for John's death. What I am is cognizant of what she's capable ofโso I can understand what's going on. A mind like that, okayโdoesn't just do PR. PR was not going to help Karen Read here. Natalie and her PR and all that stuffโnone of that was going to work. What Karen Read needed was counter intel and intel knowledge. [Explanation of compartmentalization via the Manhattan Project] When I say compartmentalizationโwhat you all have to realize is I'm talking about how the Manhattan Projectโthat's like the archetypal example of compartmentalizationโhow the Manhattan Project to develop the bomb that won the war for the United States in World War IIโhow that worked. The way that that worked is you had Los Alamos, okay, in New Mexico with Oppenheimer and whatever the hellโsome of the Operation Paperclip peopleโwhich I'm not very happy with. We took Otto von Braunโwho developed the V2 rocket for the Nazis. We brought him over via Operation Paperclip. We implanted him at Los Alamos with fucking Oppenheimer. I'm pretty sure it was like a communist sympathizer. Anywayโwe sent them down to Los Alamosโthe actual research scientists working on the core of the bomb. But to develop a nuclear bombโyou need 20,000 people at the time working simultaneously on production. You're not going to do that at Los Alamos. One: why would you ever expose them to the inner workings of the tech? It's nuclear material. You are not going to have 20,000 people around it. That's why it was in the middle of a desert. Third of allโthey would know too much. So what did they do? Okayโlook up Oak Ridge, Tennessee. Oak Ridge, Tennessee is a townโit's a government town still to this day. It's one of the mostโit's not as top secret as it used to be. But back in the dayโlike during World War IIโthey put fucking canopies over the whole thingโ20,000-person townโcanopies over all of it. So it would just look like trees from the air in case the Japanese managed to come and bomb us. They never didโthank God. But anywayโat least on the mainlandโobviously they got Pearl Harbor, and we're still upset about that. But the point is Oak Ridge, Tennessee, okayโit had people employed across a number of disciplines, all rightโand they would go intoโI'm giving you an exampleโone guy would go into a room, all right, and he would walk up to a giant computer. It was an old computerโwe're talking the '40s hereโit was a big computer, like a big green box. He would take a punch card. Okayโthis is how you used to codeโwrite computer codeโhe would putโtake one punch card with one line of codeโput it in the machineโtake it outโput it down. He had no idea what he was doing. He didn't know what the punch card had on it. He didn't even understand what the machine did. That's compartmentalization. He's likeโyou do that with all of the people working on a project that's very top secret. So if you're thinking as Karen ReadโAidan Kearney does like a rudimentary version of itโeven Tully does a rudimentary version of itโand Kate Peterโcompared to Karen ReadโKaren Read, Alan Jacksonโwhateverโunderstand the intelligence community. I don't fucking know how, but they do. So they compartmentalize. That's how they have pulled this whole thing off. They compartmentalizeโno one ever really saw the full picture. When youโif you are a schematic mind like thatโwhen you do something like reveal that Aidan Kearney has sent you a recording of conversations between you because you want the public to know that Aidan is doing this to youโyou are tactically sabotaging him. Why you do that at this momentโwhen you are an expert in counter intelโthus requires that level of understanding. You cannot just say, "Oh, I don't like Karen Read; she must be a moron." Noโif you want to understand why she's actingโyou have to think about her tactical intelligenceโbecause then you can reconstruct what the goal of this move is. It can only be designed to kneecap his support. I meanโwhen I say kneecapโI'm not talking Tonya Harding beating the woman at the ice rink. I'm talkingโyou can make it so this man's numbers are lower than Kate Peter talking about Cyraxxโlike 2,000 views of video, if that, all right. That's what it will come down to. And she wants him to feel that. I think that it's a little bit likeโit's 97% tactical. It seems to be that this is the moment where she feels he needs to lose all his supportโlike right now. Secondโit feels a little like a little personalโlike it's not just that she's causing him to lose all his support. There are ways to do that without doing this. I believe what Karen's really done here is she's taken the one thing from Aidan that gives him the strength to keep going day to dayโwhich is his public persona and imageโhis supportโher support. And so he can go around saying all he wantsโ"I owe it to Karen; she made me"โdo you think that's how he really feels? Or do you think he feels that he's the only reason she's where she is? Nowโif that's how they each feelโyou're at a stalemate. Aidan thinks he's the reason Karen got to where she is. Karen thinks that she's the reason Aidan has support and is known in the region. Who's right? Who's right? That's what this conversation is going to be about. And I'm telling youโKaren's right. Karen has more support than Aidan Kearney. Okayโit's just a basicโyou can look at the numbers. Karen has more support than Aidan Kearney. Karen has more loyalists. KarenโI don't even understand the complex, okayโbut her parasocial complex that she's created is stronger. You might call it a brandโI think that degrades the insidious nature of it. I call it a parasocial complex. That is stronger than Aidan Kearney's. [Transition to the conversation with greetings] So what we're going to listen to right now isโoh, hello, Francesca Towel. Ohโa lot of folks are coming in. Hello, Rose Water. Hello, Maureen. It's great to see you all. Hello, J.I.5. We're going to listen to this conversation. I'm going to explicate it for you. I think you have enough background to get it nowโbut just be awareโwithout this backgroundโthat would have made no sense whatsoever. I promise you. **Aidan:** Am I on? **Host/Other:** You're on. **Aidan:** So who are you? Who is this? **Chris:** Don't worry about it. It doesn't matter who I am. **Aidan:** Well, it does. You're some fucking kangaroo court motherfucker talking about her. What the fuck do you know about anything? **Chris:** Well, I know exactly what you've been doing. **Aidan:** Soโwell, what the fuck are the sites you're talking about? Noโnoโrecitesโwhat you talk about? Noโreceipts. I've got to shit up. Let's see him. Let's fucking see your receipts. **Lily:** Hang on, Aidanโyou know me. I'm the host. I'm Lily. **Aidan:** Yes, Lily. Hi, Lily. How are you? I'm sorry. I'm just wondering... **Lily:** I know you may not know Chris, but you know me. And so I just wanted to say hello. **Aidan:** Yeah, no, but... Grant: Oh, I also want to let you know this comes with a warning. They use very vulgar language. Some of them are from Commonwealth realms countries. So the language they're using is not as offensive as it would be if you used it in America. Aidan uses some very offensive language. This is for the purposes of analysis and commentary. I do not condone, endorse, promote, or otherwise suggest anyone engage in the use of this language. I personally don't like it. I use the F word from time to time, okay? And maybe like the S wordโbut I do not say some of the terms they're going to useโespecially because one of them is very offensive, okay, to women. And I'm sorry ahead of time that he uses itโbut you should hear Aidan's true colors. **Aidan:** This koala motherfucker is up here making shit up, running his... [Recap of text messages and setup for listening] Grant: So what you have to realize is these texts you're seeing on the screen got released because of this conversation. You're going to hear Joe Flipperhead talking about them. Now in the text messages, you can see Joe reaches out to KarenโJoe Flipperhead. And Karen's going to say she's trying to bounce back, but life is not quite happening. "Had a falling out with Aidan as everyone eventually does. Found out Aidan's been taping our phone conversations and sharing them with people and then telling everyone he doesn't understand how I blew him off for Howie Carr. Some anonymous person sent David and Alan a 33-minute phone call I had with Aidan that was all recorded without my knowledge. That was my final straw. He's done a lot of sneaky stuff with me, but this is above and beyond." And then Joe Flipperhead's like, "Do you want your side out there? If yes, I'm with you. If not, all goodโjust let me know. Have a good weekend." Karen says, "Sure. I told many people my side. This is the last straw. Would never and have never betrayed him. Meanwhile, he has put me in harm's way in a huge way multiple times." Okay, so we're going to listen. "Okay, okay, all right, all rightโno trolling. We shouldโwe should be banning people like that. You have been banned. You have been banned. No trolling. Absolutely no trolling. Now gaslighting and manipulative subversion is the hallmark of a lot of the forces in the orbit of this case. So none of that. We have a lot of Blue Wall of Towel friends here. Don't stand for that. Hello, Christy Mack. Great to see you. Hello. Stay tuned, Wendy. Hello, Bunny. Hello, F.B.I.โmy friend, F.B.I. DOJ corruption survivor. And hello, Meredithโwhich is not Meredith O'Neill. This is Meredith the Towel friend. It's great to see you all. And as I said, if you see anybody trolling in the chatโnow is not the day for it. Towel's health is not well. And I think there are a lot of people who want to undermine the agency of the unheard and the vulnerable in this situation. There are a lot of people who want to gaslight right now because where this is going is explosive. And furthermore, we're about to listen to the conversation. So what you're going to hear in this conversation is it's going to be Aidan Kearney and Joe Flipperheadโwho's named Nickโand a guy named Chris who Aidan Kearney calls a koala. They're going to be talking about what we just talked about. But rememberโthese text messages haven't been released. So Aidan doesn't actually know they're coming. He's being told of this and going on an X Space and reacting in real time. Now I'm going to pause from time to time, and I'll try to flesh out some of the less clear parts. But as we read through the transcript and as you see this all, I think it will be clear to youโclear to youโthe implications. So let's listen."](https://image.24vids.com/tw-1972993638146670728/amplify_video_thumb/1972991333062090752/img/HvGNy_3gMvcvFhAY.jpg)
![That was an interesting interview between myself and The Glarer tonight, as always. "If Aidan Kearney recorded Karen Read, and Kate Peter wants people to support Aidan, then I'm backing Karen." "So, I think Kate Peter, Brian Tully, Jen McCabe, Michael Morrisseyโwhateverโpsychologically profiled Aidan and used Lindsey as an unwitting honeypot. She wasn't an agent. Kate Peter was the state agent. Lindsey was the honeypot who didn't know she was the honeypot, and Aidan fell victim to it because he doesn't think straight when he has a woman in front of him for some reason." FULL TRANSCRIPT: **Will:** You're on. Who is calling? **Grant:** Will, it's Grant. How you doing? **Will:** Grant. Is this Grant Smith Ellis, the Towel? **Grant:** Yes, it's Grant Smith-Ellis. Will, I told you [in the comment section] I'd call in, so I called in. *Will:** What's up, homie? **Grant:** Well, we got some stuff going on, and I don't know how I found myself in the position where I'm defending Karen Read. But here we go. **Will:** Of course you are, because you hate TurtleBoy, bro. Like, it's not rocket science. **Grant:** That's not really what it comes down to. I just don't like people... **Will:** Isn't it though? Come on. **Grant:** I don't like people who take advantage of women and who look at women as less intelligent than men. That's what it's about. **Will:** Okay. That's... that's all that's about, okay? So why... why... why are you exactly Team Karen Read right now? Because, actually, I'm still Team Karen Read, believe it or not. I'm just telling her: if she's accusing people, accuse them and show proof. That's all I'm saying. Is that unfair, Grant? **Grant:** No, I think you're right to ask her for the receipts. But then you have to consider the implications of if she actually shows up and proves that he was doing this to herโnot just recently, but for a year and a half. What the hell was going on, Will? Why was he doing that, and why was she tolerating it? ***Will:** Why do you care? **Grant:*** Because I think that it's completely inappropriate for people to leverage a criminal trial for political purposes. **Will:** Would you care if it was two other people in the movement? Like, anybody. Like, just random. Would you care if it was Erica Walsh and Dina? **Grant:** I would care if it was Kate Peter, Jason Broyles. It doesn't matter. It's the principle. You've seen me call them all out equally. **Will:** I mean, sure, fair enough. But I mean, I stand by my position that it's a personal thing between the two of them, and it's not my fucking business. And I'm not gonna be dragged into it. **Grant:** Yeah, that's fair. And it's a zero-sum game, Will, right? So I really do believe that the filings by Bederow are true: there is an ongoing investigation of Karen and Aidan, and Kate Peter wants Aidan to flip on Karen. Okay, and so it's a zero-sum game. Someone's getting charged. Is it gonna be Karen or Aidan? I think it should be Aidan. **Will:** How do you know someone's gonna get charged? **Grant:** Because look at the filings. Look at what Bederow said. Look at the.... **Will:** What did Bederow say exactly? That... that said that somebody's gonna be charged? What are you talking about, Grant? Come on. **Grant:** Bederow, in the affidavit that I found on Defense Diaries's X within the past two days, said that there is a 2025 active investigation of Karen Read and Aidan Kearney. Thus, if one of them flips... **Will:** You don't know how to say Kearney yet. It's Carney, dude. Let's pronounce... **Grant:** Oh, I've always said Kearney. **Will:** I know, but it's actually pronounced Carney, dude. I just... I just... I just want you to look good when you're doing your live streams, dude, with all your fucking epilepsy-inducing shit that you got going on in your stream. That's fucking scary, dude. Like, I'm not even epileptic, and I go into seizures every time I watch your streams, bro. **Grant:** Hey, I remembered your name, Will, right? I try to remember how to pronounce names that matter. **Will:** I appreciate that, man. Appreciate that. Um, let me ask you this since I got you on the phone. Like, uh, what happened, dude? Why didn't you, uh, attend the deposition, bro? What happened? **Grant:** No, last week was terrible, Will. I was out in the sun and collapsed, and I'm working on actually getting a lawyer for that. So there's some rule about when you're getting counselโthere's a little bit of a delay. **Will:** So are you gonna sue God for Him being hot? **Grant:** I don't know how to respond to that question. **Will:** That's because it's sarcasm, my friend. **Grant:** Oh yeah, autistic people don't always pick up on sarcasm. **Will:** Fair enough, fair enough. **Grant:** Did you see me down at the Moakley courthouse the other day? Miss Leslie's mom called me a towel. **Will:** Wow. Wow. Um, I don't know who Miss Leslie is exactly, but... **Grant:** Oh, Jessica Leslie was the person on the Karen Read federal grand jury who leaked information to a friend, who then sent it to TurtleBoy via DM on X. **Will:** Oh, okay. Oh, okay. All right. Um, yeah. So I mean, are you... are you stoked for this deposition? Are you gonna... like, are you like... are you ready for it, bro? Are you ready to drop some bombs or what? **Grant:** I think I'll have to wait till I talk to my counsel to give you an answer on that, Will. **Will:** That's actually a very, very intelligent response. I agree with you. You should probably... I mean, because, you know, let's... let's just hear real quick. **Grant:** Will, [on the other topic], what it really comes down for me...it really comes down to; if Aidan recorded Karen, and Kate Peter wants people to support Aidan, I'm going to back Karen, alright? **Will:** Okay. So, say that one more time, please. **Grant:** So, if Aidan Kearney recorded Karen Read, and Kate Peter wants people to support Aidan, I'm backing Karen. **Will:** Okay. If Kate... if Kate Peter wants people to support Aidan, you're backing Karen out of the principle that Kate Peter is backing Aidan. So, you're backingโ **Grant:** Out of the principle that I think the criminal charges brought against Aidan were brought by Kate Peter working as a PI for Marty Kraft and Brian Tully, not to actually convict Aidan, but to actually get him to flip on Karen from the jump. That was the whole point. That's why she's trying to get the Free Karen Read movement to turn on Karen now, and I think it's bullshit. **Will:** I mean, Grant, I think that what you're thinking is absolute bullshit, bro. I don't know how you're so smart and you just miss shit. It's crazy to me. You're fucking incredibly intelligent. **Grant:** So, what if I'm right on this, Will, and that the charges against Aidan were brought... the criminal charges... against Aidan weren't a setup by Lindsey; they were a setup by Tully, Kate, and Marty Kraft to flip Aidan on Karen? I'm going to be right about that. **Will:** But there's evidenceโevidence that dictates that Lindsey worked as an agent and was usedโused, by the way, by Tully and Mello to have Aidan's bail revoked. There's evidence to prove this. **Grant:** Yeah, but let me lay it down like this. Do you know what a psychological profile is? **Will:** Uh, I've heard of them. I've heard of them, yes. **Grant:** So, I think Kate, Tully, Jen McCabe, Morrisseyโwhateverโpsychologically profiled Aidan and used Lindsey as an unwitting honeypot. She wasn't an agent. Kate Peter was the state agent. Lindsey was the honeypot who didn't know she was the honeypot, and Aidan fell victim to it because he doesn't think straight when he has a woman in front of him for some reason. **Will:** Grant, you're projecting, my friend. I mean, that. To be fair, though. [what you just said] might be true. But, homie, you're not thinking straight because you are fucking blinded by Lindsey. What is it with your fucking... Do you not see how crazy she is, dude? I feel like she should throw you a piece. Personally, I feel like with all the work that you're doing to support her, I feel like she should throw you at least a handy, bro. Like, come on. **Grant:** Well, let me back it up. Two questions. One, have you ever spoken to the girl for ten minutes? **Will:** No, no, I wouldn't. **Grant:** Two --well, okay-- two, the other thing is, I think we live in an overly sexualized culture. Okay, I really feel... **Will:** Is that just because you're not getting any? **Grant:** No, let me finish. I really like what Erika Kirk has been saying, and I really think that if we're going to focus on the American family and the values that made this country great, then we have to get away from this bullshit that every human interaction is about sex. That's bullshit. That's wrong. It degrades women and it degrades men. **Will:** Doesn't it always boil down to sex, though? Doesn't it always boil down to sex? **Grant:** Maybe for 97% of the population, but you want to make policy, reform the justice system? **Will:** 70%? That's generous. I'd say a good 90%. **Grant:** Yeah, but you want to reform the justice system, write policy, do good things, and do good work? You cannot be focused on sex. That's why priests don't get married. It's about more than sex. **Will:** Yeah, but priests fuck kids. So... **Grant:** Some of them do, but, listen, those people are the most egregious sinners because they take advantage of a sacred trust. **Will:** I agree. I agree. They're the worst. Absolutely, [punish] them all. **Grant:** Yeah, of course. More than [punish] them all, [punish] the people who moved them around. **Will:** Exactly. Grant, I knew I liked you, bro. I knew I did. **Grant:** Well, we're on the same page about a lot of stuff, and I'm telling you, Karen Read was... We may not agree on what happened [to John O'Keefe], but she was treated wrong by those cops as to how they texted about her. They were misogynistic, and she was treated wrong by Aidan. And I back her as to how Aidan treated her. That's the bottom line. **Grant:** Okay, so you support Karen Read because she's at odds with Aidan, basically? **Will:** Because she was treated as less than a human being by Aidan. She was degraded. She was dehumanized. **Grant:** How do you know that? **Will:** I got good sources. **Grant:** Okay. All right. **Will:** Grant, I'm going to take the next caller. Dude, thank you for calling in. Seriously, I really enjoyed our conversation. I always enjoy our conversations, dude. I appreciate you calling in. **Grant:** Anytime. We'll talk soon. **Will:** All right, bud. I'm giving Grant Smith-Ellis the Towel a fucking round of applause."](https://image.24vids.com/tw-1975023200405713261/amplify_video_thumb/1975020677791936512/img/M4GLfkr4tfFT9LD2.jpg)
