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![John Mayer is a master of his craft. He’s also one of the best I’ve come across at using analogy and demonstration to articulate and demystify the creative process. Here’s a 14-clip (~7-minute) masterclass on mastery and creativity: TL;DW 1/ “Whenever I want to write a big song, I can't...That's when I get writer's block: when I try to write a song to fill the entire galaxy. I've never gotten a song that way. But if I write about something the size of a glass of water—a week later, I notice it's got the universe in it. So I'd rather have the universe in a glass of water than try to make a glass of water fit in the universe.” 2/ "What connects with people is you connecting with yourself." 3/ “Writer’s block is when the two people inside of you—the writer and the reader—when the reader doesn’t love the writer. It is not a failure to write. It is a failure to catch the feedback loop of enjoying what you’re seeing and wanting to contribute more to it.” 4/ “Don't shoot ideas down before you have them. 'That won't work' is the worst thing you can ever say. 'That didn't work' is cool, but 'that won't work' is not a way to go through life.” 5/ “I’ve seen the Cool metric change so many times. I'm not telling you don't chase Cool. I'm saying…by the time you reach what you think is cool, Cool is like, 'over here now.’ ‘The princess is in another castle.' You know what I mean? That's a Mario reference.” 6/ "I'm one-half consumer, one-half artist. So I try to put music out that I myself would want to hear as somebody on the other end." 7/ "I'm seeing a lot of motivation about you following your passion, but I'm not seeing any critical thought to what that is or how to be better at that. So, really the product is passion and that's strange to me. Because my product growing up was sitting in a room yelling, 'Mom, I'm practicing,' for hours and hours and hours and hours and hours and hours and hours. 8/ "But then also read up...You know, this stuff doesn't just appear. It comes from somewhere. And as soon as you realize you love something—it's almost like catching up with some great TV show on season 9, and you can go, 'oh my God, that means there's 8 seasons before this." 9/ "Whatever you learn is the tip of the iceberg. Dive underwater and find the rest of the iceberg." 10/ "So listening to Stevie Ray Vaughan brought me back to people like Kenny Burrell and Albert King and Jimi Hendrix and Elmore James. So it became this family tree growing out of my CD player." 11/ "I came up with these guys as like references…It’s like if you're into the NBA and you wear different jerseys and you pretend you're a different player in the driveway—that's what I was doing..." 12/ "Which is a wonderful technique for being yourself. Failing to sound exactly like the person you want to sound like is a wonderful way to sound like yourself." 13/ After watching Cory Wong play guitar, Mayer told him, "You have an anatomy thing working on your right hand. Your hand is shaped in a way—you have long fingers, very sinewy hands—that you're able to play like that. That is an example of someone making the most of their anatomical gifts... And I wish more people could embrace finding what their strengths are anatomically—the way your hand is shaped, the way your mind works, whatever—and play to those strengths." 14/ Mayer picks up an acoustic guitar and demonstrates his songwriting process. “Well, I don’t always do it,” he admitted, “because it requires a stupid bravery all the time.” “You just stare at the corner of the wall," Mayer explains then improvises some vocals, “stare at the corner of the wall / try to get it going on / but I can’t sometimes / you just keep going ’til you get something,” he stops singing. “You gotta keep forcing it, forcing it, forcing it…it doesn’t matter [what comes out of your mouth].” Follow Billy Oppenheimer for more content like this!](https://image.24vids.com/tw-1688293445029302272/amplify_video_thumb/1688292988126937089/img/ru_kWINYMd3dmACB.jpg)
![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)
![Samkelo Zwane x Thabo Cele✍️🏾 Another solution the team can or could have built on. ■ There was control and a lot of forward passes. There is a way to balance the many attacks, our attacking transactional moments and dominance on the ball. ■ When you have the right profiles to improve your ideas, you need patience after you identify them. Be patient and focus on key areas like what needs to be improved, not who needs to be removed. ■ Players grow with the confidence they get from playing. The understanding between players grows with more games they play together. ■ You are not going to get the best out of players who are scared to make mistakes because they don't get a chance to grow from those. ■ The next problem would be using a 10 that does not only bring creativity but also goals we criticize and rely heavily on strikers. ■ You have solved the problem of unsustainable passing patterns or poor space management and lack of control from midfield. You also have players on the bench who provide enough tactical flexibility in case you want to freshen up the midfield. Those players can't all be started. Hence, you need a midfield partnership you will stick with longer and improve. When the team changes its spine as frequently as we did, it interrupts your abilities to identify problem areas after bad results because there is no consistency in the team. When forced changes like suspensions and injuries hit us, you don't know if we lack compactness due to a new CB pairing[injury/suspension] or a new double pivot[random change]. You end up solving the wrong problems and having a team that always looks unsettled even when they have more of the ball. We look shaky in most defensive moments. In this game vs Chippa, we dominated the game and created a lot of chances. We won, and our Nedbank Cup journey gained more momentum. ■ We changed Zwane and put Mshini in the next game, and the quality in midfield was elevated instead of dropped. ■ This gave the technical team 2 of our best possible midfield pairings. We now have working solutions in midfield, but our obsession with having players that offer more running than solutions on the ball meant we are changing this partnership again in the following game and suddenly the quality we've been seeing disappeared. Points started dropping. ■ One of the reasons I want the coach to get the players he wants is to allow us to judge the team on the application of tactics more, not proper selection. As supporters, we won't be happy to see the team drop results when we are not using our squad to the best of its potential. ■ Drop a player for another who will perform functions in midfield better than those you're dropping. We can't repeat similar tactical blunders going into the 2025/26 campaign. ❤️✌🏾](https://image.24vids.com/tw-1927699875732591040/ext_tw_video_thumb/1927699329210261504/pu/img/DAQfFEY2tKkQfw3y.jpg)
![Great to hear such kind words from Saagar Enjeti (who pronounced my name right!). I appreciate the coverage both he and Emily Jashinsky did on the hearing. Thank you! I really hope this was video of an anomalous craft but, at this point in time, I'm still skeptical. The full clip (link in replies) is 8:29) H/T: Heather | Nice People Saagar: "I do want to give some credit to some of the people who are saying that this video is not actually showing a UFO. Now again, I will let you make up your mind for yourself. But this actually comes from a guy who I very much respect, Joe Murgia, UfoJoe. Let's put it up here on the screen. Basically, he looked into it. They talk about the Hellfire missile. What he says (I was quoting one of That UFO Podcast's listeners/viewers), specifically, is that, quote, 'Contact occurred, with the missile passing through. The apparent "deflection" was a guidance system searching for a laser spot again, causing control surfaces to thrash. The three "trailing" objects align better with debris or internal components ignited by electrical damage rather than missile fragments. [IR] artifacts are possible but unlikely.' "Let's go to the next part here. And they say, the overall conclusion is that, 'The evidence is most consistent with a slow-moving or stationary balloon carrying an electrical payload, struck by a Hellfire that failed to detonate. Anomalies arise from fuse mechanics,' etc. "I will let others determine the facts, but that was some of the original, kind of, quote 'debunking' that I saw on it. You can make up your minds for yourself, in terms of what it comes from. It was Rep. Eric Burlison, by the way, who is the person who revealed it. And it's one of those where it was presented as received from an independent...from a whistleblower, according to him. But the circumstances are a bit weird. He said he received it without any metadata or any of that. He says independent review is ongoing. "So I do think it's important to at least present the fact that some analysts and others are saying that it could have been a balloon, which they say about all of them. And so, you know, I want to be totally fair about...that's part of the reason independent review is very important. Part of the reason, throwing it to the experts, et cetera, and actually taking this stuff seriously." (I hope we get more people chiming in and sharing their analysis and opinions. I'm not a video analyst so I rely on people who know more than me. Which is mostly everyone.) Saagar: "But nonetheless, it was great to see George Knapp and some of the others there recounting some of their experiences. I do think some of us are still getting very fed up with the fact that it's still so slow moving. I attended the first UFO hearing, what, two years ago, at this point...with Dave Grusch, right? I was there, I was in the room. I thought it was a big moment. I thought something was coming. And then, you know..." (We all thought we were reaching a breaking point, No pun intended. But that hasn't happened.) Saagar: "The NDAA continues to not have some of the UFO disclosure pieces, even though it's been pushed by members of the overall U.S. Senate. So we rely on Rep. Anna Paulina Luna or other people who are making extraordinary accusations. I'm very willing to believe, but we gotta see more evidence, we got to see more stuff come from the government." Emily: "Interesting disagreement playing out on X right now between UfoJoe and Lue Elizondo who, on NewsNation last night, made a very interesting argument. Which is, that the Hellfire missile UFO is evidence of, quote, 'technology that is making our premier missile system completely useless.' And if you're wondering why, in relation to what Saagar just described about the NDAA, why are members of Congress - and even, remember Secretary Marco Rubio as a senator?" Saagar: "Yeah, he was an OG. That's right." Emily: "Why are, quote, 'mainstream' members of Congress interested in getting answers to questions like these? Well, it's because they're seeing videos and hearing analysis from people like Lue, who worked at the Pentagon. You can debate Elizondo, whatever. But saying this is evidence of technology that's making our premier missile system completely useless. Now, UfoJoe disagrees." (I disagree because, to me, it appears that the missile disabled this object. So it accomplished its mission. Others, vehemently disagree. Here's one: ProPixel Video Analysis and Research. And this guy... Then you have MarikvR (anomalous) and Mick West (not anomalous), with opposing views. ~ Emily: "[UfoJoe] says, 'Early on, I agreed. Right now, I do not. I retain the right to change from my mind. Did Lue present any analysis or mention anybody who has done analysis besides the stuff shared on here by us?' But that gets to what Saagar was just saying, which is that, years into this third task force meeting, the bombshells are highly disputed. You know, it's not like this bombshell dropped yesterday, and everybody was like when that New York Times story originally dropped back in, what, 2017?" Saagar: "Oh, yeah, 2017. That's why I'm here, literally. That's the only reason, that's what got me in." Emily: "But we haven't had another moment like that, really." Saagar: "It's been a while. Dave Grusch was very important, I think, as well." Emily: "That's true, that's true." Saagar: "I just gotta see more. And, you know, credit to Jeremy Kenyon Lockyer Corbell and George Knapp, and all these guys. They're the ones who are at the vanguard. They're pushing the conversation. They're singularly..." Emily: "Responsibly." Saagar: "They're getting it, responsibly vetted. And that's why I include all of the information. You can make up your mind for yourself. I think more scrutiny, pressure on these, you know, the Democratic, Republican establishment to get the stuff out there is just so vitally important, if you want to get to the truth. "Because at this point, you know, you have Congresswomen and others, people making major accusations. Or allegations. Which I'm totally willing to believe, but we have to see more evidence in the future. That's the number one important thing. So, yeah, call your congressman or senator. Get them to the make sure the NDAA is gonna have that. What's it to them, right? It's like, so low on their priority list that if even twenty people call about it, maybe they'll do something? You never know. You truly never know you."](https://image.24vids.com/tw-1965854925956723187/amplify_video_thumb/1965841671599566853/img/j0dMAaZVCExiKxwN.jpg)
