Inside the $41B AI Cloud Challenging Big Tech | CoreWeave SVP

The future of AI training is shaped by one constraint: keeping GPUs fed. In this episode, Lukas Biewald talks with CoreWeave SVP Corey Sanders about why general-purpose clouds start to break down under large-scale AI workloads. According to Corey, the industry is shifting toward a "Neo Cloud" model to handle the unique demands of modern models. They dive into the hardware and software stack required to maximize GPU utilization and achieve high goodput. Corey’s conclusion is clear: AI demands specialization. Connect with us here: Corey Sanders: https://www.linkedin.com/in/corey-sanders-842b72/ CoreWeave: https://www.linkedin.com/company/coreweave/ Lukas Biewald: https://www.linkedin.com/in/lbiewald/ Weights & Biases: https://www.linkedin.com/company/wandb/ (00:00) Trailer (00:57) Introduction (02:51) The Evolution of AI Workloads (06:22) Core Weave's Technological Innovations (13:58) Customer Engagement and Future Prospects (28:49) Comparing Cloud Approaches (33:50) Balancing Executive Roles and Hands-On Projects (46:44) Product Development and Customer Feedback

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I don't care if the APIs are consistent and commoditized. The level of quality, performance and capability and experience that we deliver today will not win workloads in two years. For anyone who's deployed on a public cloud, especially with GPUs, and you suddenly have a personal capacity, like you're always sweating. And so what I like to think about for us is how do we go make all of that complexity then go away? I think CoreWeave already got that. CoreWeave is the best place to run training AI workloads. And it's why people use us. It's focused on basically bringing as much possible data and throughput into the GPU as you can. And that's a very unique requirement that AI workloads have because GPU is the most expensive asset across all of those componentry.

• 0:45Speaker 00

  And so that allows us to make these assumptions that are simplifying for us and daunting for the public cloud, such that even the public clouds will come in and talk to us about enabling us for some of their workloads or customers.

• 0:57Lukas Biewald?

  You're listening to Gradient Dissent, a show about making machine learning work in the real world. And I'm your host, Lukas Biewald. All right. Today I'm talking with Corey Sanders, who is currently the SVP of Product at CoreWeave. And prior to that, a longtime executive at Azure, where he worked on compute projects and a whole bunch of other things. It might seem like maybe this is CoreWeave sponsored somehow or something, but this is actually a conversation that I would be excited to have regardless of where I was working. But you should be aware that Corey is one of my colleagues now that Weights and Biases is bought by CoreWeave. But we try to stay as subjective as possible and keep it interesting. I hope you enjoy it.

• 1:39Lukas Biewald?

  All right, Corey, do you want to sing us in? Should we do this?

• 1:42Speaker 00

  Can I be on your podcast? This is a little beat that I created, begging Lucas to allow me to join this session.

• 1:53Lukas Biewald?

  Yeah, and I guess we, you know, we'll put a lot of disclaimers in here, but we're now coworkers. So this certainly is not an unbiased interview. And I guess I haven't really alerted.

• 2:05Speaker 00

  Biases, Lucas.

• 2:06Lukas Biewald?

  We're all about biases here. And I haven't mentioned this in the past, but you know, since Waits and Biceps but by CoreWeave, we actually run all of these podcasts through CoreWeave compliance. And I'm a little disappointed that we've never triggered anything, including, you know, the episode with Martin Shkreli, who's like a little controversial. And you know, we try, I try to make this interesting, but we've not ever had compliance complain about anything. So maybe this could, this could be our first time.

• 2:33Speaker 00

  Let's go for it. Let's go for the win here, Lucas.

• 2:35Lukas Biewald?

  There's gonna be like big, like quiet blocks. We'll just, we'll just chop it out.

• 2:39Speaker 00

  Or like really, really jumpy chops.

• 2:42Lukas Biewald?

  Yeah, yeah. Look out for this.

• 2:46Speaker 00

  I won't answer that stupid question.

• 2:51Lukas Biewald?

  It's also, it's funny, like researching you. So here's what I noticed, you know, as I, as I try to like, you know, Google you and find out about your past, right? Like, you're kind of doing this amazing series of videos for Azure, where you're taking like, can I say they're like boring topics? Like even to be like, technical guy. I'm just like, man, this is like, I'm a kind of.

• 3:13Speaker 00

  One of my best videos was on backup.

• 3:17Lukas Biewald?

  And so I just back up and be like, low cost, like backup alternatives for like this situation, you know? And I'm like, man, I'm an Azure customer and I'm not really that interested in this. But then you like sell it so hard, like you make it like actually like interesting. Like it's amazing. Like, I'm like, why am I like watching this? And then something happened, like I feel like maybe you got a promotion or something. And then you're like flying around the world, going from like terrible production value. Like it looks like you just got your camera out to like unbelievable production value. And also like in like fancy places. So like, did the marketing team like notice? Like we got like a real talent here.

• 3:56Speaker 00

  It was probably more that they were trying to stop me from doing my show. And so they said, we would be willing to do this other thing. If you promise, stop making that POS show, please. It's embarrassing the company. But no, yeah, those, those, those trips were amazing, actually, for Cloud Cultures. That was fun, man. That's, uh, that's great.

• 4:19Lukas Biewald?

  And you're like, dude, all this wild stuff. I don't know. Like, how did you even set this up?

• 4:23Speaker 00

  You know, it was, um, we were having a conversation about a data center expansion that we were having, um, I think it was in London, actually. And we were, we were sort of facing this first wave of a lot of public sentiment of like, we don't want these Western companies to be building data centers right in our backyard for, without a lot of value to us. And, you know, I think the realization was, gosh, the services that are running in that are from that guy down the street and that big business down, down the road. And like, they're all local businesses. And so this was sort of the concept of how do we now translate that like local culture into sort of a, an interesting storyline, right?

• 5:05Speaker 00

  We could basically, the culture feeds, the technology needs feeds, then the sort of the demand. And, you know, some of the interesting things that we did with the podcast that I think, excuse me, the, the series that I think were very foreign for, for sort of series to that date at, at Microsoft was like, we refused to say Microsoft or Microsoft products in the, in the series. Like, it was just all about focusing on those end customers and what they were doing. Uh, and so it was, it made it a lot of fun, man, because it was just like talking about, talking with people about their stuff, which I guess is kind of what you do in this show, I guess.

• 5:35Lukas Biewald?

  The good news is you don't need to budget for it. Like, I think it's like Cory walking around with a phone.

• 5:39Speaker 00

  No, that's a hundred percent. There was zero budget. It was, I think it was my, I had my cell phone that I was recording it on. Uh, so, you know, it's, the ROI was through the roof.

• 5:48Lukas Biewald?

  And no studio, you're like in the cafeteria, like, did anyone complain? Why are you filming? Like, oh, we're trying to eat.

• 5:55Speaker 00

  And I was bringing like guests in and we were just sitting in the cafeteria. And, uh, no, man, it was just, why, why would we not?

• 6:01Lukas Biewald?

  Pretty cool, pretty cool.

• 6:04Speaker 00

  It was, we really, we upgraded when we brought, when we brought microphones in. That was like the big thing. It was just like, wow, we have microphones now.

• 6:14Speaker 00

  Yeah, versus again, the production value of like 16 cameras everywhere I went just tracking me. So that was fun.

• 6:22Lukas Biewald?

  All right. So you're like at Microsoft, like working at Azure most of the time for like 20 years. And then you came to to Corey. I guess like one question I wanted to ask you, this is like really maybe also a personal interest, but like, you know, like, what, what, what did you, what did you notice? Like, it must have been a, was it like a dry experience to go from like 20 years of this, like, sort of like, you know, one of the biggest companies in the world to like a startup? Like, I, I always kind of like worry about execs when I hired them and they maybe have like, the last five years, they were like a big company, like, how are they going to feel? Like, are they going to feel like it's total chaos? Or?

• 6:56Speaker 00

  Well, you know, it's funny, because it, it, you know, when you're, when you're at 20 years at any company, you, you get to experience a lot of different parts of the company, a lot of different sort of, you know, different groups of people and so on and so forth. And the early days, because at Microsoft, they had the opportunity to sort of get to work on the very early days of infrastructure as a service. So we wrote, wrote the first spec, sort of work through, you know, this was sort of the beginnings of containers, Kubernetes partnership, and, you know, I was sort of a part of the first Red Hat partnership with Microsoft. And those early days, actually, Corey reminds me a lot of those early days in IS, right? Where it's basically a, a little bit to your point, it's sort of, there's a

• 7:39Speaker 00

  sort of beauty to the haphazard, like, there's sort of, you know what I mean? Like, there's sort of, like, you can, if you take a far enough step back, it, it makes perfect sense. But if you're real close, it looks like insanity. And, and, you know, and I think that like, that can exist inside big companies as well as in sort of startups. Obviously, I think it would be in a pretty much all startups. And so, you know, and I think the fun part of the job is to sort of find that beauty, find that sort of, that harmony in everything that the company is doing. And the company is doing amazing, amazing sort of groundbreaking work in, in almost every facet that it's involved in. And so it's, it's an exciting and thrilling place to be, but it is fast paced, that's for sure.

• 8:23Lukas Biewald?

  So, okay, but here's like, here's really, here's the question I want to ask you. I really just have like one core question that, that I, I'm really curious about. Like, what, what do you think, like, kind of gives CoreWeave the right to exist, right? So like, there's, there's like a couple of years, I mean, there's like many years of like these clouds taking off. And it's sort of chaos, I remember back in the aughts, and now there's like, you know, kind of like three clouds, like really. And then you see these new neo-clouds. And, and it's like, you know, like, what's going on that there's like, um, new options here?

• 8:53Speaker 00

  Yeah, I think there's a few things at play.

• 8:58Speaker 00

  You know, I think, I think the first thing is this AI revolution, sort of this, uh, this pivot towards massive amounts of new innovation, uh, new ideation surrounding AI, has created this sort of new tier of business critical workload.

• 9:19Speaker 00

  And, you know, I compare it to sort of the analytics wave of maybe 10 years ago, right? Where this sort of realization with analytics that it could drive and fundamentally change your business.

• 9:31Speaker 00

  And we're seeing that again now with AI. And, and the reason why that's important is because it sets the framework for what I think customer, customer need for best in, best in class solutions, right? When something is business critical and has a relatively high cost associated with it, that is when customers are going to be willing to look for the very best there is. And be willing to separate from, um, existing sort of contracts, existing, uh, sort of environments that they're comfortable with, to be able to get the best in class. And we saw it with analytics, I would argue, with companies like Snowflake, um, Databricks as an example, where these companies ended up existing outside of this sort of, um, you know,

• 10:14Speaker 00

  jack-of-all-trades type public cloud environment, um, because they enabled a best, a best-in-class offering versus just a best-in-suite, uh, type solution. And I think now the AI revolution is seeing that same demand and that same opportunity for a company like CoreWeave to deliver best-in-class services and capabilities for this business critical and very high-cost requirement. And I'm excited to get to be a part of that, about, about the momentum.

• 10:44Lukas Biewald?

  Although I guess, I guess one difference maybe, I mean, it's an interesting analogy with like Snowflake and Databricks.

• 10:49Speaker 00

  You could just say you agree with me, Lucas. That's fine.

• 10:52Lukas Biewald?

  Oh, yeah, yeah, yeah. It is very exciting to be a part of. No.

• 10:57Speaker 00

  You know, forget it. Go on with your question.

• 10:59Lukas Biewald?

  All right. No, no. I mean, I think it's an interesting analogy.

• 11:02Speaker 00

  This is gotcha journalism, it is.

• 11:03Lukas Biewald?

  Yeah, yeah. Hard hitting, hard hitting. So, Snowflake and Databricks, they run on top of the clouds and they like actually pay money to the clouds. I guess like one difference here that's like, you know, like maybe super surprising is that like Microsoft and Google actually customers of Correiv, right? Like, how does, how does that happen?

• 11:25Speaker 00

  Yeah, it's interesting. Although I will say Microsoft, Google, I suspect many of them use components from Snowflake and Databricks as well. But yeah, I mean, I think, yeah, they're both customers and in some ways partners in some situations and circumstances. I think part of that is also, you know, there are elements of what makes an AI cloud special or a Neo cloud special in, in sort of decisions and designs and implementations that make them not fungible, right? And my two favorite examples, you know, one of the, one of the things that I think from a software side that Correiv is super unique on is our, is our object storage, our sort of implementation of object storage, which again, for like

• 12:10Speaker 00

  backup, for many people that like snooze fest, like you're talking about object storage. And so that coupled with a, with a caching solution that we call our lot of cache, because you need a lot of storage to deliver AI workloads. Look, it's focused on basically bringing as much possible data and throughput into the GPU as you can, right? And that's a very unique requirement that AI workloads and, you know, particularly training workloads, but certainly interesting as well, have to sort of be able to basically feed the GPU so that the GPU is not idle, because GPU is the most expensive asset across all of those, across all of the componentry. And so, you know, would I say, gosh, you should use that to run your e-commerce?

• 12:53Speaker 00

  Website? No, probably not. Like, I don't think our lot of cash with our KIA storage would be the right thing to run an e-commerce website. But we don't need to design for an e-commerce website, right? We can design for what we're built for, which is AI. And so that allows us to make these assumptions that are simplifying for us and daunting for the public clouds. Because how do they make those types of assumptions based on workload? It goes all the way to the physical side where you think of something like liquid cooling. Liquid cooling is a hard thing for fungible data centers to take advantage of. You've got to plan ahead. You've got to deliver all the components. You've got to build the right piping, etc.

• 13:30Speaker 00

  And so for us, we can make those assumptions because we know that we're going to need that amount of liquid cooled capacity. You know, I think the public clouds have a harder time about setting that space aside. So again, making that simplifying assumption that we're delivering AI exclusively allows us to build better services, solutions and experiences, such that even the public clouds will come in and talk to us about enabling us for some of their workloads or customers.

• 13:58Lukas Biewald?

  So like, okay, liquid cooling, obviously badass. I mean, I think we're about the same age, clearly, based on the fact that I understand your obscure musical references. And like, you know, I think I always wanted like a liquid cooled desktop in my youth, but like,

• 14:15Speaker 00

  Green, like green liquid, like that's, you can see it going through it, right? It doesn't need to actually cool things. You just need to see the liquid going through it. Anyway, go on.

• 14:24Lukas Biewald?

  I just want to like, I just want to trade off like reliability, you know, for like slightly faster, like absolutely, I want that.

• 14:31Speaker 00

  And that trade off always wins.

• 14:32Lukas Biewald?

  Yeah, yeah.

• 14:35Lukas Biewald?

  So like, if I'm a, if I'm a, if I'm a customer of like a liquid cooled data center, if I'm actually like using it, how does that like manifest for me? Like, I mean, you know, like I can like actually buy these GPUs and lots of different data centers. So why would I care if it's liquid cooled?

• 14:50Speaker 00

  Well, so, so some of the GPUs require liquid cooling because of basically the nature. And so some of the latest, greatest, largest actually require liquid cooling. And so you can't get them unless you have a liquid cooling solution, right? So that's at least one. And then, you know, for others, I think, look, transparently, I think the verdict's still out on sort of the full extent of the value. It definitely reduce improves efficiency, right? So it improves on our side, the ability to sort of serve those with sort of, you know, lower HVAC costs, sort of lower, lower air conditioning because we're able to do the liquid cooling to enable it. And, you know, the hope is that that would translate into

• 15:30Speaker 00

  cost savings over time. And so I do think there probably the stronger case is the GPUs that are so powerful, so strong that they actually are going to require it. And we're just able to then deliver those much more effectively and efficiently and at larger scale than others out there.

• 15:49Lukas Biewald?

  That makes sense. And what about like the, what about like storage? It's another one where, you know, I've used like object stores, you know, like my whole career. It's like a super, you know, it's simple API. I haven't really like, you know, thought deeply about different ways that it, it might work. But like, I mean, I guess like, are you saying like the, the core of object store is like kind of faster to, to put, to like, serve the files into a computer? Because presumably if I'm an e-commerce company, I kind of also want, I don't know, like fast downloads for my customers. It's not like totally different. Like what?

• 16:19Speaker 00

  Yeah, it's fair. I think, I think, so it, it, a key component of it is around sort of the caching tier and how the caching tier is designed across the GPU framework. So basically, it, it takes assumptions around sort of a multi GPU deployment and sort of delivers and serves the cache from, from the GPU or from surrounding GPUs, right? And so it enables you to optimize sort of a scaled GPU deployment and leverage the cache effectively that way. And, you know, the e-commerce example, probably the, the reason why I like to use it is that,

• 16:53Speaker 00

  you know, with any sort of cache and cache architecture, you've got to make assumptions around your read to write percentages, right? And, and sometimes if your caches make the wrong assumptions around, you expect to have this many reads and this many writes, you can actually hinder performance with a cache, right? Because if you end up having more writes than reads. And so for a lot of these workloads, right, outside of a check Pointing process, which ends up probably requiring less of a backend storage write than just a local sharing write. You know, these types of training workloads don't have as much writeout. Right. And so, yeah, you're right. Some components of an e-commerce site may be sort of exposing the content.

• 17:34Speaker 00

  You know, I'm not maybe an expert on designing an e-commerce site, but certainly all of like the management of the, you know, of the basket, the management of actually making an order, right? These sorts of things take consistent writes to be, to be, to be executed. And I think this type of cache is not as optimized for that type of frequent sort of needing consistency and sort of high consistency, if that makes sense.

• 18:02Lukas Biewald?

  Totally, totally. Are there like other things that you like sort of expect to change when you like kind of look forward at, at like workloads that are coming or like people like, you know, wanted to like run agents all over the place? Like, you know, can inference is like, you know, constantly changing? Like, I don't know, like, what are you, I don't know, what are, are there other places where you sort of expect to like have?

• 18:23Speaker 00

  Yeah.

• 18:24Lukas Biewald?

  You know, kind of purpose built stuff?

• 18:25Speaker 00

  Yeah.

• 18:26Lukas Biewald?

  Or make different decisions?

• 18:27Speaker 00

  Yeah, yeah. Well, I mean, one of the areas that I think

• 18:31Speaker 00

  is super interesting with inferencing that, you know, is also potentially questionable. Is it a point in time or is it sort of a forever thing? The, the amount of time that sort of an overall inferencing call takes, a huge percentage of it is inside the GPU, right? Like, like to do the actual inferencing call, the sort of response, et cetera, whether it be agent, whether it be, you know, a chatbot, et cetera, is sent inside the GPU. And it dramatically reduces the percentage of overall sort of time to serve that sits on the network. Right? Which creates some interesting opportunities around network flexibility.

• 19:11Speaker 00

  Right. And so, you know, one of the things that I that I like to think about a lot and sort of as we think about designing that I also think puts us in a different position from from others is that flexibility in network positioning and network deployment gives a lot of opportunity for changes in the way we think about workload requirements. Right. Whether that be availability, right, suddenly going from five different data centers to make your calls and basically being able to use whichever one may be available or not. You can suddenly dramatically improve your availability of a giving serving app. You know, I would argue, um, uh, you know, the, um, ability to react to bursts of capacity needs suddenly become a lot easier.

• 19:54Speaker 00

  Right. For anyone who's deployed on a public cloud, especially with GPUs, and you suddenly have a burst of capacity, like you're always sweating that you're going to go ask for capacity and it's not going to be there in that location, in that region, in that zone. Right. Um, suddenly with sort of, um, uh, with these types of workloads, I think you have a lot more flexibility around sort of your regional deployment. And so what I like to think about for us is how do we go make all of that complexity then go away? Like, how do we go say, you know, you, you, you may want to run a given model off the shelf, or you may want to run a deeply customized model with a bunch of custom code that you're going to go write to set it up. Regardless, you shouldn't have to care about how you're going to get your capacity. Right. You should be able to say in loose terms, I kind of wanted here, I kind of wanted there.

• 20:40Speaker 00

  But you take, you sort of send that to the platform and the platform will sort of take care of it for you. I feel like this is a pretty novel approach because these workloads are different from an e-commerce site where the network time and your sort of time to the actual VM is meaningful because so much of the time is spent in the GPU, suddenly that becomes less meaningful. Now, does this change over time? I don't know. Right. This is one of the fun things about working in this business is you got to be fast and you got to listen. Sometimes more than talk, which I'm not. Not doing well on this podcast, to be clear.

• 21:11Lukas Biewald?

  Well, that's your role. I'm listening and you're talking.

• 21:16Speaker 00

  About like, but here's, let me like, let me, can we roll, let me just rewind just for a minute because you started out being like, hey, you do these things. You talk about these really boring things and you make them interesting. And now on this podcast so far, I've talked about object storage. I've talked about liquid cooling.

• 21:30Lukas Biewald?

  Yeah.

• 21:30Speaker 00

  I've talked about like global capacity availability. Like these are super boring topics. Is there anything?

• 21:38Lukas Biewald?

  But you're making them good. Really? I feel like you're selling these topics. I mean, I am actually, I think more interested in these topics than the Tuesdays with, with Corey topics.

• 21:48Speaker 00

  Well, I mean.

• 21:49Lukas Biewald?

  But I don't know, I'm enjoying it.

• 21:51Speaker 00

  There's no reason to be mean to your host, but to your guest, excuse me, but that's fine.

• 21:56Lukas Biewald?

  Really? I actually thought it was pretty interesting. I mean, do you like, I guess the thing in the back of my head though, like as you're saying this is like, you know, you were at Microsoft for a long time. I mean, I've, I've worked with Microsoft for a long time and had folks on, on, you know, the podcast that were like super smart about like infrastructure and AI and stuff. And, and I think that, you know, clearly they have, must have liquid cooling if they're offering the same, you know, GPUs. They must be kind of doing the same stuff and thinking along the same stuff. Like, do you think there's like a, like a durable advantage here? Like is the idea that Corey kind of gets to a similar scale and just sort of like continues to compete and now there's like a fourth cloud? Or is there like something like kind of fundamentally different that that's happening in your mind?

• 22:36Speaker 00

  Yeah. I mean, I think, you know, those points about fungibility, fungibility is the lifeblood of a public cloud, right? Like it's sort of the way in which the business model works. It's the way in which the apps work, right? It's sort of like, you know, we are going to build services that, that meet the needs of a massive scale of customers, right? For, for, for tons and tons of different workloads, right? And so like the liquid cooling example, yes, there is liquid cooling in certainly in the, in the public clouds. But it oftentimes is like a, an add-on like to a given location, which then means it can't work in every location, right? It's not sort of easy to add it. It's also not easy to scale in large quantities, right? And so.

• 23:18Speaker 00

  That maybe is a very precise example, but I feel it's very illustrative, as they say, of the problem, right? And so it's very, very hard for these sorts of special... And then I'd say like the lot of cash, like certainly that type of technology could be built in the public clouds. And as you sort of go down and look at our scheduler and our... Another good example is our SLRMM integration on CKS, the sort of some capabilities that we've got. Yes, these could definitely be built in other environments. But just like in sort of other innovation and revolution, like I would argue the Databricks and stuff like work could also be built in those public clouds. And so the opportunity to be laser-focused

• 24:02Speaker 00

  on delivering to a specific set of scenarios, shedding any sort of concern about, does it work in these cases? Will it break in those cases? Like, I don't care, right? Like, those are not cases I'm going to care about. Like, does it work? And does it deliver unique value in this usage case? And as that remains true, I think we have the opportunity to continue to innovate and continue to differentiate. And then, just like any technology advance, it's all about continuing to stay ahead, right? And so we can't slow down, we won't slow down. And I think we're gonna have to see sort of where the rest of the market moves in innovation. But I think it is, I do believe it's a sustainable advantage to

• 24:44Speaker 00

  have that focus. And we just have to continue to take advantage of it.

• 24:52Lukas Biewald?

  Okay, this is gonna sound like a real softball, but it's a really genuine question.

• 24:56Speaker 00

  Good man, your questions have been hard so far.

• 24:57Lukas Biewald?

  We're both coming from that side. I mean, one thing that is like, actually pretty remarkable about Corv is like, you know, how much like real kind of customer love there is for what I think, you know, before I joined, I really thought was like a commodity product. I think like probably most people would, you know, that aren't like deep in this and trying to do Big Data Center feel like... This is a pretty commodity product, but it does seem like people are getting wildly different, like, you know, kind of good put and T flops out of the same, you know, machines because of like, you know, kind of technical details on how they're set up. Or maybe, you know, I sort of suspect that it's like actually the way that Corey was engaging with customers feels friendlier than the other clouds, having been on the

• 25:41Lukas Biewald?

  other side of it for a long time. I do think there's a lot of room for, you know, customer service to improve, you know, for especially the technical customer service. But I don't know. What's kind of your take? Like, do you notice a difference in the way like Azure versus CoreWeave like engages with customers from the inside? Is that, does that feel right?

• 26:01Speaker 00

  Absolutely. I mean, look, absolutely. Look, I think the, well, there's two things maybe to say. I feel that, you know, the product, the product is real. Like, I think, you know, I think in sort of the examples that I give, there's sort of numerous additional examples. One that, you know, I didn't actually spend time on, but is a key one for customer love is our observability, right? Like, the sort of awareness and depth that we have into the infrastructure on what's happening and why it's happening. And then the automated integration of that into mission control, into sort of the, you know, operations that the end customer is running, simplify the ability to run these jobs. And this is part of what like the magic of something like Sunk or it's the Slurm on CKS. With the observability integration, customers are able to sort of manage their workloads, manage their training

• 26:45Speaker 00

  jobs in a much simpler way. And so that to me, like, I think the product line is a big part of the love, right? From the, again, object storage to the CKS orchestration to the Slurm on top of CKS to the observability. But I do also believe to your point that that that customer engagement, and, you know, we've got this really sort of amazing customer success, customer enablement team that is so focused on helping customers figure it out. You know, I think we sort of start with the assumption that this stuff is complex, right? It's hard to sort of get things working, especially with the fast pace of the infrastructure.

• 27:28Speaker 00

  And you know, for the many of our customers, getting down to the infrastructure and using it effectively is critical to success. And so enabling, working closely with them, you know, even sort of the deep engagement of our CTO with sort of the day-to-day activities of our customers is stunning, right? He is out, he is on the channel. I think he is like double the amount of Slack messages of anyone else in the company because he's just out there, working with customers and helping them solve their problems and making sure that they're using the platform in, you know, the best way possible. That's pretty unique. That's a pretty unique outcome. You know, I would argue that the big clouds probably have that, but with, you know, their top nine customers, right? Or whatever it may

• 28:10Speaker 00

  be. And so I think just from an overall percentage of our customer base, we're able to deliver upon that with, with a much greater percentage. And so I think that that, that delivers upon, I think, a lot of, a lot of love for the platform. And, you know, that, that alone wouldn't work, but that coupled with all the product capabilities that we talked about, you know, that customer support to get people to use those products in the most effective and efficient ways. That's really where that connecting glue becomes a lot of love.

• 28:42Lukas Biewald?

  Was it the same, like in the other, you know, kind of new things that you worked on at Azure where you're kind of like making a small number of customers successful at like big scale and then kind of disseminating them to lots of people? Because like, I think what I'm used to from like, you know, kind of my Silicon Valley SaaS background, it's like typically the, the journey is more like, you know, we make like a lot of little customers happy and we kind of gradually like move

• 29:10Speaker 00

  That's right.

• 29:11Lukas Biewald?

  up market. I think like, you know, like the core we've approached, I think most of the NeoCloud approach has been actually totally the opposite of that and sort of different than the model I'm used to.

• 29:20Speaker 00

  Yeah, that's right. That's right. I mean, again, I would say the very early days of like infrastructure to the service were closer to that. It was a small amount of customers and sort of make them happy. But like, I think today, if you look at all the sort of clouds, it's very much, I think, exactly sort of the way you were talking about it, which is, you've got a scale of customers and you're building things to meet the needs across the scale of customers versus, you know, I mean, I would argue that CoreWeave has their ideation for new products by sitting with a customer, customer saying, well, I'm stuck. I mean, in some ways, Lada and Chaos came out of this, right? Some big customers were like, I'm stuck in sort of really feeding my GPUs with the fullest amount of data possible.

• 30:04Speaker 00

  And sort of the design and implementation came out of that and was delivered to that customer first as sort of like a let's work together on it and then became a product, right? And became something now that that sort of we now can enable for everybody and is, you know, growing, growing like crazy. And so, yeah, I think that approach is very different and pretty unique. And a lot of that is also the shape of the of the AI market, right? The shape of the AI market is you've got sort of the big, you know, the big elephants and then a whole lot of, what's a smaller animal? Like little, little birds?

• 30:36Lukas Biewald?

  So I guess, do you think like it's a natural life cycle here, the stuff that it like all kind of becomes a commodity, then you like innovate on another dimension? Or do you think there's something like kind of fundamental about like these AI workloads and they kind of stay non-fungible?

• 30:52Speaker 00

  Yeah, I mean,

• 30:56Speaker 00

  I sort of, look, I believe that while there's value that's being added to a service in in operations, in quality and performance and experience.

• 31:12Speaker 00

  Then something will never be truly commodity, right? And you know, I've made this argument about the public cloud for years, right? This like forever, the public cloud, you know, infrastructure service was going to be this commodity thing that anyone could go move to anywhere. And you know, I made the argument of like, look, I don't care if the APIs are consistent and commoditized. I don't care if we all have the same APIs and we all. I was like, but the, the service we offer, the quality of the experience, right? The quality of sort of the, the uptime, right? The performance that you get like these continue to differentiate forever and continue to make something not commodity. And so I would argue of a sort of a very similar position here about the AI world.

• 31:53Speaker 00

  Like, you know, so many of the things I talked about were about enabling TCO, enabling better throughput, enabling better ability to serve on workloads, enabling better usage of your GPUs, right? Enabling better good put like these things in the set of services and capabilities that we talked about, they're all delivering upon that end goal for a customer. And that end goal is quite valuable. That end goal is quite valuable. And so, no, I think that will always, there will always be value. Will the bar continue to go up? Yes. Right. Which is an amazing part of how these types of markets work, right? Like the bar will go up, the level of quality, performance and capability and experience that we deliver today will not win workloads in two years, right?

• 32:38Speaker 00

  Like we, we better be moving the bar up, but there will always be differentiation, especially when the cost is so high and the business value is so high.

• 32:49Lukas Biewald?

  So you would actually argue that Azure and GCP and AWS are, are not equivalent? That they're, they're, I mean, I realize it is like hard to move a workload.

• 33:02Speaker 00

  I definitely would argue that they're not equivalent. I would, I mean, I would, I would ask you.

• 33:05Lukas Biewald?

  What would be the, I mean, it's funny, I. I feel like I'm always like talking to them now, maybe I could say this, you know, I kind of pretend like, oh yeah, you're like special. But I think as a startup guy, you're kind of like, okay, who's going to give you the most credits? I'll use that one first and oh man, now I'm stuck on the thing that I tried first. I think that's the startup experience of these things. Like I sort of the sense that like Azure is like a little more like enterprise. I have an experience that GCP is like a little harder to get their attention, their support team. And I feel like Amazon is like kind of the default. But I don't know, what do you think? Like, what would be the internally in Azure, what do you say is like the, the advantage?

• 33:46Speaker 00

  Yeah, I mean, look, I think, um, uh, I, I, I mean, obviously I loved my time at Microsoft and I, so, so this is a very biased perspective. But I, I thought that Azure was, um, to your point, I think the strongest in delivering upon sort of the end to end enterprise requirements. I mean, one of the things that I felt like made Microsoft and then Azure as a component to it. And by the way, we saw this from the very beginning, like this was never a, never a surprise, but I was glad the way it played out. Was it the concept of the Microsoft cloud? Like the Microsoft cloud was, was and is super unique, right? The ability to kind of come in and say, look, I'm, um, I am an office user.

• 34:27Speaker 00

  I use components of dynamics for my business practices. And so like, if that's the case, like, of course I'm going to use Azure that is integrated deeply into all of those components and bring it all together. And so, you know, I felt, I, I felt like that, um, full value. Then you layer on sort of the security layer that now you've got a consistent security story that spans all the work that's happening at your company. You've got a consistent sort of billing and quota story that spans all the work that's happening. So like, to me, that enterprise story, but even a step up on like the Microsoft cloud story. I thought always resonated really well and, and customers who were in those groups really sort of appreciated the fact that things hunted together

• 35:11Speaker 00

  and felt like they were all kind of unified together. And I think, I think the, the, those services, and then they look, there's a bunch of like one. Off things that I'd say like I felt like for the longest time, you know, Azure had the strongest SAP offering. And so that was a big value add for a bunch of customers who want to deploy SAP. And, you know, I think, I think the, you know, Cosmos DB is one of the best sort of global databases in the world. And so like, there's a bunch of things that like I would go into if you wanted me to about specific services capabilities that I think are deeply differentiated.

• 35:43Lukas Biewald?

  So is there like a, are you trying to create like a core weave story like that?

• 35:49Speaker 00

  So where basically we have differentiated services and capabilities. Yeah, I mean, look, I think Corey's already got that, right? I think Corey's got that on the training front. Like, I think that when you sort of look at the, look at sort of the platform that we've got today with all the things we've already talked about, the observability, the song, the etc, etc. Chaos, Lada, like CoreWeave is, I, I, I, I believe the best place to run training AI workloads. Period in the market. And I think that, that sort of class of workload with all those capabilities and features puts it, stands it outside the sort of other, the other clouds, whether they're Neo clouds or public clouds. And it's why people use us at scale, right?

• 36:32Speaker 00

  Is because of that, that sort of functionality and that capability. And I, and I look forward to, I think there's a bunch of other places that were on the path to being differentiated in a similar way. But the biggest one I'd probably say is, is sort of scale training workloads.

• 36:47Lukas Biewald?

  I mean, I think like one thing that's also different, that is different than anything I've seen in my career is that, you know, we, we look totally supply constrained. Like all my friends ask me, hey, are we going to Core even now? Look, it's like, can you get me some like GPUs? You know, I'm like, I'm like, probably not. Also, like, you know, if you try to like go buy from the, the sales team, you should realize that like, you know, they're kind of at capacity. So it's a little more like you're going to be like selling yourself to try to, you know, get them to, to sell you GPUs. Doesn't that create like a really different dynamic here?

• 37:20Speaker 00

  Yeah, it does. I mean, I think.

• 37:22Lukas Biewald?

  Because like also, like, it's interesting to be differentiated even when I think like most, many of the customers are using, you know, multiple training providers, maybe just because they, they like are just trying to get capacity anywhere they can.

• 37:35Speaker 00

  But the supply, yeah.

• 37:36Lukas Biewald?

  Yeah.

• 37:37Speaker 00

  Well, and you know, and this is where like, I think the, the, one of the challenges of, of the market. First of all, the demand is insatiable. Like it's, it's stunning, sort of the demand that we have in the market, which is, you know, it's, it's a great place to work for sure, uh, in that regard, right? Like, I think, um, uh, you know, I, I, I believe we have the best services. I believe we have some, some of the best customer experiences, but the demand is really, really high, right? And so, um, that helps certainly. You know, I think from a, from a supply perspective, it's also, it's a little bit tricky to give broad strokes to supply because it's like, okay, great, supply, but like which GPU flavor, right? Like, are you talking about GB 200, GB 300? Are you talking about B 200?

• 38:19Speaker 00

  Are you talking about, uh, H 100s? Like what, or H 200s? You know, what, what supply are you looking for? And, and what's your quantity? Like, are you looking for 10? You're looking for 100? You're looking for 1,000? You're looking for 10,000, right? Like, there's not a lot of places that can run 10,000 GB 200s in the world, right? Um, and so, yes, like there's, you know, this range has definitely got some, some supply constraint, um, in sort of what some of the requirements and demands are, are hard to deliver. And so I think that, that, that, that is absolutely true. But I would say, you know, there is, um, a growing sort of amount of both research and then sort of supply to deliver upon different approaches to those same workloads, right?

• 39:01Speaker 00

  Can you, can you partition up the workloads into more chunks to your point, go to more clouds, do this at that cloud, do this at that cloud? Can you use a different generation of SKU for some of your workloads, right? These sorts of things. And so that I think is crucial to, um, to continue to serve. And we do have capacity when it comes to various different types of, uh, workloads. And a growing amount, actually, as we look at sort of the increased demand for, for, for things like on-demand or, or, or sort of spot type pricing and so on, where I think more and more workloads will, will have those expectations.

• 39:37Speaker 00

  Did I answer your question, Lucas?

• 39:39Lukas Biewald?

  I think so. That was a good question. I don't know, man.

• 39:41Speaker 00

  Yeah, I just, you know, I keep dodging everything you're asking, so and just say, just say what I want to. The essential AI cloud, Lucas. That's the answer.

• 39:49Lukas Biewald?

  You've actually had PR training. I appreciate it.

• 39:53Speaker 00

  I don't use it, though. I don't use it. By the way, I look like really, it's like really dark here because it's, it's nighttime. You know, you've scheduled this. The sun's down over here, so.

• 40:03Lukas Biewald?

  Yeah, trying to tire you out and then come in at the hard hitting.

• 40:06Speaker 00

  Yeah, exactly. End of the day, man.

• 40:13Lukas Biewald?

  Okay, I'll just keep asking the questions that I personally want to want to ask you. So, I mean, I think one of the things that I I really admire about your process and relate to.

• 40:23Speaker 00

  Oh, I thought you were gonna ask about me. Go on, sorry.

• 40:24Lukas Biewald?

  This is why you know, just I really relate to you. It's like, I feel like you are really like trying a lot of tools. Like you have CoreyWeave.com, you know, where you put your, your projects. I don't know, maybe we should censor that one out. Maybe it's like too many people go to CoreyWeave and learn about, you know, what you're up to, but.

• 40:39Speaker 00

  They'd have to guess the subdomain. That's the beauty of it. CoreyWeave.com doesn't, doesn't actually resolve anything, but the subdomains do. Yeah, go ahead.

• 40:48Lukas Biewald?

  And it's funny, I always feel like guilty for not like spending more time building projects and trying to stay on top of AI. I feel like, you know, you're like clearly doing this like big executive function. Like, how are you actually able to prioritize? And how do you like switch your mind into being able to think like clearly enough to actually like build something?

• 41:07Speaker 00

  Yeah.

• 41:08Lukas Biewald?

  Because as I get older, actually, I find that like switching from like a bunch of meetings to trying to like actually like write some code and like especially like use a new library that might or may not be like buggy and I don't understand. Incredibly challenging. Like, are you like blocking out weeks to do this or what's happening?

• 41:24Speaker 00

  Yeah, no, it's a good point. And it's, it's so funny because I actually just finished a project last night and it was like, I worked on it till like midnight. And I was so mad because it was like, oh, man, I'm gonna be so tired tomorrow. And I gotta be on for this interview. I gotta be on.

• 41:41Speaker 00

  But like, yeah, look, and the other thing that really frustrates me is like, you know, my first five years at Microsoft, I was actually an engineer. I coded in Windows. And so like, I was a, it was never .NET. Like, I joke about how I was a professional developer for five years, but it was all assembly in C. Like, I'd never, I never professionally coded any managed language. And when I was in college, dating myself a little bit, like, I don't think there was any course that was in a managed language. So, but anyway, I had this, why, you were gonna, you were gonna comment on this, on the managed.

• 42:17Lukas Biewald?

  I know, I just, I've worked with guys like you. I have a feeling, I have a feeling I'd find some flaws in your coding style.

• 42:23Speaker 00

  Oh, 100%, man. This is why, my production, look, my production coding is not, is not.

• 42:29Lukas Biewald?

  I'm not saying I'm like the master. I'm just thinking about colleagues that I've worked with where their, their background is completely like C and assembly, and now they're writing Python. And it's just like, batchy crazy.

• 42:37Speaker 00

  Yeah, that's right. I mean, the concept of functions is boring to me.

• 42:42Lukas Biewald?

  Yeah, why? Why bother?

• 42:43Speaker 00

  Why, just, you know what? If you're smart enough, Lucas, you can just write it all with jumps. I don't understand.

• 42:49Lukas Biewald?

  Absolutely.

• 42:53Speaker 00

  Anywho, so, look, I think that one of the things that's both really good and bad is like, when I get into a project, it, like, it does consume me. So like, I actually don't allow myself to do projects that often, because I know once I start one, it's like, it really, it like consumes me. And I get like, super frustrated, because inevitably it's not going to work a bunch of the time, right? And so, I also, look, because it's not, because it's not a production level coding, the part of it is also just setting boundaries for like, good enough, right? Like, a good example, I've been working now, and I just deployed it actually on a bunch of CoreWeave infrastructure. I've been working

• 43:32Speaker 00

  on using Anthropic, actually. My brother works Anthropic, so I thought I'd give it a go. Using Anthropic to basically build a new CoreWeave portal. So like, I wired it up to connect to our backend APIs. I tried to wire it up to Grafana. But yeah, like, there's points where you sort of get to good enough. Like, I couldn't figure out how to get the Grafana token. For me to connect to the API and I don't know if that's a core thing or something, something else. And so I gotta dig into it, but in the meantime, I just put basically mock data in. I'm like, forget it. Like I'm just, I want to just see if I can get something to work versus to, you know, for to spend forever to figure out how to get to our Grafana API.

• 44:14Speaker 00

  So like that to me is a big part of it, like setting boundaries on what am I trying to do? And making sure I don't get too caught up on the things I'm not trying to do as part of it. Um, and being sort of willing to kind of take, take passes. Um, but then, yeah, I mean, it's like, it's about carving out the time, like, um, uh, I'll admit, I think one of the meetings that you and I were in where you, I wasn't really paying attention. I was coding. I was like,

• 44:36Lukas Biewald?

  Hey, wait, that was something I was thinking last night where.

• 44:40Speaker 00

  I think actually, uh, actually, yeah, no, two nights, there was, there were moments. There were moments. Um, so, you know, uh, but like it, look, I think it keeps, um, like it's a stupid thing. This thing that I built with this portal was a stupid thing to go build. Like it's like, it's, I think the outcome, I don't know. I'm going to write a spec around the outcome because I think there are some interesting things that we could go learn from it. But in some ways I just learned a lot about challenges of writing an application like that using, you know, and like an API like Anthropic, like, you know, I wanted to be able to put stats and buttons. And so, but to do that, then I needed, and so the API, you know,

• 45:21Speaker 00

  the API calling was working great, but like doing two things wasn't working. Like you can only do one thing because you can only take one pass. And so suddenly now I'm like designing, oh gosh, well now how do I make two pass? Like, do I think about forking it off and doing two calls? And, you know, so anyway, like, and so it got me into the mindset of like, okay, like, I feel like it was a huge waste of time, but then I also feel like I left and I'm like, I kind of get now what, how hard these types of applications are going to be. And how to think about where can we deliver services capabilities that make some of those things? Some of them we can't help, right? But like some of them we can, some of them we can make easier and simpler to go be able to build.

• 46:01Speaker 00

  And so for me, like the best, the best way to be a product leader is to play with things out there in the mindset of what your customer is going to be doing and then talk with your customers about it. And like, and evaluate, make sure that like what I was doing is not totally stupid. Like the worst thing is I do this thing and the customer's like, well, that's, I would never do that. And then like, well, okay. So then it definitely was a waste of time, but for the most part. Uh, I think it keeps me sharp in where the product actually is and in using our own product as a key. I've used your product a lot, Lucas.

• 46:32Lukas Biewald?

  I know, I know. I appreciate it. Yeah.

• 46:33Speaker 00

  A lot. Oh, by the way, I used Weave in this product. So I had, I tracked all of the commands that people were, that we say I was doing through this portal thing to Weave. Yeah, it's nice.

• 46:44Lukas Biewald?

  So do you have any advice for me as like, uh, like a long time executive on a cloud company and to a founder who's trying to be an executive? Is there a, what should I be doing differently?

• 46:57Speaker 00

  Look, I, I look, it's hard, man, because, um,

• 47:05Speaker 00

  for me at least, is that the unfortunate reality was a lot of it was circumstance, man. Like I got, like, I got, I got tapped to go write the spec on infrastructure as a service in 2009, where there was one player in town. And so it was, it was like, um, it was like, cool, you know? Um, and, and so, you know, I think I got some things right. I think the things that I got right, um, uh, are the things that I think you do naturally. So, you know, like, which is iterate frequently, ship something and learn, um, realize that the first thing you're going to do is make a bunch of mistakes, but listen to your customers. I mean, one of the things that I feel like, um, is the strongest sort of argument I can, I would make and, and,

• 47:50Speaker 00

  um, you know, I think Corey does a really good job, but it, it always takes refreshing on this, is like, who are your customers and are, uh, and are they satisfied and happy with what you're building and what you're planning? I wouldn't say let your customers design what they're building, right? Like that's, it's, there's a fine line between like, you know, like, but I always took this attitude of like, when I go and talk with a customer, I don't want to just have open ended, like, well, what do you want? Because it's a stupid question for a customer, because it's just-

• 48:18Lukas Biewald?

  So what, what do you ask? Actually, I feel like this is always, I talk about this a lot.

• 48:22Speaker 00

  You know what it, you know what it is? I always come with, with like, hey, here's what we're building. Now tell me what you think, right? Like, or here's the direction we're going. Like, I, I seed it.

• 48:35Speaker 00

  Because then you get into actual actionable feedback, right? If it's just like, well, tell me what's missing. You're gonna get, you're gonna get sort of, oh, my gosh, this morning, I was really annoyed by this. And like, that thing may never have happened before and may never happen again, but it's top of mind that morning. And so this open-ended nonsense of like, well, tell me what you want. I feel always fails with customers. And also, customers' job is not typically to be a product owner. Their job is to be a product user. And so they're not going to give it to you in terms that are actually, I think, as actionable. But if you go and pitch, I've got this idea. Let me show you what I've got. Let me show you, and go as far as you can with screenshots or flows or whatever. But like, you know, build that confidence with the customer of like, I'm sharing this to you ahead of time because I want you to tell me.

• 49:20Speaker 00

  Then you get like, I, I love the feedback from those sessions because you get like this really actionable like, oh, this is cool. But I like this instead of that. Or you get like, sometimes that heart-wrenching, I don't think I'd ever use this. And just like, oh, ah, really? Like, ah. But, but better than like, I'm gonna go build something and then I'm gonna say, well, what do you want? Well, they didn't say they wanted that, but I think they probably do anyway, right? Like, you know, that's a useless approach. But I love that approach. I love it and I love getting the chance. And I haven't done enough, frankly. I did a bunch of customer conversations at the beginning of my time at CoreWeave. And now I'm sort of kind of learning everything that's in the pipeline. But like, to me, my next step is really like, okay, great.

• 50:03Speaker 00

  This is what we're launching in February. I want to go sit down with customers in December and I want to test it with them and say, would you use this? Like what, like, how do you feel about that? And that, to me, is the best way to get feedback.

• 50:17Lukas Biewald?

  Is this just something that you learned intuitively? I actually totally agree with it. But have there been like, I don't know, like books you've read or like something that you've consumed that have kind of like helped you along the way?

• 50:26Speaker 00

  I don't like to read, so.

• 50:29Lukas Biewald?

  That's apparent, yeah.

• 50:30Speaker 00

  No, actually, look, I think there were some books that I read. I'll look, I'll be, I'll be like, super transparent. The, I feel like a lot of what I learned about how to think about product and how to sort of approach that product in those early stages was from. My boss at the time, Scott Guthrie, who's still at Microsoft, right? And, you know, I felt like, you know, he had done, he had done a bunch of work with sort of the original .net and, and sort of was a leader in some of the original design there. And then he took over Azure and led a lot of the Azure strategy along with Jason Zander. And, and I feel like the approach to product that Scott had was probably based on a bunch of books he had read. So, you know, I've got basically, maybe, maybe you should have him on the podcast.

• 51:15Speaker 00

  But it was really this focus on like, you know, going with customers, learning from customers, building and iterating.

• 51:22Speaker 00

  And so there definitely were a bunch of books, Toyota Way, I think was something like, I remember that working, sort of how to think about.

• 51:29Lukas Biewald?

  Doesn't it start like throwing out random books? Nobody wants that.

• 51:35Lukas Biewald?

  The Toyota Way?

• 51:36Speaker 00

  He caught me. That was one of the books. I didn't read it, though.

• 51:39Lukas Biewald?

  What is it, like 2005?

• 51:41Speaker 00

  But yeah, that's right. Dude, this was in 2009. This is the. Okay, you know what?

• 51:48Lukas Biewald?

  You know what? I appreciate, I feel like your process, I mean, what I observe is actually like kind of building, and which I think probably helps authentically connect with the customers. And it's funny, because the first thing that I would say, actually, for customer interviews, which I'm not saying in the world's expert on, but like my feeling of after years of doing it is, yeah, you can't ask open ended questions. You have to show something. And like, I even, it's funny, I always try to, like, make it look as built as possible, you know what I mean? So I feel like showing, showing someone like a website, like actually what you do with Corey, we've like, just like putting a URL where someone can kind of see like a mockup, but it feels like more like a product. I feel like you get more honest feedback. And the more you can actually like mock it up where it looks like, hey, I built this thing. What do you think about it? Versus like, I might know this thing. I just feel like you get more.

• 52:30Speaker 00

  Text, text ideation versus something, yeah. In fact, I will send you the link to my, to my, my Anthropic based portal, Corey Portal Experience, actually.

• 52:41Lukas Biewald?

  Awesome. We'll put it in the show notes.

• 52:43Speaker 00

  I'm not going to broadcast it here because it's got my real data on it. It's got my real, my real cluster working. Yeah, I had to make it work, man. Had to make it work.

• 52:51Lukas Biewald?

  Plus, this is some good IP, you know, I think it constantly like automatically configures based on what you might want. That's pretty awesome.

• 52:58Speaker 00

  I mean, that's the idea, man, but it's, I mean, it works terribly, but I'm sure real smart people could do a much better job. But like, you know, it works, so it's fine.

• 53:08Lukas Biewald?

  All right. Well, it seems like a good place to stop. A lot of fun.

• 53:13Lukas Biewald?

  Thanks so much for listening to this episode of Grading Descent. Please stay tuned for future episodes.