CoreWeave, Inc. Class A Common Stock Goldman Sachs Communacopia + Technology Conference 2026

Sure. I'll do the best I can. One of the things that's important to understand is when we built the company, we had an opportunity to break it down to first principles and say, "If you were going to build a cloud, specifically built to address the needs of artificial intelligence, parallelized computing, how would you go about building that?" The clear answer was, you don't go about doing that by retrofitting a legacy environment to go ahead and create the solution. We jokingly talk about it internally, it's like the minivan versus the F1, right? It is a tool that was specifically built in every decision from when we founded the company in order to optimize for this specific use case, not to provide generalized computing. There are lots of great options for that.

What you have is an environment that has these compounding, incremental, thousands of decisions that have been built around making the environment as performant as possible for this specific use case. We select our clients carefully, in terms of finding folks that need this use case to be able to be supported. You find a software stack, an infrastructure stack, all of those things really are built to be able to provide that environment in the way that we do. It is great to hear that the clients that you are speaking to are taking advantage of the efficiencies that the tooling that we built provides them.

Sure. One of the things that we believed very early on was that the space was going to evolve very quickly. When you are in an environment as dynamic as that, you want to build your infrastructure to have the most amount of optionality embedded in it as possible, right? We do not really think about our infrastructure as being, "Oh, this is our training infrastructure, and this is our inference infrastructure." We think of it as AI infrastructure, and we build to a standard that allows our clients to use that infrastructure in whatever way they deem to be most productive for their businesses. That is how we built it.

All of the tooling that we have within our Mission Control and all the other observability suites and all the tooling that we have provides for an environment that allows for incredibly performant environment for folks that are using the compute. We can see when people are using it in different ways. The consumption profile will look different. All of those things will follow with their use case. To varying degrees, different parts of our stack will provide for different advantages, depending upon what their use case is.

Yeah. We have been incredibly consistent in the way that we talk about demand, and that has been driven by our ability to talk to an incredible cross-section of compute consumers, right? That's everything from the hyperscalers, through the AI natives, the frontier labs, people that are productizing and delivering agentic AI solutions, all of those things. We have never flinched from our assessment that the world's capacity to deliver compute has been, and will continue to be, wildly overwhelmed by the delivery and demand for intelligence, broadly speaking. We've been righter than wrong on that one. I've got a bunch of really smart folks around me that come and email me every day that we don't have enough compute. I'll take their word for it.

One of the really interesting, I'm not sure this exactly answers your question, but one of the really interesting phenomenon that you're seeing in the market right now is the large consumers of our services of compute delivery of the software stack that we've built on top of that. Those consumers are demanding ever larger amounts of resources, right? We have the 9-month rule at CoreWeave. We look back at whatever we've done, and 9 months later, we think it's cute. That's the dynamic that we've seen in the market. But that is being compounded right now because of new entrants into the market, and new entrants are enterprise clients coming in. I talked about this a little bit on my last earnings call where a company like Caterpillar comes and starts to use us.

It's a great example of enterprise consumer coming to us and saying, "Hey, the way that we're going to participate with our company in artificial intelligence, the way that we're going to train our models, the way that we're going to serve our models, is going to look different than it has historically. We're going to build our own clusters." That is transformational, right? That is really allowing CoreWeave to establish itself as an AI cloud participant, a hyperscaler within the AI system, and that's been really, really exciting for us.

I think it is a lot of things. I think part of it is the experience of building cloud-based systems over the past 20 years has given companies some perspective about how important compute was going to be. Then with the advent of artificial intelligence and the degree to which that kind of raises the stakes, there is an interest in having more control over that resource that they consider to be fundamental and important to their businesses than perhaps they did historically. It is the boiled lobster problem, right? The cloud kind of came out of nowhere, and people began to use it, and people were using it before they realized how incorporated and embedded it was going to be within their critical systems.

This time, they are going in with their eyes wide open, which really provides us with a wonderful opportunity to go to them and say, "Hey, we can really assist you beyond what has been an oligarchy of three massive companies that have delivered this service. We have some alternatives. We have a different way of looking at it. We have a different way of providing the compute that will be most performing to you." That drives down cost. It does all kinds of great things for them.