DigitalOcean Holdings, Inc. Goldman Sachs Communacopia + Technology Conference 2026

It is wonderful to be here. It is a wonderful way to, what I call, start the sprint to finish the year.

Yeah. Thank you, Gabriela. That is a great question to set us up here. I think the first thing we had to figure out was what role did we want to play as an AI infrastructure provider, right? I think the first order decision was to figure out in the AI infrastructure space, there were two broad categories. One was training, one was inference. We made a bet, which at that time, a lot of people squinted at that decision saying, "Okay, we do not want to go after the training space. We want to go after the inference." Which at that time was a little perplexing, but in hindsight, the reason why we made that decision was, number one, self-reflective. What are we good at? We are really good at understanding developers. We are really good at building platforms.

We are really good at managing global scale infrastructure for production workloads. That was a big part of it. The second was inferencing. We believed back then, and now everyone believes that it is the more durable workload. It is the workload that companies eventually come to when they start making money. It is the workload that the end customer is paying for the most part, versus the VCs or your investor money. That was the biggest decision we had to make. Then there were a lot of other decisions. Number one, we were fortunate to have an incredible talent density for building platforms. Over the last 18 months, we have added to that talent pool in a big way. That's one. The second is we have a phenomenal luxury of direct customer interaction and direct customer feedback.

Because when you're building a platform, it's really hard to build it in a lab or build it with four or five very deep customers, because usually that takes you in a way that doesn't lend itself to building a broad platform. Having the luxury of now 680,000 customers, is a luxury that not many companies have, right? Then you fast-forward to where we are right now. If you take a step back and think about the platform that we have built, we actually made a couple of other important decisions. One is we decided to build for the most part, and we had a couple of tuck-in acquisitions here and there, but for the most part, we built a platform because my fundamental belief is platforms cannot be stitched together. You cannot assemble it. This is not an application portfolio like Salesforce.

There is a reason why Azure, Google Cloud, AWS did not have a lot of bolt-on acquisitions. Platforms, by definition, need to be built from the ground up and needs to be integrated top to bottom, right? That was one. Another important decision was the order of operations. The sequencing really matters. We built software first, now we are adding scale, right? A lot of companies went for scale first and now are building software. We'll see where we all end up, but we like our chances and our order of operations. Finally, I would say if you take a step back, Cloud 1.0 was built to cater to applications that were built, deployed, and managed by humans for the most part, right? Even the applications were servicing humans. But now, the cloud that we need to build caters to applications that are built by agents.

Agents are deploying these applications. Agents are monitoring and observing it. The cloud needs to be built for agents versus humans, and we call that the AI-native cloud. That's how I would summarize the last three years of our journey.

Yeah. When you look at our customers and what they are doing, of course, coding is a big part of the whole inference ecosystem for a number of reasons, right? It is very structured. There is a huge corpus of ground truth data you can feed into models. So there is a lot of reasons why coding has really taken off, and coding is also the fundamental building block for many other things, where you can actually build PowerPoint slides, or you can build interactive applications using coding as a building block. So there is relatively no surprise there, and we have a lot of customers that do that as well.

If you look at some of the other emerging micro verticals, generative media, not just from a model perspective, but there are a lot of companies that are reinventing how digital ads are produced, inventing even full-length feature films, changing the workflows of movie production. There is a lot of action there. It is also with OpenClaw and Hermes and other agent harnesses, personal productivity is seeing. GrokBot, I was very pleasantly surprised. I have been using it for the last 10 days.

Yeah. It is an amazing product.