--:-- Sarah Guo: AI has become the tool that's causing this kind of security apocalypse. It is also the tool that can help us to solve it faster as well.
--:-- Dane Knecht: It went from how to get everyone just to using AI. Now all of a sudden, everyone's racing to figure out what AI security means.
--:-- Sarah Guo: I've heard serious technical people say things like, air gap everything important. And we're not going to be able to trust the internet for a while. And we just assume all the critical infrastructure and government services fall down at some point. Is that your expectation for what happens?
--:-- Dane Knecht: Dane, I'm so excited to do this with you.
--:-- Sarah Guo: Yeah, thank you. Thanks for coming here too. I'm sure I'm not the first person to make this joke, but your last name, Connect, that's pretty good for the Cloudflare value prop.
--:-- Dane Knecht: Yeah, yeah. There's been some jokes about renaming the show next year. So with everything that Cloudflare is doing, what are your top few priorities as CTO right now?
--:-- Dane Knecht: Well, this past year, it feels like 10 years compacted into one. So those priorities are constantly shifting. But it all goes back to our mission of helping build a better internet. That really hasn't changed over the last 15 years, where we want to make sure that the internet's secure, that everyone has access to be able to get their content online easily and scale it up.
--:-- Dane Knecht: Just over the arc of the AI changes in the past year, it went from how to get everyone just using AI, how do you make it easy for them to deploy and their agents deploy, to like most technical transitions, security is kind of an afterthought. And now all of a sudden, everyone's racing to figure out what AI security means. And it means different sides view it kind of differently. One side is, as a company, how do you keep your data safe from AI leaking the data out? But it's also how do you keep people from getting in as well.
--:-- Dane Knecht: Over the last three to six months, the number of vulnerabilities that are getting reported in CVEs has just gone up exponentially. Previously on the internet, we would see these Log4j moments or these Shellshock type incidents maybe once a year. And it would be all hands on deck internally at Cloudflare to make sure how we protect not just our enterprise customers, but also our free customers because we view it as a kind of public good and making sure that the internet stays safe. These things are now happening weekly. Not all of them are publicly reported on, but there are things that are as serious as the Log4j type things, but just having a greater frequency.
--:-- Dane Knecht: I expect that through the rest of this year and in the next year, by the next 18 months, the majority of teams' time is going to be spent on security. I think there's a stat that was put up earlier today during one of our keynotes, showing that I think over 50% of engineering time is going to start to be spent on security. I don't think that will last forever. I think that will be a short transition. At some point, the AI will have surveyed the majority of the code and found most of the bugs or found most of the shortcuts.
--:-- Dane Knecht: There's one that's kind of coming out today and has been started to be blogged about and tweeted about where one of the keys on the internet that protects all TLS and WebPKI, which just secures all your connections, was secured by the number four. Literally, they basically used, you know about cryptography, it's all about randomness, right? That's why our lava lamps are so that you can get good randomness. And when a key out there uses the seed, the initial thing to create it with a single number four, it's going to be reverse engineered. And AI can just do all these things. It doesn't sleep. It's not like the one engineer you had that was red teaming things.
--:-- Dane Knecht: Last week, I think OpenAI found the seeds for the NIST curves that were back in 2000 that were released. So these things are just moving so fast and the bar is going up and the models are just getting so good at cybersecurity. Mythos was just kind of the tip of the iceberg there. Since then, it's not just been the models getting better, it's the harnesses. It's how humans know how to use them and use those frontier models in order to find those exploits.
--:-- Sarah Guo: Given your visibility, what do you know about the humans behind these attacks and harnessing these models and taking the volume of vulnerability discovery up so quickly? Are they nation state actors? Are they script kiddies? What can you say about how the attacker landscape has changed?
--:-- Dane Knecht: For some of these larger vulnerabilities that have come out more recently, actually haven't been nation states. They've been high school kids even that are...
--:-- Sarah Guo: We're going to call them agent kitties now.
--:-- Dane Knecht: Yeah, that are just spending their time, like they used to do capture the flag security contests. They're pointing their agents at an area and doing that. There's also financial reward for them. There's bug bounties that they get paid out sizable amounts. But it's given the tools that honestly the nation states have had in some forms for much longer, either through agents or through sheer number of people that were working on the problems, given it to the masses.
--:-- Sarah Guo: This is the first time in 15 years I've heard serious technical people say things like, we should just air gap everything important. And we're not going to be able to trust the internet for a while. And we just assume all the critical infrastructure and government services fall down at some point. Is that your expectation for what happens?
--:-- Dane Knecht: Humans, we are pretty adaptable and we can move fast when we need to. I've seen the industry kind of partner together. When things like this happen, people that you usually think of as competitors are no longer competitors. We're just literally protecting critical infrastructure. I think when those kind of critical moments happen, people will rise to that challenge. On the last doomsday, I do think that a lot of the things that we've done over the past five or 10 years, moving away from a castle moat infrastructure for security to moving to more of a zero trust, does put a lot of companies in a better position where you're not saying this office is completely air-gapped. You're saying these devices, these flows are secured in a different way and everything's going to be tightened.
--:-- Sarah Guo: What is it going to take for organizations to do what you're describing? Like 50% of engineers do not work on security right now. I had Greg Brockman from OpenAI on the No Priors podcast last week, and he said that he thought in 2027 people were going to spend as much money on tokens for security as engineering. Like you're saying, very related idea. What is going to drive that shift?
--:-- Dane Knecht: Just emergency. You're going to move forward all your security spend over the next 18 months, both from the red team side, which is more of the offensive, trying to actively try to exploit things, as well as the defensive side, how you prepare things. But I don't think that's going to last forever. I see a world in like 18 months where new software productivity goes way up because all those resources are back focused on that. But there's definitely a period where security needs to be on everybody's mind.
--:-- Sarah Guo: What are some of the key elements of getting to a better place in terms of overall software and internet security? I think people discover, of course, that there are libraries and services everyone uses that had vulnerabilities that took effort to discover and now do not. And I think we'll hit some of those. What else is important there? Because part of the concern that I have is the rate of software production is also going up a great deal. To some degree, we got to patch everything that we have already made and then keep up and get ahead of the pace of delivery.
--:-- Dane Knecht: For one, right now we're patching 70 years of software out there. So some of it is just catch up. And then on a go-forward basis, the software development lifecycle, the agent development lifecycle is going to need to change. Luckily, the same way that we can use security right now for red team and things like that, it'll just be built into the process every step of the way. I think software will just get more secure over time.
--:-- Sarah Guo: What have you learned about building secure production software internally already that you think people can learn from? What does that mean? Shift left. There are many theories of how to do this, including broader use of formal verification, using agents for security in the development process. What do you think is going to create better software from first delivery?
--:-- Dane Knecht: I can go back to first principles. You want to reduce your attack surface area. The easiest thing you can do is to give less places for there to be vulnerabilities. So looking at all your software and saying, how can I simplify this? How can I reduce the footprint, the code? Beyond that, things like formal verification, safer programming languages, things that are built into the runtimes that make everything safer will come. But I think it just starts with that. AI, at least early AI, is very verbose. It likes to create complexity. So AI in a sense of what we've been dealing with has actually not been helping build more secure stuff right now, but I think it will get there. That's where humans still come in and human judgment comes in and making sure that we design the software in a way that it can stand on its own securely.
--:-- Sarah Guo: That was actually going to be my reaction. When you say we want to reduce the surface area, I'm like, oh, yes, of course, in principle. And that's not the natural inclination of today's models. I ask it to do something and I'm like, with one-tenth the complexity, please try again. Is that the role of engineering and security engineering today? Is that something that's going to be solved at the model level?
--:-- Dane Knecht: The way that humans did before agents, it needs to be solved at all levels. You need to train the engineers that are writing the code, the product engineers. The security teams still need to be involved in making sure that they're getting checks and balances, a second set of eyes on things. You need to build in processes. We've gone to defining things a lot more internally on how we build at Cloudflare, writing down our principles. We have a document called the Codex, which is kind of like a buildup of a lot of RFCs that the teams have built. Here's how you build secure software at Cloudflare. Here's how you build available software at Cloudflare. Here's our best practices. And then it gets boiled up into some 10 commandments that the agents know how to follow and use in every part of the review process that can help enforce those things. You have agents out there that are just riding a lot of the slop and then you have deeper down the factory. You have people that are doing the performance runs and the security runs. Just like how the company operated before, you need those adversarial reviews.
--:-- Sarah Guo: When you zoom out a little bit and just look at overall traffic on the internet and how much of it has become agent driven over the last year, I think it's outpaced most people's expectations. What has updated in your worldview of what the web a year from now looks like, either from an economic model perspective or a security or requisite infrastructure perspective?
--:-- Dane Knecht: I kind of think of it as we're in the messy middle right now where humans and agents are riding the same rails on the internet. Agents are trying to parse a human web when it's just inefficient and was designed for humans to do things at different speeds. Going to a website and being able to read and see the ads and participate in the full economic model versus an agent that now can go to a thousand web pages in the same period of time, which is great. You just need to find a new economic model to support that.
--:-- Sarah Guo: Do we get parallel webs? Is there like a human web and a machine web? Everybody's trying to do, what's it called? AEO now?
--:-- Dane Knecht: Yes, I think we do. I think we find ways to deliver the content and meet agents and humans where they are, as opposed to trying to meet them in the same place. Right now there's translation layers. There's a lot of companies that help an agent view a webpage. These are just all extra burning of tokens for things that probably don't need to happen. The website usually knows what data it has. We've had things like this, we've had APIs, ways that computers talk to each other for years. It's just that APIs only covered a small fraction of the information on the internet. And agents have a thirst to understand everything. So they're going out and trying to explore the human internet. We need to make it easier for them. We need to make it less costly for the site owners. And we need to find a way for them to get compensated.
--:-- Dane Knecht: In a world, you can get very simple. Most content websites, like a Substack, they know what their CPM is for how much money they should be making on ads for that site. So if an agent's reading the site, I think there is a world where you get to the point where an agent can decide whether or not they want to read the content. And then they can decide if they want to pay the CPM rate. That's where you need to then get new payment rails for the internet that can do millions of transactions a second for these little micropayments. All these things we've been talking about for years, micropayments, always two years away. I think agents will actually push that forward and we will see a world where there is a new economic model for content creators.
--:-- Sarah Guo: Who do you think the players are? What are the variations of that infrastructure? I think Cloudflare has an important role to play here. But the rise of personal agents like Instinct and Muse have also made this an immediate question from a transactional perspective. I don't think everyone knows on the other side what the business outcome is going to look like. Everyone's been through these transformations where the internet was thought to kill Main Street. It didn't kill Main Street. Small businesses are still thriving. But there were people that were displaced, so there's always some skepticism. There's some natural inclination to just block them out. You saw Amazon just say, no personal shopping there from an agent. I think these are all people in that messy middle, but they're trying to figure out what that path forward is and trying to keep some of the negotiation leverage there. I think we will get to a place where Muse and Dots and all those personal agents will be able to accomplish tasks seamlessly as you as a human could do, even easier. But I don't know if the technology is quite caught up to that yet and the business models either.
--:-- Dane Knecht: Is there anything you're personally excited about on the roadmap or just from a technical exploration perspective on the Cloudflare front that you feel like is going to enable this ecosystem in the future?
--:-- Dane Knecht: Absolutely. On the content side, we've released a conference monetization gateway where we make it easy for people to put their sites behind us and take microtransactions for their content, including providing wallets for agents to use, and a stablecoin that's going to be able to help facilitate that transaction as well. We're also doing things with OpenAI, a project called Signals, where we're making it easier for agents to actually discover content. Instead of having to crawl the entire internet and continually go back to pages, we're making it easier for them to know what's new content and more proactively do that. So it's a win for the AI labs as well as a win for the site owners not having to get constantly crawled and pay for that infrastructure.
--:-- Dane Knecht: There's a whole set of kind of new laws on the internet that I'm really excited to see grow. The X402 from when Stripe came out with it, I loved it because it went back to the 402 HTTP code, which Tim Berners-Lee created 20 plus years ago, 30 plus years ago for payments. So you kind of always knew that you needed a better payments rail on the internet, but we haven't been able to figure it out. I think agents will lead us to that as well.
--:-- Sarah Guo: When you think about these initial products that you've released, what would success for a content creator or somebody who ostensibly had a website on the internet that they were monetizing with ads before look like? What's the killer success case you guys need to see or show the world where it just becomes like a default to do this?
--:-- Dane Knecht: Instead of them paying us, we're paying them. Where it's covering their infrastructure costs. It's providing money that supports their livelihood. We can actually increase the number of content creators out there, which the last generation of the internet has done very well with YouTube and TikTok and X. We can actually make it exponentially larger.
--:-- Sarah Guo: When you look at the workspace OS release and ecosystem work that you guys have been doing, what are you hoping are the biggest use cases of it coming up? This is transitioning a little to a new release called Cloudflare OS.
--:-- Dane Knecht: Cloudflare OS is our internal platform for how our employees use AI every day. It actually goes back to security roots where we were very worried about customer data and internal data leaking out. We wanted to make sure that our employees could use all the new AI tools and models but have a way to safely deploy them internally, to understand how that data is being used and flowing, and have good governance over that. The reason I call it Cloudflare OS is we started to realize that as we have more and more agents, we need to be able to teach them what we call "how we build at Cloudflare." For humans, we did that through the university and the onboarding process and meeting your colleagues and working with them. But we needed to really find that and document that for agents.
--:-- Dane Knecht: Cloudflare OS is the platform where our employees can build anything that they want in a secure way without having to think about security. It's not something they have to think about. They don't have to worry about security. It's just built in there for them. But they also know that it's being done in a way that is consistent with the themes and values of how Cloudflare works.
--:-- Sarah Guo: Why release it? I think of this as somewhat different from the other products that Cloudflare offers today in that it is not infrastructure. It's an end user facing product for managing AI use within the organization. Why release it? Or do you think of it as a departure?
--:-- Dane Knecht: For one, it's kind of a reference architecture. Over the past 10 years, we've built our developer platform where we started with just a simple serverless compute primitive. And now over 100 different developer platform tools from storage to databases to durable objects. We wanted to show how you can build it completely on Cloudflare, how we build things internally, and give people the option to fork it and build their own version of their own company OS on top of it.
--:-- Sarah Guo: What is a way in which it is helping your people and your organization that you think is clear success?
--:-- Dane Knecht: It's actually used more by our go-to-market teams and our G&A teams than it is even used by our engineering teams. Early on, I thought training was the biggest gap for people using AI. When you just point them at a chat interface or another tool, it's too much of a blank slate for them. This is a platform that's designed for how your business works. You immediately can go there and get access to all the data that they need. They can get guided and taken through where they quickly realize, oh, this is not trying to replace me. This is trying to make me better at my job. That's been really exciting to see just all the different ways people at the company have done that. A lot of how this conference got put together, the marketing team built hundreds of internal tools where previously they would have had to go out and work with different agencies. But the speed that they can move with a smaller team now is just amazing.
--:-- Sarah Guo: Assuming this is a continuation of starting in May, you guys did this restructuring to be an AI first organization. Reflecting on the last number of months, what has worked or not worked that you would recommend to others?
--:-- Dane Knecht: The restructuring was hard. Saying goodbye to some of my colleagues. It was the first time Cloudflare ever did it. We had always been very careful not to overhire. This was for different reasons. This was because we saw the way AI was transforming some teams and how they work. We thought of it as like a factory floor where you needed to actually rebuild, rethink how things happen. There were some processes where the way a product manager would send an email forward to customers, it involved three teams. It involved a team where you went to BI to go get a cohort of the people that you wanted to send an email to. You went to the marketing team to help you design the email and get the voice right. You went to the marketing operations team to get the email out. You're never going to be able to actually redesign that process unless you make some hard changes and force people to rethink what actually is the right way to do that. It might not involve those three teams at all. It might just involve a new way of doing things.
--:-- Dane Knecht: What came out of that was a tool where a product manager now goes in and describes the cohort. They write an email. It rewrites it in Cloudflare's voice. It sends it to their manager. The manager can click approve if they like it, and it goes up. We didn't go from three teams getting faster at doing that. We went to one tool that can let a product manager now have a superpower they didn't have before.
--:-- Sarah Guo: When you think of all of the different workflows and tasks within an organization that's got about 5,000 people like Cloudflare, how do you decide who the owner is of rethinking that process? Was it bottoms up from one of those teams in this case? Is it an organizational leader? When you have so many of these things that could change to be faster and make more sense, as you described.
--:-- Dane Knecht: Cloudflare has always had a thousand more things that we could ever do, whether it was products and features or things like this. We always look for people that are going to take initiative and ownership. It doesn't really matter if you're ordering it one to 100 and trying to prioritize it. Any one of those hundred things are probably safe if someone's passionate about it. We gave people at the beginning of last year the tools and started seeing how they were experimenting. People quickly broke out in different cohorts of people that were really leaning in and naturally doing those things and taking ownership of them. I think it was very bottoms up from how we're going to do those things.
--:-- Sarah Guo: It's been a major topic of conversation for organizations as to how they should think about token budgeting. What's a reasonable amount to spend? How do I think about this versus human capital? Should we get tokens even within our organization? What is your philosophy on this now?
--:-- Dane Knecht: It's definitely changed. Each model kind of makes you rethink it as the cost dynamics change. But in general, I think it's kind of silly that we're actually asking humans to decide which model to do each task. It should be intelligently routed.
--:-- Sarah Guo: Exactly.
--:-- Dane Knecht: Humans just aren't ever going to be good at that. Early on, you do it kind of brute force and you get people to experiment. You say, let's try for the planning part, let's use the top frontier models for that. Once the plan's written out and agreed upon and iterated on, then potentially some more of the open source models can go do that. Then you go back and you have one of the frontier models do the reviews and the red teaming and things like that. All that today is fairly manual. But as we start to learn and experiment, I think people will become intelligent. Over time, there'll be more governance on that.
--:-- Dane Knecht: At Cloudflare, largely we let people use the models and tools that they see fit for the job. We don't have a token leaderboard. We don't encourage that. We encourage people to focus on the output. They're not graded on if they used it. They're graded on what they've shipped and what they've built. But we do have some kind of notices. If you happen to use $300 a day, you just get an email that says, hey, did you know? Because most of the time people didn't realize they were doing it. If it gets to like $500, it goes to your manager. If it goes to $1,000, it goes to a VP in a day. But those things rarely happen. Usually people are actually happy to get those notices.
--:-- Sarah Guo: Where do you think you are in your overall evolution of rethinking the way different things at Cloudflare are done, from go to market to engineering, just for the current level of capabilities of models, assuming no new development?
--:-- Dane Knecht: I think we're still so early. Two years ago, we had about 200 interns. What we saw was those interns were really the first fully AI native group. If you took AI away from them, I don't think they would be able to work.
--:-- Sarah Guo: Is that good?
--:-- Dane Knecht: Actually, I think it is. I think they know how to use the tools better than us. It's just like you took Google away from me over the last 10 years. How would I learn anything? That's where they reached to first. We actually saw the managers that had interns from that summer actually adopt AI faster. So this past summer, this past year, we decided we were going to hire a thousand interns.
--:-- Sarah Guo: For a 5,000-person company?
--:-- Sarah Guo: Yes. Wow. Yeah, over the course of the year. Yeah, still. Yeah, and it's just been amazing because, one, just the number of ideas that come from the interns. So that's something that, with AI, lets us experiment faster. Having more ideas, getting more people in there, but also just seeing the way that they use AI. If they need to fill out a form, they reach for AI. And I still find myself in so many things where I think, "Oh wait, I've just been doing this manually still," and then I realize, "Yeah, I should be using AI." And I don't think that that's natural for most of us yet. I think that will take time. So yeah, I think we're still very early in our AI journey.
--:-- Dane Knecht: I love it, though. The mass intern strategy.
--:-- Sarah Guo: I run a very small partnership and we always have an intern or two floating around a team of about a dozen for ideas and intern energy. But we just converted one of our in-college interns to full-time and had him drop out. I think you're right that maybe the dial should be turned up on the amount of DNA that is really, really native to these tools.
--:-- Dane Knecht: Yeah, I think it's great for them as well. You see these schools like Waterloo and Northeastern with these co-op programs. From what we've seen, people that get that type of real work experience are some of our best employees many years in and go on to do great things.
--:-- Sarah Guo: It is interesting or encouraging that instead of it being, "Here's a master plan, we're going to map out every department and sub department at Cloudflare and re-engineer the workflows," it is instead a strategy of: assume people are rational about their tokens if given information about their usage, hire a bunch of interns, assume high agency people are going to shift those workflows to something more intelligent over time, and then brute force and just try things.
--:-- Dane Knecht: Early on, we had an email alias called Agents at Cloudflare, back in January of this year, where we just told people, "You're curious, can I use AI for this? Email in your jobs to be done." And that email would reply back to the skill file. For a while, people thought it was all AI and automated. It was actually a bunch of interns helping people write skill files. But that let us get to see, in a way that's not hiring a consulting firm to catalog every single thing to be done, people recognizing, "Hey, this seems harder than it needs to be. I wonder if an agent can help me here."
--:-- Sarah Guo: Is there anything else about the last year that's changed beyond the intern level? Your hiring philosophy, what you look for in people to bring on?
--:-- Dane Knecht: One of the biggest things we've always looked for is curiosity. If people aren't using AI at home in their personal life, that's a pretty big red flag. How can you not be embracing AI if you have a level of curiosity? So I think doubling down on characteristics like drive, curiosity, and empathy plays even better for this next set of people.
--:-- Sarah Guo: I am an alpha user of all products and technology forever. But I think the answer is fear and skepticism. So implicit in this claim about curiosity, including experimentation with frontier tools, that needs to be a core principle for people who work at Cloudflare.
--:-- Dane Knecht: Yeah. A lot of things we're doing, we're inventing new ways of doing things. The scale that we operate at for the number of sites behind us and the amount of free services we give away, it's just not possible with off-the-shelf technology. So you need people that can come in and literally invent new things. And that starts with curiosity.
--:-- Sarah Guo: I have a couple of questions for you to close out, mainly about security and how to do that in a new way, both at Cloudflare and in the broader ecosystem. What do you think is the process by which, if half the engineering team is going to go work on security and fix 70 years of vulnerability, how do you attack that problem internally? Assuming not all software is perfect, even amazing production, internet scale software.
--:-- Dane Knecht: Today we have one red team. I think by the end of the year, next year, we will probably have four or five red teams. Break people out into groups that are being more adversarial, actually going out and actively trying to find vulnerabilities.
--:-- Sarah Guo: Why is that the approach instead of, "We're finally going to get our patching systems right, our processes right"?
--:-- Dane Knecht: Processes can always be better. We have a volume process. We have a patching process. Are they perfect? No. But the best way I've found for those things to get better is that out of crisis comes how you get those things fixed. When the volumes get too big for the engineering team to just do them using their normal processes, engineers are inherently lazy in a good way. They will automate away those things as they need to, as they realize there's no other way to do it. So I think the focus needs to be on the discovery side. People will do the right thing and figure out how to patch it in a scalable way over time.
--:-- Sarah Guo: Do you express a philosophy on prioritization of this versus shipping new features? My understanding is it's not as if we didn't have a backlog of vulnerabilities in every large piece of software to go fix. It was just whether or not that was a priority for engineering teams previously.
--:-- Dane Knecht: I think you need to figure out how to do both. It might come at the expense of cost optimization or other things. But companies, if you're not shipping, you're dying. That's how we think about it. So it's not going to be a freeze in order to do this. No, absolutely not. You need to be able to continue building and shipping new things, but you need to make sure you're doing it securely and patching and fixing bugs. If we do it right, we'll actually be able to do them both faster with AI. While AI has become the tool causing this security apocalypse, it is also the tool that can help us solve it faster. It's on both sides of it.
--:-- Sarah Guo: Where do you fall in this debate on the role of open and closed models on the cyber front? The broad argument is that defensive and offensive cyber capabilities are parallel in the same model, despite safety and guardrails being built in. So you can't have open defensive models without them also being offensive. Then the counter-argument is the concern around only having security capabilities in a set of frontier closed models. How are you going to release them? You can't possibly get them out to the distributed set of actors that need to defend. Did I characterize that correctly?
--:-- Dane Knecht: Yeah. I think over time it all has to be open because everyone's going to get access to it anyway. The bad guys are going to find a way to get it. The top companies will have a way of getting it as well. So I think you're just excluding a mass population that doesn't have the access that probably needs it.
--:-- Sarah Guo: Final question. Cloudflare is very mission-oriented and carries the weight of internet resilience on its back. What about all of the people who can't afford to have four red teams, or never had a red team to begin with, that run important systems? How do they protect themselves?
--:-- Dane Knecht: I would say put your sites behind Cloudflare. Put your infrastructure behind Cloudflare. Build on Cloudflare. When major vulnerabilities come out, like the React one last year, we don't just give it to our paid customers who have the advanced firewall and WAF capabilities. We give it to everyone. We view those kinds of things as part of the utility we offer. We want to provide that, just like we want to provide performance for everyone. Before Cloudflare started, there were probably 3,000 sites in the world that had a large-scale CDN to cache their stuff at the edge. Now there are hundreds of millions of sites that do. Cloudflare has always viewed our goals as democratizing security and performance for everyone.
--:-- Sarah Guo: Awesome. Thanks so much for doing this, Dane. And you guys heard it first. We have the agent kitties and the volkpocalypse. Am I pronouncing that right?
--:-- Sarah Guo: But it's resolvable. All right. Thanks so much, guys.
--:-- Dane Knecht: Thanks.
--:-- Sarah Guo: Find us on Twitter at NoPriorsPod. Subscribe to our YouTube channel if you want to see our faces. Follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week. And sign up for emails or find transcripts for every episode at no-priors.com.
