No Priors: Artificial Intelligence | Technology | Startups - No Priors Live: Building Durable Software in the AI Age with MongoDB President & CEO CJ Desai

Episode Date: January 22, 2026

Why are there only a handful of companies in the world with over $10 billion in pure-play software revenue? CJ Desai believes the reason is that products are replaceable, but platforms are forever. For No Priors’ very first live from MongoDB.local SF, Sarah Guo is joined by CJ Desai, CEO and President of software developer MongoDB, to discuss the shifting landscape of enterprise software. CJ discusses whether AI will erode the value of software, and what truly constitutes a “moat” in the age of generative AI. CJ also talks about why AI adoption with Fortune 500-sized companies is still lagging, the importance of customer relationships, and why the “bear thesis” on SaaS may be overblown.  Sign up for new podcasts every week. Email feedback to [e-mail] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @cj_mongodb | @MongoDB Chapters: 00:00 – Cold Open 00:58 – CJ Desai Introduction 01:38 – The AI Stack and the Future of Software 04:18 – Why Platforms, Not Products, Are Sticky 09:59 – Vibe Coding and the Threat of On-Demand Apps 12:15 – Paths to Success for Software Vendor Incumbents 14:24 – How CJ Chose MongoDB 18:55 – Debunking the SaaS Bear Thesis 22:07 – Fortune 500 Perspectives on AI Value 24:24 – Can AI Native Startups Replace Systems of Record? 28:10 – The Importance of Customer Relationships 31:46 – Managing Through Massive Technology Transitions 36:37 – Conclusion

Since 2022, the future of software is in question. This is from the investor community, but also customers. It is a very pivotal moment on the software stack. And then you look at the software stack and you say, okay, what is the one thing that will always be there? How many companies today that are there that are more than 10 billion in just pure play software revenue?

It's single digits. Why is that? The software industry has been around for a long time, created by many, many smart people like yourself. Why is it only single digit? Single-digit companies are more than 10 billion in real. Platforms are rare. Platforms are there.

Speed matters. When technology transitions happen, are you building as fast as you can? And then are you learning on the technology shift, whether it's the Internet age or AI age or mobile? Are you pivoting fast? It's just that you have to stay ahead of that game. If you fall behind that game, investors or customers will always ask you that question, what is the future of your company? to the very first live recording of the No Pryor's podcast with host, Sarah Guo, and MongoDB,

president and CEO, C.J. Desai. Hey, everyone. I am so happy to be here with you guys and my longtime friend, C.J. I know you guys have had a great day of announcements and learnings here at the conference, but I'm really excited personally and to have the opportunity to zoom out with C.J. to talk about the future of software. what's happening in SaaS and where the value is going to be. These are important questions to me in my day job as a venture investor. So, CJ, you have worked at these platform enterprise software and infrastructure companies, became CEO of MongoDB recently.

I feel like the one question that we were just talking about, that every investor asks you, and then everybody in the technology ecosystem has the back of their mind, is what is the value of software when you can generate a bunch of software? And so I'd love to just get your thoughts on this. It's a very spicy question to start with. I like it. I'm making sure everybody's awake. Yeah.

Yeah. First, thank you for doing No Prior's Live for the first time. It's Maiden, and we have a really good crowd here, so it's always exciting. You know, when you think about technology transition, software, whether you look at Internet age or mainframe all the way to AI, you have to really think through. you have to really think through what is the mode here, right? Which of our applications you create, you know, SaaS applications got created late 90s, right? Late 90s.

I think Salesforce had the 25 years anniversary recently. And so SaaS has been around for at least 25 years from a transition perspective. And now with AI, the question is just in general, what is the future of software, what's the stack, and do you really have a moat as a company or not? There are folks who will say, hey, my moat is, I have a great customer relationship

or my channel is amazing and that's my moat as I disrupt myself within. But from my standpoint, speed matters, right? Speed matters. So when technology transitions happen, are you building as fast as you can and then are you learning on the technology shift, whether it's the Internet age or AI age or mobile back in early 2010

when MEDA made the pivot towards mobile, are you pivoting fast? And if you pivot fast to leverage the technology, whatever the platform shifts are happening, I think it is fine. It's just that you have to stay ahead of that game. If you fall behind that game, investors or customers,

We'll always ask you that question, what is the future of your company? And that is something you have to be on the leading edge. Not every bet will work. But from my standpoint, just going on the extreme terminal value being zero for some of the software, they are overblown. And we'll figure this out together. Part of your career, you were leading product at ServiceNow. It is one of the most durable enterprise software companies.

Or so everyone assumed until relatively recently, and now this question's up for debate, I think for a lot of people within an engineering mindset who think about buying developer tools or using developer infrastructure, the word like customer stickiness or distribution as the moat, it feels very abstract. Can you just talk a little bit about how important,

you know, service now as an example, is to its customers and what you think about that? One of the things is platforms are sticky, products are not. Okay. So no matter with software company you create today in the age of AI, or you create it in the past, products can be replaced. My hiring manager at ServiceNow, Frank Slutman, used to say tools are for fools. As in if you say, this is a software tool, that's never a good sign.

And that's why he used to say that tools are for fools. So one is products can be replaced because that's a fast software is a disruptive market. So you want to make sure that your platform that you are positioning to the customer, whether it's a builder here in San Francisco that is creating a brand new company for a use case, all the way to a very large company that is selling to, say, a large bank. So one is, when you position yourself as a platform, maybe that increases your sales cycle versus selling, hey, you are using this, now you can use this, go ahead and replace it, right? So platforms are sticky because it's a thoughtful decision from a customer's perspective. The second thing that is actually not the general advice of many people in the startup and VC community.

So I want to talk about this little bit. And then I want to get to your second point. Yeah. You know, a lot of people talk about having, like, a wedge, right? And for ServiceNow, you know, IT service desk would have been considered the wedge. Is that not the right? Is that like a wrong retelling of history here? I mean, you need an initial use case, and that initial use case has to be a killer use case.

Because if you go in front of a large bank or a healthcare company or a manufacturing company, say you are building something here with this great audience we have, you can say, okay, this is a disruptive way to think of a legal use case or a finance use case or a help desk use case, that's great, that's your entry point. But then the entry that was easy for you to get in if it was disruptive, exit would be in a similar way, easy because they have not built things around you.

So that's the main part that, okay, today it will work for your maybe zero to $200 million, 0 to 10, 10 to 100, whatever steps you want to go in. But it gets harder and harder set up from 100 to billion, billion to 5 billion, and then 10 billion plus. I mean, how many companies today that are there that are more than 10 billion in software, 10 billion in just pureplace software revenue,

how many companies are there? It's single digits. Okay? Why is that? The software industry has been around for a long time, created by many, many smart people like yourselves, Why is it only single-digit companies are more than 10 billion in revenue? Because platforms are rare.

Platforms are there, and platforms are rare. So one is your dream or aspiration as a software company should that you become a platform. And once you are a platform, that means you have n-equals at least two. You have two-plus products being used by your customers from whatever you are offering. They all work in unison with each other. So it's sticky, truly from a technology perspective. And then what I would argue further, all the integrations that your customer has to do with their existing systems. Because remember, if you go to a large bank, bank has been around for some of them 100 plus years.

You go to a large insurance company, they've been around for 100 plus years. If you go to a healthcare company, same thing. You look at Fortune 10, Fortune 100, Fortune 500. That's where the TAM is. And if that's where the time is, and you go there, and if it is just a product, eventually you're going to max out, and then you will have to add multiple things. So if you're a platform, you're sticky, products work with each other, and then those products work with all the systems you have. And I'll just make it very specific. Speaking to a bank, on behalf of MongoDB, they run their commercial banking applications on top of MongoDB.

They have built a lot of other integrations. they have done all the security checks, governance, all of that stuff. And I said, wow, gee, how many applications you have built on MongoDB? They said, very critical, and that matter. I said, how many? And finally, the CTO tells me in London, 300. I said, wow, okay, that's great. 300 applications built on MongoDB.

I said, C.J, don't worry. Thank you for coming to London. We are not going anywhere. I said, can I just ask you what's the denominator? I understand the numerator is 300. he said 9,000. I said, 9,000, that's a great opportunity for MongoDB. And he said, I'm not going anywhere.

I'm not going anywhere. So that's when the more they use, the more sticky we get, and then we are in the fabric of their infrastructure. So the other premise that some builders and buyers and investors now have is those 9,000 applications, with vibe coding being possible or engineering and some code generation, some set of those are just going to be made on demand

or in niche ways by every company. What's your take on this? And that's the way that this bank or whoever it is as a customer is going to get exactly what they want and they're not going to be horizontal, more standardized or even vertical applications anymore. Yeah. But if you are trying to sell banks have huge budget for technology, right?

So, okay, you used a vibe coding platform, ABNC, you've created an app, great. So your app velocity has increased. If you used MongoDB, it accelerated. Just kidding. Okay. But your app velocity is high, got it. But you still need that go-to-market channel. How are you going to approach the bank?

And then what is your true disruptive way? And then the bank will ask you, hey, we talk to regulators a lot more than we speak to our customers and vendors. Stuff. Yeah. Will this work? Will it pass our regulatory test?

We need resiliency. Oh, what do you mean you have just built in AWS? It doesn't work in GCP. I need multi-cloud resiliency. Oh, I really need for this banking application in on-prem, truly sandboxed or a better way to say, It is an air gap network. I mean, these are like enterprise class things that you need where the TAM is.

Right? And so that's what could hold you up. That is this truly an enterprise class application that you can go to a healthcare company or a public sector federal customer and do that. So, yes, wipecoding will allow you to create an app fast. You have a great use case. You have some disruption in mind. That's excellent.

But then there is a lot of things that you need from a go-to-market perspective. to be able to break in, pass all their checks, governance, security audits, and things like that. You are, and I want to talk about the decision to join Mongo and lead it in a minute, but having worked at these platform companies that are incumbents, service now and cloud fare and such, what would you do if you were them

or any other large enterprise software vendor today? What do you think is the path to success five or ten years from now that the investor community does not understand? Wow. What would I do, I was there recently at Cloudflare? I would say the TAM for these platforms still exist, and the TAM is still large. So that's a good thing, because if you feel like your time is decreasing or all of a sudden not relevant anymore, that's an issue. But whether it's MongoDB or anybody here who are working on their company, so I would say, you,

really, really need to understand what is that moat you have and you need to protect that moat or maybe strengthen that moat even more using AI. Whatever that mode is, okay? If the mode is truly, you are the platform, you already have integrated with 50 different systems in that large healthcare company, great. Why can you now integrate with 100 more companies in there? Why can't you create additional products for additional use cases really fast using AI and continue to show, I want to say, reacceleration of growth,

that AI is really helping us innovate more and sell more. Because if you say you're innovating more, but you're not selling more, then you have potentially issues, no matter who you are, any company. I'm just saying it's a generic comment. But can you innovate more? Can you disrupt within and can you sell more? That's what if I'm an investor, and we speak to investors all the time, that's what they are looking for, that, hey, would this, will AI re-accelerate this company's growth? And unless you show re-acceleration, they are going to say, okay, maybe I'm neutral or in some extreme examples, I'm a bear.

When you were at Service Now, you got a lot of calls for different jobs, and at Cloudflare, you got a lot of calls from different jobs. I know because I call you about several of them. There's actually been this big shift of dollars in the investor community. I'm really thinking about public markets, but also private markets from business software to essentially AI infrastructure, right, and the model layer. And maybe hyperscalers. And hyperscalers, yes. The data and developer infrastructure layer has not been the focus of that dollar movement.

And, you know, you could have done any of these things. How did you think about what sectors would be long-term relevant? And it sounds like you're pretty committed to being platform. So be a platform. Yeah. It's absolutely true that I had choices and choices are always hard. Or I could have Cloudflare is a great company and I could have stayed at Cloudflare. So from my perspective, the first thing I look for is that is there a durable term?

Right. and I started my career out of college with Oracle Corporation and understood how they scale the database platform, truly created apps on top of it and a bunch of other things during Oracle's organic growth days before they started buying various assets. Learned a lot on how they really think about the database platform, then the middleware, then the application layer on top of it and so on.

So one with Cloudflare, having understanding of the database market, large time, that's great. And then MongoDB is also a large term. So that was the sequencing between Cloudflare and MongoDB. Second, with MongoDB, when I truly talk to, I want to say, many, many customers when I did my own diligence on MongoDB, one of the surprises I had was mission critical apps, whether it's an e-commerce app for a retailer, or whether it's a commercial banking app or a healthcare app or an insurance claims processing app, These are a very critical app.

And database industry, Oracle will celebrate its 50th in a year and a half. So it has been around for a long time, 50 years. MongoDB has been a truly disruptive force with being created in 2007. So it's been only 18-ish years. So there is a large time that could be disrupted, and whether you believe database market has been around 50 years or 60 years. And MongoDB is truly the only disruptive force. And then the second thing I learned by speaking to some of the companies here in San Francisco area

was that some of the digital natives around 2010-15 timeframe and some of now the AI natives that I spoke to were building on top of MongoDB. And I'm like, wow, okay. So there is something. And when the founders created the company, they didn't know that, hey, it was like almost accidental, that it will be full of unstructured data, and you would want very high velocity, and you will need to be able to search on this, which is what AI application. AI applications, just the data is so messy,

and MongoDB is perfect for that. So I said, okay, cloud transition is going on. It's still going on. When I speak to Fortune 500, I can tell you without hesitation, they are all still talking about I need to move X percent of apps to GCP, AWS, Azure, some combination, Alibaba, in Europe, whatever the case might be. So that's one.

But second, AI transition has just started. So if cloud started with AWS, we are in the almost approaching 20th year and it's still going on. AI will still go on and this is a layer you must have. That's it. So Tam must have layer, no risk of disruption. I think it's actually a really interesting observation that in this clearly core and durable and very, very large market, the number of like pervasive disruptive technology is very few over many decades, right? And so there's more to do with that starting point.

The previous CEO, a wonderful human being, told me that CJ, you know, that many attempts have been made by many folks to create next version of database and this and that or next disruptive database. Nobody has passed billion and definitely nobody has passed two billion. And, definitely nobody has past 2 billion and MongoDib did that. So there's something special there. When you think about the investor focus on the model layer versus the application layer or in the anxiety, they're anxious about the SaaS applications. They're anxious about data infrastructure because it feels like the way you build applications

is still evolving very quickly. Okay, yep. Tell me if you disagree with any of these assumptions. And then they're anxious about the AI-native companies because they're worried that all of the value ends up in the models. So I just feel like it's a very anxious investor environment overall.

That's the bare thesis, right? That is the bare thesis, but I think it is like the dominant thesis right now in the investor. It is the dominant thesis, okay. Well, you know, change my mind and in the assumptions. What do you feel like more confident on, you know, in terms of ways in which applications will be valuable in the future?

Just even speaking to, to since 2020. I think that's probably a very pivotal moment with the Chad GPT in the fall. Since 2022, now we are three years plus in the journey. I have never seen this because it's been pretty static for a while. The future of software is in question. It's definitely in question.

And this is from the investor community, but also customers that are asking, hey, should I use X or should I use Y and whatever, right? So definitely it is a very pivotal moment on the software stack. And then you look at the software stack and you say, okay, what is the one thing that will always be there? I mean, LLMs will be there for the software stack for foreseeable future when you are truly building AI application that rely on that stack.

and even you've seen a lot of innovations in, you look at XAI came from nowhere, kind of, and how well they're doing overall, but that stack will be there in the Agentic software framework. So that's a constant, and the data layer has to be there because you need to store data somewhere, so the data layer has to be there. So that's the second one.

Everything, you know, that is around that, that that's going to evolve and you better show true value on whether you use the platform analogy or whatever, whether it's the top layer of the stack, where you really understand use case for the insurance industry and you are building an AI native company for the insurance industry. Insurance industry has multitude of use cases. You say, okay, please move from old SaaS X to new Y, and this new Y, the speed to value is going to be this fast, and we will always be ahead. And things that you thought were not possible with the old SaaS are now possible because

of AI. So that use case focus on the top layer, besides the LLM and the data layer, will still always be critical. Mongo has startup and individual developer customers all the way to Fortune 10, almost all of them. What do you hear from the buyers and builders at the very largest companies in terms of their real perspective on like AI value and what they're excited about or skeptical about now? Yeah, so I would say I feel it's a total failure of a week if I don't speak to at least 10 customers a week. That requires a lot of prep, a lot of follow-up, but it's usually at least 10, okay? And so I'm constantly getting this data points and trying to do pattern matching on what's going on.

The first thing I would say is that when you think about Fortune 500 Global 2000 and the community there, some of them are here, it is still not moving very fast. A lot of them tried with the office productivity type co-pilots unclear how much value they got out of it. They're like, okay, this really works with my Excel or can I really do this thing or create a PowerPoint slide using natural language. the feedback is not great on the value they got. The feedback on coding assistance that kind of took off in 2024, in a meaningful way, very, very positive. 2024 and 202.

Started with GitHub copilot, then view others, all the way to Anthropic and so on. So 2025 was a breakthrough year from my perspective on the coding assistance, and that's still going on. I get very positive feedback from customers, hey, I'm using this particular coding assistant or this one, and it has improved the innovation,

velocity, security, whatever I'm looking at, and so on. And then people are still tinkering around customer support. You know that. And on customer support, they're like, okay, truly, if I'm a large, say, telco, or I'm a large healthcare company, can that fully be done on this AI-Hine? on this AI-native company that does customers?

Not there yet, right? They are going after initial use cases, and that's great in certain industries. You mean the end-to-end customer experience? End-to-end customer experience. And the question that I get from these customers, they ask me my perspective on SaaS, is that should I think about this AI-native company

and customer support as an end or an or? So I have a system of record on one of the companies for customer support. We can say Salesforce. Yes, Salesforce. And if I'm using, and I'm using, I have this disruptive company that came and said they can solve these problems, do these support cases. Should I think about that as an end or an R? And I ask them the same questions. You know, we use these systems of record, SaaS systems of record.

And when somebody comes and says, I'm like, are you a layer on the top of system of record, or you can replace the whole system? Because you will have my attention as a leader. If you say, I'm going to replace it, it's going to be cheaper, it's going to be faster, it's going to be better. And oh, by the way, I have disrupted pricing. And for the value you get, that's when you pay me the money. That's a conversation I'll have every single day.

That's a very surprising attitude, actually. I mean, I think it is risk-taking and the value. that you're asking for is much higher, but you're showing openness to, you know, a lot of pain or, you know, being willing to ignore a bunch of the sunk cost of the implementation of the systems you already have. Yes. And having built systems of record yourself,

you think that's feasible, that other people will do that too. I mean, absolutely. If you are, you know, our CIO here is in the audience, Deepa, and when we have this conversation, she gets approached by AI-Native companies daily. multiple times a day. And when she comes and asks me, how do you think about that, whether it's for go-to-market sales, marketing,

whatever the case might be, I said, this is how I think about it, that if this allows us to hire fewer people, makes our people more efficient, then we will use that budget. And I want to be AI-first organization on behalf of MongoDB to say, we are transforming our business, not making just productive. Productive is OK.

But we are transforming our business. business using AI. I think that's really interesting because a lot of the conventional wisdom would be the system of record is so embedded that you're going to come in with a wedge or a layer on top. Yeah. And that is different from what you're describing, which is I'm going to sell platform and I'm willing to buy a platform if the use case is good enough. That's correct. But I actually think, you know, coming full circle, that's a very interesting opportunity for, you know, MongoDB in particular because one of the reasons you might actually replace these systems of record in this age is you want to keep much richer information about interactions or whatever else it is in your

system of record and it's messy it's got to sit something right it might not be Oracle anymore I was talking to a European retailer day before yesterday at NRF in New York and they said they tried a bunch of systems of record for ERP expensive fail implemented organizations, lots of issues on supply chain all the way to financials, and decided they're going to invest in just building it themselves, and they are building that on Mongo TV. And I mean, that's a great use case, and I'm like, okay, you had me at hello. And to do that, but if these kind of organizations are going to transform within or disrupt within, I asked Deepa or the same question that are there things that we can

can build ourselves to disrupt within on MongoDB. So that's the story and the compelling value we can articulate also to our customers. I want to take the last couple minutes that we have together to talk a little bit about leadership, especially as a product person. I think of you, of course, as a CEO, but first and foremost, as an extraordinary product person.

I do think you talk a lot more about business strategy and have for the decade I've known you than many product people. Like, when did you start thinking about that as a product and engineering person? Because when you're talking about defensibility modes, like how people buy you. And I know that's a lot of business orientation for somebody who's also, you know, thinking about the product itself. I think it was our CEO at the time was John Thompson at Symantec. And this was early 2005-ish time frame.

And I learned a lot from him. And specifically, his bar on how you interact with customers, how you sell to them, how you serve them, how you show up in front of them, was very, very high. And through my early career as a product person, I was director of product management, I still remember, I made a huge impression on me. And how was it higher than other people's, right? Because I think everybody would be like, oh, I'm going to be a high quality product director. Yeah. What he basically taught me, Sarah, was, hey, when you speak to customers, not only you ask them how we can serve you better, but ask them, hey, what other problems they are having, what pain points they are having, and you fly there, you meet them, you have coffee with them, whatever it is, truly understand because it allows you to see around the corner. And you cannot be a great, one of the best advice he gave me, you cannot be a great products and engineering person. unless you speak to customers all the time, okay? All the time, because that will allow you to not only do a pattern match,

but see around the corner. So even when we have a platform story and I'll say, hey, this is what, this another retailer at NRF in New York on Monday or Sunday, I met him, and he's the CTO, reports to the CEO, and I said, oh, so you use MongoDB for your e-com application. He said, yep, we're very happy e-com is 20% of our revenue, you as a great. Do you know that you are not using our search? You know, we also have vector search. He's like, oh, I didn't know that. Does my team know that? And we are following up with him.

But this kind of like having that customer intimacy makes you much better of a product person. I would say any product person who thinks as you build, they will come. That does not happen. And that gives you the orientation that how do they think about deploying your product, how long will it take to deploy that product, how much value they expect. And these people, I never say that a large bank has bought, say, ServiceNow or Cloudflare. I will say it is Jeremy at this large bank who made a bet on Cloudflare, for example. So that has been for the last many, many years, that has given me a lot of fun. How do sales team show up? How do we price the customers?

If something bad happens and outage happens or something, how do we show up during the crisis? Those are the things that have really made me very, very grounded product person and understanding the go-to-market channel and the business strategy. Some of the step function jumps that a lot of SaaS and infrastructure companies don't make are from a single product to multiple products, right? Or maybe it's because they were never platforms to begin with, but let's say like to multi-product. Yeah. And then also, you know, it's technology transitions, right? Like Mongo got Atlas to be great and dominant, but it was a question at some point. I don't know if I'm allowed to say that, right?

And many companies struggled through the cloud transition will now have to address the AI transition. What do you think differentiates, like, a product and engineering organization that does it versus fails? Yeah. You get comfortable, and I still remember, we were early on ServiceNow on AI, and when I'll speak to our engineering team,

they're like, oh, this is just something that's out there, not sure. And I said, no, not leaning in is not an option. Not leaning. This is a platform, whether it matures two years from now or four years from now, we have to do that. So I think it is more of a change management thing because if you are doing something really, really well, I mean, I'm going to date myself, you think about Nokia handsets, they were doing really, really well. And even if you think about BlackBerry, do you know that, when actually iPhone launched, I think I want to say three or five quarters after now, after the iPhone, BlackBerry was still selling a lot. and was not being disrupted until it got really disrupted. So these transitions, you know, is more of a change management thing,

and that's when you achieve the staff function to say, like MongoDB did the Atlas transition or multi-cloud transition nicely, and they have to do the AI transition nicely. Fortunately, a lot of architectural advantages are there, but they still have to nail it and get the trust information from the customer. And that's when it happens. Otherwise, you are on the bare thesis that I'm not sure. And the only way you prove investors wrong on the bare thesis,

because sometimes they don't get it right, is by re-accelerating and showing that, hey, now we are back. We're on in time here, but I think there's such an interesting question of, can the incumbents get AI right or not? And one of the dynamics that I think is worrying people is one of the ways you sell, as a very large incumbent as you bundle a bunch of products together. Yes. And then you call a piece of the product that may or may not be working for customers,

cloud, or you call it AI, and you do, like, let's say a bunch of, like, pricing hijinks to, like, make the number. And I look at this, and I think it's so interesting because so many talented people work at any of these incumbents. And so my observation would be you absolutely need people who are committed to those transitions, a leader with innovation as they're like North Star, and you also need like some guardrails for intellectual honesty in the organization between what, like, what is working for the 10 customers you talk to every week and the street. Yeah, I agree. And the only

thing I would say, that's why even MongoDB published our Q3 results, I got asked this question over and over again, is this because of AI? And I said, absolutely. Not. Yes. You're not allowed to say that. Yeah, no. I said this is our core. And our core on CNBC, I said it's our core. Yes, we have AI-Native companies building on MongoDB. We have hundreds of them.

But that's not. Once then I give them X percent of, this is how I think about AI-native companies. The company can optimize for that. Yeah, yeah. And then you're going to a different cycle. And I said, yes, you know, whenever they do something at scale, because let's look at it. Like if you think about however you define success

for AI-native companies, whether it's 100 million ARR, billion ARR, pick one, there are like 10 companies like that. Today, today, right? They're not that many companies. And if they are not that many successful companies, they won't have a lot of data. Some of them, whoever data do use MongoDB, right?

So from my standpoint, this will be an end, not an or, that when AI wave really takes off, that will of course add, but our core data platform and core business is still growing. That's the answer I gave because that was the truth. Thank you so much for doing this. Yes, and thank you very much. Really appreciate it. Thank you.

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