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Transcript

Cold Open

Since 2022, the future of software is in question. This is from the investor community but also from customers. It is a very pivotal moment on the software stack. Then you look at the software stack and you ask, "What is the one thing that will always be there?" How many companies today have 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 are there only single-digit companies with more than $10 billion in revenue? Because platforms are rare.

Platforms are rare. Speed matters. When technology transitions happen, are you building as fast as you can? Are you learning from that technology shift? Whether it's the internet age, the AI age, or mobile, are you pivoting fast?

You just have to stay ahead of that game. If you fall behind, investors or customers will always ask you that question: "What is the future of your company?"

CJ Desai Introduction

Welcome to the very first live recording of the No Priors podcast with host Sarah Guo and MongoDB president and CEO CJ Desai. Hey everyone, I am so happy to be here with you guys and my longtime friend CJ. I know you have had a great day of announcements and learnings here at the conference, but I am personally really excited to have the opportunity to zoom out with CJ to talk about the future of software, what is 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 and became CEO of MongoDB recently. I feel like the one question that we were just talking about that every investor asks you, and that everyone in the technology ecosystem has in the back of their mind, is: "What is the value of software when you can generate a bunch of software?" I would love to just get your thoughts on this.

The AI Stack and the Future of Software

That is a very spicy question to start with. I like it.

I am making sure everybody is awake.

Yeah. Yeah.

First, thank you for doing No Priors live for the first time. It is amazing, and we have a really good crowd here, so it is always exciting.

When you think about technology transitions in software, whether you look at the internet age or mainframe all the way to AI, you have to really think through what the moat is. Whichever applications you create, SaaS applications were created in the late '90s. Salesforce had its 25th anniversary recently, so SaaS has been around for at least 25 years from a transition perspective. Now, with AI, the question is, in general, what is the future of software, what is the stack, and do you really have a moat as a company or not? There are folks who will say, "My moat is I have a great customer relationship," or "My channel is amazing, and that is my moat as I disrupt myself within." But from my standpoint, speed matters.

Speed matters. So when technology transitions happen, are you building as fast as you can, and then are you learning from that technology shift?

Whether it is the internet age, AI age, or mobile, back in the early 2010s when Meta made the pivot towards mobile, are you pivoting fast? If you pivot fast to leverage the technology, whatever platform shifts are happening, I think it is fine. It is 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?" And that is something you have to be on the leading edge. Not every bet will work.

But from my standpoint, the idea of just going on the extreme terminal value being zero for some of the software is overblown. We will figure this out together.

Why Platforms, Not Products, Are Sticky

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 is 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 "customer stickiness" or "distribution as the moat" feels very abstract. Can you just talk a little bit about how important, for example, ServiceNow is to its customers and why you think about that?

One of the things is that platforms are sticky; products are not.

Okay.

So, no matter which software company you create today in the age of AI, or you created in the past, products can be replaced. My hiring manager at ServiceNow, Frank Slutman, used to say, "Tools are for fools," meaning if you say this is a software tool, that is never a good sign. That is why he used to say that tools are for fools. So, one, products can be replaced because that is a fast-moving market. Software is a disruptive market, so you want to make sure that you have a platform that you are positioning to the customer, whether it is a builder here in San Francisco creating a brand-new company for a use case, all the way to a very large company selling to a large bank. So, one, 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." Platforms are sticky because it is a thoughtful decision from a customer's perspective. The second thing is that this is actually not the general advice of many people in the startup and VC community, so I want to talk about this a little bit and then get to your second point. You know, a lot of people talk about having a wedge. For ServiceNow, the service desk would have been considered the wedge. Is that not the right, is that 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, a healthcare company, or a manufacturing company and 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 is great, that is your entry point. But then the entry that was easy for you to get in, if it was disruptive, an exit would be in a similar way easy because they have not built things around you. So that is the main part. Okay, today it will work for your maybe 0 to $100 million, 0 to 10, 10 to $100 million, whatever steps you want to go in, but it gets harder and harder to set up from $100 million to $1 billion, $1 billion to $5 billion, and then $10 billion plus. I mean, how many companies today have more than $10 billion in software, $10 billion in just pure-play software revenue?

How many companies are there? It is 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 are there only single-digit companies with more than $10 billion in revenue? Because platforms are rare.

Platforms are rare, and platforms are rare. So, one, your dream or aspiration as a software company should be that you become a platform. 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 is truly sticky from a technology perspective. Then, what I would argue further is all the integrations that your customer has to do with their existing systems, because remember, if you go to a large bank, banks have been around for some of them 100-plus years. You go to a large insurance company, they have 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 is where the TAM is.

And if that is where the TAM is, and you go there, and if it is just a product, eventually you are going to max out, and then you will have to add multiple things. So, if you are a platform, you are sticky, products work with each other, and then those products work with all the systems you have. I will 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. I said, "Wow, CJ, how many applications have you built on MongoDB?"

They say, "Very critical and that matter." I said, "How many?" And finally, the CTO tells me in London, "30." I said, "Wow, okay, that is great. 300 applications built on MongoDB." I said, "CJ, don't worry. Thank you for coming to London."

"We are not going anywhere." I said, "Can I just ask, what is the denominator? I understand the numerator is 300." He said, "9,000." I said, "9,000, that is a great opportunity for MongoDB." So he said, "I am not going anywhere."

"I am not going." So that is 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, buyers, and investors now have is that those 9,000 applications, with low-code 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 is your take on this? And that is the way that this bank or whoever it is as a customer is going to get exactly what they want, and they are not going to be horizontal, more standardized, or even vertical applications anymore.

Vibe Coding and the Threat of On-Demand Apps

But if you are trying to sell, banks have huge budgets for technology, right? So, okay, you used a low-code platform, ABC, you created an app, great. So your app velocity has increased. If you used MongoDB, it accelerated. Just kidding. 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." 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 an on-prem, truly sandboxed, or a better way to say it, an air-gapped network. I mean, these are enterprise-class things that you need where the TAM is.

Right.

And so that is what could hold you up. Is this truly an enterprise-class application that you can take to a healthcare company or a public sector federal customer and do that? So yes, low-code will allow you to create an app fast. You have a great use case. You have some disruption in mind. That is 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 and lead in a minute, but having worked at these platform companies that are incumbents, ServiceNow and Cloudflare, 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?

Paths to Success for Software Vendor Incumbents

Wow. What would I do if I was there? So recently at Cloudflare, I would say the TAM for these platforms still exists, and the TAM is still large. So that is a good thing because if you feel like your TAM is decreasing or all of a sudden not relevant anymore, that is an issue.

But whether it is MongoDB or anybody here who is working on their company, I would say you really, really need to understand what that moat is that you have, and you need to protect that moat or maybe strengthen that moat even more using AI. Whatever that moat is. Okay. If the moat is truly you are the platform, you already have integrated with 50 different systems in that large healthcare company, great. Why can't 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 a re-acceleration of growth? That AI is really helping us innovate more and sell more, because if you cannot innovate more but you are not selling more, then you have potential issues, no matter who you are, any company. I am just making a generic comment, but can you innovate more? Can you disrupt within? And can you sell more? That is what, if I am an investor, and we speak to investors all the time, that is what they are looking for. Will AI re-accelerate this company's growth? And unless you show re-acceleration, they are going to say, "Okay, maybe I am neutral," or in some extreme examples, "I am a bear."

How CJ Chose MongoDB

When you were at ServiceNow, 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 called you about several of them. There has actually been this big shift of dollars in the investor community. I am really thinking about public markets, but also private markets, from business software to essentially AI infrastructure, the model layer, and maybe hyperscalers, and hyperscalers, 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 are pretty committed to being a platform. So be a platform.

It is absolutely true that I had choices, and choices are always hard. Or I could have stayed at Cloudflare. Cloudflare is a great company, and I could have stayed at Cloudflare. So, from my perspective, the first thing I look for is: Is there a durable TAM? I started my career out of college with Oracle Corporation and understood how they scaled 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. I learned a lot on how they really thought about the database platform, then the middleware, then the application layer on top of it, and so on. So, with Cloudflare, having an understanding of the database market, large TAM, that is great. And then MongoDB also has a large TAM. So that is the sequencing between Cloudflare and MongoDB. Second, when I truly talked to many, many customers and did my own diligence on MongoDB, one of the surprises I had was mission-critical apps, whether it is an e-commerce app for a retailer, or a commercial banking app, or a healthcare app, or an insurance claims processing app. These are very critical apps. The 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, created in 2007, so it has been only about 18 years. So there is a large TAM that could be disrupted, whether you believe the database market has been around 50 years or 60 years, and MongoDB is truly the only disruptive force. Then, the second thing I learned by speaking to some of the companies here in the San Francisco area was that some of the digital natives around the 2010-2015 timeframe, and some of the now AI natives that I spoke to, were building on top of MongoDB. I was like, "Wow, okay, so there is something." And when the founders created the company, they did not know that this was almost accidental that it would be full of unstructured data, and you would want very high velocity, and you would need to be able to search on this, which is what AI applications need. AI applications just have messy data, and MongoDB is perfect for that. So I said, "Okay, cloud transition is going on." It is still going on. When I speak to Fortune 500s, 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 is one. Second, the AI transition has just started. So if cloud started with AWS, we are almost approaching the 20th year, and it is still going on. AI will still go on, and this is a layer you must have. That is it. So, TAM, must-have layer, no risk of disruption.

I think it is actually a really interesting observation that in this clearly core and durable and very, very large market, the number of pervasive disruptive technologies is very few over many decades. There is more to do with that starting point. The previous CEO, Dave, a wonderful human being, told me that, "CJ, you know, there have been many attempts made by many folks to create the next version of the database and this and that, or the next disruptive database. Nobody has passed $1 billion, and definitely nobody has passed $2 billion, and MongoDB did that."

So there is something special there.

Debunking the SaaS Bear Thesis

When you think about the investor focus on the model layer versus the application layer, or the anxiety they have, they are anxious about the SaaS applications. They are anxious about data infrastructure because it feels like the way you build applications is still evolving very quickly.

Yep.

And tell me if you disagree with any of these assumptions. And then they are anxious about the AI-native companies because they are worried that all the value ends up in the models. So I just feel like it is a very anxious investor environment overall.

That is the bear thesis, right?

That is the bear thesis, but I think it is like the dominant thesis right now. The dominant thesis. Okay.

Well, you know, change my mind on the assumptions. What do you feel more confident on in terms of ways in which applications will be valuable in the future? Just even speaking since 2022, I think that is probably a very pivotal moment with ChatGPT in the fall. Since 2022, now we are three-plus years into that journey. I can tell you, I have never seen this because it has been pretty static for a while.

The future of software is in question.

It is definitely in question, and this is from the investor community, but also customers who are asking, "Hey, should I use X or should I use Y?" So, it is definitely a very pivotal moment on the software stack. Then you look at the software stack and you say, "Okay, what is the one thing that will always be there?" LLMs will be there for the software stack for the foreseeable future when you are truly building AI applications that rely on that stack. You have even seen a lot of innovations. You look at XAI, which came from nowhere, and how well they are doing overall. But that stack will be there in the agentic software framework. So that is 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 is the second one.

Everything else that is around that is going to evolve, and you better show true value on whether you use the platform analogy or whatever. Whether it is the top layer of the stack where you really understand the use case for the insurance industry and you are building an AI-native company for the insurance industry. The insurance industry has a multitude of use cases.

You say, "Okay, please move from old SaaS X to new Y. 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. You have startup and individual developer customers all the way to Fortune 10.

Fortune 500 Perspectives on AI Value

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 AI value and what they are excited about or skeptical about now?

So, I would say I feel it is a total failure of a week if I do not speak to at least 10 customers a week. That requires a lot of prep, a lot of follow-up, but it is usually at least 10.

Okay. And so I am constantly getting these data points and trying to do pattern matching on what is 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 copilots.

It is unclear how much value they got out of it. They are 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, is very, very positive. 2024 and 2025 was a breakthrough year from my perspective on coding assistance, and that is still going on. I get very positive feedback from customers: "Hey, I am using this particular coding assistant or this one, and it has improved the innovation velocity, security, whatever I am looking at." And then people are still tinkering around customer support. You know, on customer support, they are like, "Okay, truly, if I am a large telco or a large healthcare company, can that fully be done on this AI-native company that does customer support?" Not there yet. They are going after initial use cases, and that is 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?

Can AI Native Startups Replace Systems of Record?

So I have a system of record on one of the companies for customer support, and we can say Salesforce.

Yes.

Um, 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 or? 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 top of the system of record, or can you replace the whole thing?" 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 is when you pay me the money." That is a conversation I will have every single day.

That is a very surprising attitude, actually. I mean, I think it is risk-taking, and the value that you are asking for is much higher, but you are showing openness to a lot of pain or 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, do you think that is feasible? That other people will do that too? I mean, absolutely. If you are, our CIO here is in the audience, Deepa. 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 is for go-to-market, sales, marketing, whatever the case might be, I said, "This is how I think about it: If this allows us to hire fewer people, makes our people more efficient, then we will use that budget. And I want to be an AI-first organization on behalf of MongoDB to say we are transforming our business, not just making it productive. Productive is okay, but we are transforming our business using AI."

I think that is really interesting because a lot of the conventional wisdom would be that the system of record is so embedded that you are going to come in with a wedge or a layer on top. And that is different from what you are 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 is correct. But I actually think, coming full circle, that is a very interesting opportunity for 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 is messy. It has got to be something. It might not be Oracle anymore.

Yeah. I was talking to a European retailer the day before yesterday at NRF in New York. They said they tried a bunch of systems of record for ERP, expensive, failed implementations, lots and lots of issues on supply chain all the way to financials, and decided they are going to invest in just building it themselves. And they are building that on MongoDB. And I mean, that is a great use case. And I am like, "Okay, you had me at hello," to do that. But if these kinds of organizations are going to transform within or disrupt within, I asked Deepa, our CIO, the same question: "Are there things that we can build ourselves to disrupt within on MongoDB?"

So that is 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 first and foremost as an extraordinary product person, of course, as a CEO. But I do think you talk a lot more about business strategy, and have for the decade I've known you, than many product people. When did you start thinking about that as a product and engineering person? Because when you are talking about defensibility, moats, like how people buy you, and I don't know, that is a lot of business orientation for somebody who is also thinking about the product itself. I think it was our CEO at the time, John Thompson, at Symantec, and this was early 2005ish timeframe. 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, it made a huge impression on me. And how was it higher than other people's? Because I think everybody would be like, "Oh, I'm going to be a high-quality product director."

The Importance of Customer Relationships

Yeah. What he basically taught me, Sarah, was, "Hey, when you speak to customers, not only do you ask them how we can serve you better, but ask them, 'What other problems do they have? What pain points do they have?'" 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 product person. One of the best pieces of advice he gave me: You cannot be a great product 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 will say, "Hey, this is what another retailer at NRF in New York on Monday or Sunday I met him, and he is a CTO reporting to the CEO." I said, "Oh, so you use MongoDB for your e-commerce application?" He said, "Yep, we are very happy. E-commerce is 20% of our revenue." I said, "Great. Do you know that you are not using our search? Do you know we also have vector search?" He is like, "Oh, I didn't know that. Does my team know that?" And we are following up with him. But this kind of having that customer intimacy makes you a much better product person. I would say any product person who thinks, "As you build, they will come," does not happen. And that gives you the orientation of how 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 insight on how sales teams show up, how we price the customers, if something bad happens, an outage happens, or something, how we show up during the crisis. Those are the things that have really made me a 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 do not make are from a single product to multiple products, or maybe it is because they were never platforms to begin with. But let's say, to multi-product. And then also, it is technology transitions, right? Like Atlas to be great and dominant, but it was a question at some point. I don't know if we are allowed to say that. And many companies struggle through the cloud transition. They will now have to address the AI transition. What do you think differentiates a product and engineering organization that does it versus fails?

Managing Through Massive Technology Transitions

Yeah, you get comfortable. And I still remember, we were early on at ServiceNow on AI. And when I would speak to our engineering team, they were 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 in. 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 am going to date myself. Think about Nokia handsets. They were doing really, really well. Even if you think about Blackberry, do you know that when the iPhone actually launched, I think, three or five quarters after the iPhone, Blackberry was still selling a lot and was not being disrupted until it got really disrupted? So these transitions, you know, are more of a change management thing. And that is when you achieve the step function, 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 is when it happens. Otherwise, you are on the bear thesis. I am not sure. And the only way you prove investors wrong on the bear thesis, because sometimes they do not get it right, is by re-accelerating and showing that, "Hey, now we are back." We are out of time here, but I think this is such an interesting question of, can the incumbents get AI right or not? And one of the dynamics that is worrying people is one of the ways you sell as a very large incumbent is 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, let's say, a bunch of pricing shenanigans to make the number. And I look at this and I think it is 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 their north star, and you also need some guardrails for intellectual honesty in the organization between what is working for the 10 customers you talk to every week and the street.

Right. I agree. And the only thing I would say is that is 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 are not allowed to say that.

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, and we have hundreds of them. But that is not because, then I give them X percent of this is how I think about AI-native companies, then they are like, "You can optimize for that."

Yeah. And then you go into 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 is $100 million ARR or $1 billion ARR, pick one. There are like 10 companies like that today."

Mhm.

Today, right? There are not that many companies. And if there are not that many successful companies, they won't have a lot of data. Some of them who have data do use MongoDB, right? So, from my standpoint, this will be an end, not an or. That when the AI wave really takes off, that will of course add, but our core data platform and core business is still growing. That is the answer I gave because that was the truth.

Thank you so much for doing this.

Yes.

And thank you very much. I really appreciate it. Thank you. Find us on Twitter at @nopriospod. 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-priers.com.