The Exchanges

Q think, you know, coming full circle, that's a very interesting opportunity for, you know, MongoDB in particular, because the, like 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.

A I was talking to a European retailer the day before yesterday at NRF in New York, and they said, they tried a bunch of systems of record for ERP, Expensive failed implementations, lots, 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's a great use case, and I'm like, okay, you had me at hello. And, ah, ah, to do that, but if these kind of organizations are going to transforms within or disrupt within, I asked, ah, Deepa, our CIO, the same question, that are there things that we can build ourselves to disrupt within on MongoDB? So that's the story and the compelling value we can articulate also to our customers.

AI assessment note: “decided they are going to invest in just building it themselves, and they are building that on MongoDB.”

Q Um, and having built systems of record yourself, you think that's feasible that other people will do that too?

A 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 okay, but we are transforming our business using AI.

AI assessment note: “I mean, absolutely. If you are, you know, our CIO here is”

Q to talk about the decision to join Mongo and lead it in a minute, but, um, having worked at these platform companies that are incumbent ServiceNow and CloudFair and such, um, what would you do if you were them or any other large enterprise software vendor today? What do you think is the, the path to success five or 10 years from now that the investor community does not understand?

A Wow. What would I do if I was there? So 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 TAM 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 moat is, ok? 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 a hundred 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 re-acceleration of growth that AI is really helping us innovate more and sell more. Because if you can't, 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, 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 you know, 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 grow…

AI assessment note: “You really, really need to understand what is that moat you have, and you need to protect that moat”

Q At some point. I don't know if I'm allowed to say that, right? And, you know, many companies struggled through the Cloud transition will now have to address the AI transition. Um, what do you think differentiates like a product and engineering organization that does it versus fails?

A 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 a more of a change management thing, and that's when you achieve the staff function to say, like MongoDB did the Atlas transition or Multicloud 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 righ…

AI assessment note: “So I think it is more of a change management thing”

Q Well, you know, change my mind on any of the assumptions. What do you feel like more confident on, you know, in terms of, um, ways in which applications will be valuable in the future?

A Just even speaking to since twenty-twenty-two, I think that's probably a very pivotal moment with the ChatGPT in the fall. Since twenty-twenty-two, now we are three years plus in the journey. I can, 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 have seen a lot of innovations in, you look at XAI came from nowhere, kind of, and how well they are 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'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 y…

AI assessment note: “the top layer of the stack, where you really understand use case”

Q 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?

A 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, right? So that's, that's the main part that, okay, today it will work for your maybe zero to a hundred million, uh, zero to 10, 10 to a hundred, whatever steps you want to go in, but it gets harder and harder set up from hundred to billion. Billion to five billion, and then ten billion plus. I mean, how many companies today that are there that are more than ten billion in software, ten billion in just pure play software revenue? How many companies are there? It's single digits, ok? 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 ten billion in revenue? Because?

AI assessment note: “you need an initial use case and that initial use case has to be”