All right, welcome to another exciting session at the Morgan Stanley TMT Conference. I'm really excited to have the management team of Couchbase. We have CEO Matt Cain. Matt, thank you for joining the conference. And then we have Chief Financial Officer Greg Henry. Greg, thank you for coming to the conference once again. Super excited to have you. I wanted to frame out this conversation to sort of kick things off. I would proffer that if you looked at growth in 2023 versus 2022, I haven't verified this, but 90% of software companies probably slowed down. You guys, I was expecting you guys to, like, sustain growth, but you actually had accelerated ARR growth this year, came in at 20%-25%. The year before that it was 23%. The year before that it was 23%. So, pretty remarkable sustained growth in the context of maybe the worst software spending environment that we've seen since GFC. So let's pick it up from there. Like, what are the factors that has allowed Couchbase to sustain growth, and what is a pretty challenging spending environment? Oh, when you say it like that, nice work. Look, appreciate you calling that out. We had our Financial Analyst Day, middle part of December, and we sort of laid out kind of the recent history of the company in three chunks. One of them was working really hard over the better part of a decade to build a foundation that we thought we could create a great software company on top of, working really hard to get this point of inflection that's really driven by Capella, and then leading to a phase of leverage, that we think we're going to take both of those and demonstrate things to the world that you haven't seen out of out of the company. So I think we've been working on improvement that have driven those results, over that time period, probably layering in different points of improvement over time depending on the year. So, you know, through the IPO, which was a couple years ago, now it was about solidifying our go-to-market execution, really getting more out of kind of the enterprise foundation, preparing for Capella. I think if you look at this year's financials, a lot of it is benefiting from that inflection point where Capella is becoming a meaningful part of our business. So I think we've been a company that has consistently taken a mid to long-term approach, but realizing that we need to build in, you know, improvement over time, and I think the financials, you know, justify that. That said, we're focused on continuing to improve, and we truly believe that we're in the very early innings of a generational market opportunity, that, you know, we committed to delivering, you know, pretty exciting growth rates and financials on a go-forward basis. So, you know, we have our eye on the prize, you know, as we go forward, but certainly take pride in the results that we've delivered over the past many years. Yeah, that makes a lot of sense. I also want to just take a step back and sort of weave in some of the themes of the earnings call last night, particularly on the product side. So you guys announced your vector search capabilities. Correct me if I'm wrong, there's a lot of companies supporting vector as a data type. Can you, and then retrieval-augmented generation, you know, I've heard that term thrown around all week at the conference, and so what is going to be Couchbase's unique play in sort of enabling this next generation of applications just more broadly? And I'd love to get your perspective on that. Yeah, Sanjit, before we get into kind of the technology that we're working so hard to add to the platform, I like to start with database companies are built to support and manage applications. So the hero of the story is the applications that we allow our large customers to build and enable. And we're talking a lot about this concept of highly personalized, interactive, what we call adaptive applications. So if you think about how you interface with your bank, or if you're booking travel, or your health care provider, the gateway between the human world and the digital one is applications. We now all have these expectations that applications are going to work for us in a unique and personalized and highly customized way, providing insights to us that we may not be asking for in a real-time basis, and how my application performs needs to be very different, you know, than Greg's application, even though for, you know, interfacing with the same company. So everything we do is in service of these mission-critical applications that our enterprise customers are working so hard to leverage internally and externally to transform their business. Now, we are the operational database that support these applications while they're running. Our job then is to layer in additional services that make those applications that much better and that much more personalized. And so the world is very excited, and rightly so, on what could be the biggest market transition and opportunity we've seen in AI. As it pertains to the database, the trick is how do we layer that in to make these applications that much more applicable and beneficial to users. So one of the examples that we like to talk about, we're very successful in e-commerce, and the extension to retail stores. And so how do you have an inventory of millions and millions of items distributed across storefronts, and yet create a personalized experience for an in-store shopper? Well, imagine if I went into a store and instead of trying to describe to an associate that's looking through inventory, start to use technology to find me, you know, something that is pertinent to me at the time. And we talked last night on the call about this example of I walk into a store and I say, I want a pair of shoes to match this outfit. I want them to be, you know, kind of funky and new. I want to pay somewhere between $100 and $200. And I actually want them to be the color of that blue car out there. I can now take a picture of that and with that additional information use AI to do vector search against that picture, but then combine it with other services that we've built into the database. Because if you think about the demand that I just put on the database, I got to look through inventory. I've got to do range-based searches for pricing. I need to do geospatial-type looks across, you know, different stores if I'm looking within a, you know, certain radius. We all can sort of feel the transformational opportunity of that additional element of AI. But in the context of Couchbase, we need to provide this with the rest of the application that if you only think about that addition, it's going to sort of render the application useless if you can't bring it to life with real inventory and real goods and credit card processing and customer information. And so what we're so excited about is the addition of vector and how it's going to allow AI-powered adaptive applications. And one of the things that's really unique about us, not just that platform approach, but we're enabling it at the edge. So, you know, another use case, we support IoT-based applications where people are industrial companies out in the middle of nowhere servicing wind turbines. Well, a lot of times they're using a mobile device to do diagnosis there. Well, imagine if I can start to inject weather patterns with different inputs and then use AI to take the diagnosis and corresponding action to the next level. There's not a predictable connection on that mobile device. And so taking the power of AI to the edge when you don't have predictable connectivity, that is completely unique to us. And when we think about the world of AI, connected homes, future health care, travel, we think so much of it is happening at the edge. And so it's really powerful to unlock, you know, potential innovation leveraging AI, but being mindful of, you know, existing technologies and data sets that are so critical. Yeah. And so to your point is like, you know, people talk a lot about Vector Search as a capability, RAG as an agent pattern. But this has to be, you know, implemented in the context of a broader set of capabilities. Without question. That's supporting an existing set of applications that's going to get modernized with these new capabilities and to do that, in an integrated approach. On top of that, enterprises a lot of people are excited about AI-based use cases. Our enterprise customers are very smart, and they're aware of what that can do. They're also aware of the challenges that can come with data breaches gone wrong, AI implementations, you know, going in the wrong direction. So again, last night we referenced this logistics customer of ours that wants to augment their service with a chatbot. Well, there's a public use case of one of these deployments gone wrong where the chatbot started profanely talking to the customer and then writing poems in a disparaging way against the company, saying it was the worst logistics company to have ever been created. And this is all public, and it's happening in real time. They're trying to shut this thing down. Wow. Our customer is saying, hey, we need the upside, but we have to avoid that. Yeah. Or, God forbid, proprietary customer information gets out, you know, customer data. So these enterprises are very sophisticated. As much as this is an immense opportunity, going too fast could get people into real trouble. We pride ourselves in being a trusted advisor for customers on, we're going to enable you with the platform, mitigate the downside, certainly allow you to innovate, but doing it a smart, platform, you know, based way. One of the things we say is AI is going to hate data complexity and is going to hate disparate technologies trying to do this holistic thing for an application. So we really believe that the platform approach is even more relevant in an AI-powered world than it has been up to this point. Awesome. It's been a great introduction so far. Let's bring Greg into the conversation and talk a little bit about the outlook he provided yet last night and sort of the assumptions that underpin that guidance. So again, great quarter, end of the year at 25% ARR growth. You accelerated. You got Capella coming on. You're guiding to 16%. It's, you know, it's a similar, like it sounds very similar to how you guided this time last year, right? And wanted to understand, like, how did you land on, you know, the 15%-18%, and what are the assumptions that underpin that, and what are the potential upsides, upside factors, that could cause you to come above that guidance as you did the past couple of years? Yeah. Thanks, Sanjit. And again, thanks for the Morgan Stanley team for having us. Look, we, like you said last year, we think our guide was 17%. We ended at 25%. We're guiding around the same this year. As Matt said, we've got this great foundation, this enterprise business. We've been running it for well over a decade, well instrumented. We can forecast that pretty well. The factor is Capella and the pace at which, first of all, migrations are going to happen, right? That'll dictate some of it. And secondly, the pace at which the consumption continues to go. We've only been in market with on all three clouds for a year. So yes, we have some consumption history, but it's pretty limited. So understanding where that's going to go, we are not seeing some of the consumption dynamics you're hearing from some of the other companies that have been in market for five, six years where they're seeing this, you know, you know, rationalization of some of their consumption. We are not seeing that. But at the same time, we just don't have the same period of history. So Capella is going to be the driver. It was a bit this year as well. We've talked about, you know, Capella at the investor day having a net retention rate in Q3 of last year of 167%. We've talked about Capella, that a customer that's in Capella goes from zero to 100 2x faster than it did in enterprise. And from 100 to 500, it goes 4x faster. So we've seen some of these early dynamics. But again, it's pretty limited time frame. So that's what's going to potentially provide the upside. And we are still mindful of what's going on in the macro, even though it's stabilized. It isn't great still. There's still challenges with getting deals done and all that. And so we've baked some of that same thinking that we had last year into the process this year. As I always state, and you've heard it a bunch of times now, look, we set guidance at a place where we feel very comfortable that we're going to be able to meet it. And we then go work our tails off to try to beat it. And we'll try to replicate the same thing this year. That's a great perspective. So I'm going to fast forward from the next 12 months to the next four years, because going back to the analyst day that we had in December, you gave us a sort of a midterm, like a way to think about growth and margins over the midterm. And that essentially called out you guys being a 20%+ grower through fiscal year 2027, free cash flow positive, and I think free cash flow positive in 2026, operating income positive in fiscal year 2027. In addition, on the Capella side, you're assuming that Capella is about a third to half of the business in four to six years, right? And so what would have to happen to get you to be the upper end of that growth and margin framework? What would have to happen for you to be at the higher end of that, Capella contribution? Yeah. I think it's going to be Capella. And it's going to be the biggest part is going to be the migrations, quite frankly. It's how fast. And that's why we gave that range. And I realize it's a wide range. But it is very difficult to predict when customers are going to migrate. And we were talking to, you know, some of the callbacks yesterday and then today that, look, we just announced we're at 11% of Capella mix. And you got to look at the Capella mix over time. So one quarter it might go from 11%-12%. One quarter it might go from 11%-13% if we get one of our larger customers to migrate. So it's the pace of migrations. Because when a customer migrates from enterprise, a dollar that was sitting in enterprise becomes $1.50-$2 right away. So you get that nice uplift. Plus, again, if I go back to the net retention rate we saw, I'm not going to say it's going to be 167% forever. But we are seeing a nice pace. And it is above, you know, the company average. And we expect it to stay that way. So that would pull the business along and allow us to sustain that 20%+ growth rate, get closer to 50%, and even potentially pull in, you know, some of those opportunities to get to free cash flow positive and op income positive. But Capella migrations is the number one driver of that. Yeah. It makes total sense. So we just think, you know, so migrations now are sort of squarely in focus as a, you know, a lever that you guys can pull to enable greater growth and margins at the company. Can you talk about the journey when an existing, you know, Couchbase Enterprise customer moves to Capella year one, year two, and what the patterns that you're seeing, both in terms of revenue and ARR in year one and how that expands into year two? Yeah. So I mean, we talked about probably a year and change ago about our first really major migration. We had a $1 million enterprise customer come in all in to Capella. They came over. And I think we've talked about this previously, that, you know, a year and change later after that migration, they're running it over 3x what their initial purchase was. So they came in. They were running a series of apps. Those apps grew. They put more apps into it. And it just continued to grow from there. So we saw great, you know, great, results from there. And we've seen that with, again, a majority of our customers are consuming at a rate higher than what their initial purchase was. So, you know, we've seen some really nice trends for the first couple of years in terms of that. That's why I try to differentiate when people are asking us about consumption. They're reading from others like, you know, Snowflake and Mongo and Datadog. But those companies are obviously further scaled. They've been on that journey for five or six years. And they're getting to that inflection point. Or Or they're running 10+ million customers that are trying to figure out how to rationalize. We are in the very early days. So if you go back to the early days of those companies, they were just seeing the consumption ramp. That's exactly the phase that we're in right now. Yeah. Let me add some context. That customer that Greg's referring to, we're in discussions with them about the next set of applications, which would be a replatform off of one of our competitors. So even if they were doing cost optimization on the 20+ applications were deployed, we're hunting for the next set of apps. And when you talk about migrations, it's actually more rare that a customer migrates the entire estate at one time. So what we're focused on is just get them going with Capella. I mean, you've seen we've disclosed the growth rates. It's a better platform for customers because we're managing the database for them. We have a different customer that has also migrated now the entirety of their estate. And they said, look, I've been managing databases and data infrastructure for the better part of two decades. Started off his career, used to be the guy in the data room ripping out servers and doing upgrades to get things running. And he said, never in my life would I have believed that we would reach this point of euphoria with Couchbase that I don't worry about the database at all. You're running it. You're upgrading it. You're sizing it. I can get new applications into it. My team is now focused on, you know, building the next set of applications. And so we want to allow developer productivity focus on building adaptive, game-changing, industry-leading applications. And we run the database for people. So, again, the pace at which they go, there's factors outside of our control because these can be complex environments. But we want to get people going because the value proposition is real. We're delivering the experience that people are looking for. They're seeing the productivity. They talk to us about the operational savings that comes from, you know, us running the DB. So, you know, the value proposition, product-market fit, really powerful. It sounds like such an exciting opportunity, frankly. And, you know, Greg, when you mentioned that 1.5x-2x, you know, uplift that you're seeing, if I think more applications, I think that that's easy to understand. But if you sort of unpack, like, why you're seeing the magnitude of uplift that you are, is it because you're taking on more of the administrative version? There's, like, a pricing, you know, a higher ASP, if you will, for a like-to-like application. And there are other factors that are driving that uplift that you're seeing when customers migrate from Enterprise to Capella? Yeah. So if you think about the enterprise business, which is a customer-managed today, they buy the software for us. Again, I'll use the simplicity of a dollar. And then they have to go procure the infrastructure, you know, hire and train and maintain all the resources to run the database. When they come into Capella, we're so the dollar comes over. We're also now taking all the infrastructure, procurement, and management, and all the resourcing of running and managing the database. So all that goes away from them. We take it on, which is why we're effectively charging them more for that element of it. So we get that uplift. But in the end, for the customer, it's a net win because, yes, they're paying us more, but they're still saving by not having to, you know, run through the infrastructure, hire, train, maintain all those resources. They see the benefit. So the customer I said that went from $1 million to 3x, you know, in a year and change, he was at our SKO a year ago and was talking about how great it was and that he was saving money by going into Couchbase. So it's a sort of a win-win for both sides of the equation there. Significantly reduces barrier to adoption. I mean, developers can roll out new apps much easier to do. On top of that, we can manage our fleet of Capella installs. And with that information, we have telemetry on what features are used, what features aren't. We can continue to fine-tune the UI that we put in front of developers, so it just makes it easier to consume. And again, let them focus on what's going to matter to their business, which is building great applications. But they still get the full power of the Couchbase platform under the hood. So, you know, that good enough is not a viable strategy for an operational database. If you need to manage 5 billion or 10 billion concurrent documents to satisfy the application, you can either do that or not. That's why this foundation was so important to get right and building Capella on, you know, industry-leading scale, performance, flexibility, et cetera. I got one more question on this topic of migrations or the unit economics of Capella. And it's a kind of a two-parter. On the sales side, Matt, are you putting incentives in place to nudge customers to cloud versus self-managed? And then, Greg, when you think about the potential expansion opportunity or the impact on the financial model, I remember going back to analyst day, there was like a sort of transition period where it's sort of revenue neutral, but the consumption ramps up in year two. Can you speak to some of those dynamics of the revenue contribution as a customer makes that journey to Capella? We talk about the most important metric for us being ARR and driving Capella mix as a percentage of ARR being a big driver. Fundamentally, our compensation system is set in place to make sure we get those two things right. So, yes, we have incentives to, first and foremost, drive new business. You're not going to be successful here selling if you're not driving new business. And then disproportionately rewarding for Capella because of the impact it has on our customers and correspondingly on our business. There's a lot of mechanics to get into as we go through the different layers. But we're fundamentally in service of the metrics that matter for the company. Yeah. The financial aspect from an ARR perspective, when they come in, their purchase is their ARR balance for the first year unless they get to a point that they're consuming above what their purchase value is. And then that'll increase. So there's no sort of downside from an ARR perspective. After a year, they flip to consumption for sure. The revenue is. There's a timing delay because under the enterprise model in ASC 606, we take a license upfront and then go pro rata. On Capella, it's completely consumption. And so obviously, there is a ramp period for them. So it starts slow. And then we'll ramp up. So the revenue is trailing in a little bit more delayed than you would see on the enterprise. But as Matt was saying, it's great because we have all this telemetry. You can't overuse Capella. If you run out of credit, you either have to buy more or you go on demand. On the enterprise model, given that it's, you buy, you procure a certain number of nodes. You download the software and put it in production. We don't have telemetry to know if you bought 100, if you're using 50, 100, or 150. So from time to time, we see customers that are actually overusing versus what they're paying. You can't do that. So there's no leakage in Capella, which means we're monetizing fully, where I think in enterprise, we probably have, you know, a decent amount of leakage, if you will. It makes total sense. So, Matt, we talked about migrations. What we haven't talked about is just sort of, you know, bringing on new customers, kind of organic expansion. So, what's how do you think about that part of the Capella growth equation? I think migration's got a ton of focus over the last couple of months. But what's the strategy to get Capella in the hands of more customers over time? Big, big point of focus for us. We talk about part of our foundation being highly sophisticated enterprise go-to-market motion. But when we think about leverage from the Capella inflection, a big part of it is benefiting the go-to-market. So we're spending a lot of time thinking about how do we augment our traditional enterprise motion with product-led growth? If you think about the care abouts and the personas that are evaluating a decision for migration, that could be VP of infrastructure, procurement team, CIOs, how do I get my application into a modern cloud-based technology? If it's a net new developer, new application, they're looking for capabilities. How does this enable me to create an application that has different attributes than competitive solutions? So getting them up and running with trials, using our iQ Copilot that we've embedded in Capella to make development that much easier for them to get sample apps, for them to run sample SQL queries on data set. I mean, so there's a ton of capabilities that we're getting from Capella that are going to, you know, benefit us from on the go-to-market side. It's a big point of focus for us. We're much more relevant with the hyperscaler partners than we were before without Capella. Imagine the extension that gets us from a go-to-market perspective. So, you know, I like to say we have a lot of lines in the water to continue to drive improvement on, you know, new logo and new app acquisition. You know, we talked earlier about an integrated vector search RAG implementation capability, you know, infused into the platform as, you know, helping customers build GenAI applications. How is what's the opportunity for GenAI that gets infused into Couchbase? I'm thinking of things like relational migration opportunities. And more broadly, if you could speak to that to enable more applications. Well, first of all, our own engineers, which I would consider to be highly sophisticated, experienced developers, will tell us that they're 30%-50% more productive leveraging AI in their own building code for our internal purposes. If you think about a generic developer that may not know SQL, that may not yet be up to speed on vector technology, we can now come to them with a managed service. With natural language and SQL, they're now building apps on one of the most sophisticated, modern data platforms in the industry. If you think about vector technology or any database technology, oftentimes, those have a different query language. Developers need to go learn a different one. One of the things that has differentiated Couchbase is we've committed to the SQL query language with all of our services. We've extended that with vector. And so now, this combination of natural language and SQL, you're up and running with relational offload technology, vector search, the entirety of the platform. Now, I think what you're speaking about is, if you are needing to do a rewrite, people don't want to necessarily spend time rewriting applications, even if there's a TCO benefit. Well, if you can use AI to say, "hey, help me rewrite this application," or take the relational technology and map it into Couch, "Help me understand where my queries are broken," we can start to automate all that and get it up and running into Capella in, you know, very easy fashion. So I think sky's the limit in terms of AI benefiting, getting into Couchbase, and doing the work to do any kind of application rewrite for modernization. Yeah. I mean, this has been called app modernization, application replatforming, refactoring. It hasn't been a huge driver of growth for, like, the, you know, NoSQL operational databases. It's been, I think, talked about. Do you think we're on the cusp of that actually materializing as a growth driver for the business? Here's what I would say. There are a lot of positive net present value projects in enterprises. The question is, who's creating the compelling event? And what are the most important ones? And so if you look over the time period that we've been through, there's been other points of prioritization: developer productivity, distribution of workforce, cloud modernization. The question is, at what point does that become an important imperative? And it's going to vary by customer. So I think it's going to be a matter of time. We benefit from knowing enterprises around the world. There are still some mainframes that are sitting out there. Now, are there a lot less than there once was? Sure. So do I think there's going to be a moment in time where it's a complete shift over? I think there's going to be a gradual, you know, shift from legacy technology to new. The other fact of the matter is, there's so much growth in data and database spend that there's a component where both can be true over a certain time period. So I think it's going to be a factor. But I don't think it's the light switch catalyst that we've seen in other technology transitions. It's not like there's, like, a massive tipping point in three quarters from now or something like that. It's a gradual evolution, which makes total sense. Let's still talk a little bit about go-to-market and partnerships, starting with the cloud service providers. What's the sort of latest state of play with your relationships with the big three? And where do you want to see, like, you know, call it marketplace revenue or CSP-influenced revenue? What does that mix like look like today? And where do you want it to go over the next, you know, three or four years? I think we've been pretty streetwise about establishing partnerships before we might have been kind of punching above our weight. Like, we signed a strategic collaboration agreement with AWS. If you look at the other vendors that have achieved that, we're probably on the smaller side. I'm very pleased with the state of relationship with, you know, all three of them. We have the structure and all the contractual stuff in place. What I like to see now is, you know, the account planning, go-to-market initiatives jointly between us and the cloud providers. We're starting to see new logo wins come in that we don't touch that are coming from, you know, CSPs. So those are the kind of more important indicators beyond sort of the corporate structural stuff. But, you know, like the multimillion-dollar Capella migration that we saw in Q4, the biggest in company history, we have a picture at the dinner table right after signing, half the table's GCP, half the table's Couchbase. I mean, I don't think that happens if we don't have, you know, that go-to-market relationship. So I think we're in a really good place. The relevance that we have because of Capella traction is increasing dramatically. It makes total sense. And then talk about, like, the partnership opportunities within the emerging AI stack, the LlamaIndex and the LangChain of the world, I think some of which, I think, was discussed on the press release yesterday. Where are you with that ecosystem? How do you decide which players to partner with and bet on? As we think about our innovation agenda over the next year, there's a few core themes, you know, obviously, AI, extending, you know, enterprise platform support, developer productivity, customer experience. And so our job is to think about, for the developers that we want to be relevant to, which integrations matter the most. And I think on a go-forward basis, partnerships combined with new software development are going to be a pretty important combination. It's a vibrant ecosystem. So we approach, you know, proactively partners that we think are going to matter a lot to our customers. And we're very customer feedback driven. So what emerging providers are there? Are they saying? I I think one of the things that we're excited about in particular are unique things happening at the edge, where we have an unfair advantage. You know, we'll be focused on extending our differentiation on, you know, that vector, pun intended. Nice. When we think about looking at some of the verticals that you guys played in historically, strong in travel and transportation, e-commerce, obviously, tech, even fintech, payments guys, is there a verticalization part of the story that starts to emerge over time as you look to maybe even expand beyond some of these, you know, historical verticals that have been strong for you as you think about financial services and health care and moving beyond some of those core verticals over time? I think there's an opportunity to share success stories in a more efficient way, you know, things like reference architectures and particular use cases and ways to deploy applications. You know, you could have different companies in the same vertical that are in different sort of states of play as they think about, you know, software development. We are a broad-based platform that's applicable in a lot of use cases and and a lot of verticals. So we certainly don't need to, like, do go-to-market specialization. We can benefit from some of our partners who have more breadth of resources that do a lot of that work for us. I actually think this is an area that AI is going to benefit us a lot. Because imagine being able to bring all that information in via iQ into Capella. I'm a health care app. Well, instead of us having to build all the marketing material, it's drawn upon, you know, the information that's readily available. So the disproportionate benefit of AI bringing community and information into the hands of our developers in a more efficient way, I think we're pretty excited about. Awesome. I'm going to take a pause here to see if there's any questions for the management team up front. Can you share any examples of a shift from Atlas to Capella to the extent you can? I mean, we compete with Atlas quite a bit. I actually love going head to head with them. Because, what we're more worried about is opportunities where we don't get the at-bat. Mongo did a really good job in building a great customer experience. One of the things we're excited about Capella is, we now have parity as it pertains to the way to interact with the database. A lot of the proof of concepts then come down to scale and performance and TCO type benefits. So we certainly have wins against Atlas and, expect that that's going to be an area of focus for us as we go forward. You'd probably be hard-pressed to find our customers that don't have some Mongo or, you know, maybe not as much the other way around, right? Great. Any other questions for the management team? Great. One topic, and sort of keying off, like, the sort of the Mongo example and we're seeing this theme kind of play out in software is, like, as the cloud ecosystem gets more mature, cloud-based sales is also maturing. And I'd love to get your perspective, Matt. You've always been real thoughtful on how to build a high-performing sales organization, building rigor and muscle. How is the sales organization and the, you know, how is the role of a salesperson at Capella changing now? And is there a time where, you know, we see Snowflake, you know, talking about usage-based sales, Confluent saying, "don't push commitments. Just get them started. Forget about the commitments. Just focus on driving usage, usage, usage." It doesn't sound like that's how you're thinking about that now. But is there an evolution that is going to happen over time as you think about evolving the sales organization to become a world-class cloud sales company? Yeah. We think about adjustments we need to make on, you know, a constant basis. And I think the persona, the buyer, the value proposition shifts a lot. And there's a lot of discussion in technology companies about product-market fit. I think that implies that it's everything to do with the technology and not as much to do with the go-to-market. Again, if we think about a net new developer building a new application and how you need to approach them from a go-to-market, that is fundamentally different than a competitive displacement, whether it's Atlas or Oracle or who you're selling to, what the value proposition is, how you approach them, completely different. And so fundamentally, we like to think about being a trusted advisor to our customers. And how you develop trust for the different personas, I think, is changing dramatically, even prospecting. We are expecting now that our go-to-market professionals are spending half of their time prospecting. How much of that time is them picking up the phone, dialing for dollars? Like, how many times have I gotten a call for all the money we spend on technology answered and said, "yes, I'm going to go"? Zero. The way you prospect, the value proposition that you're offering, helping somebody on their application development lifecycle is very different than, you know, "help me with an ROI." And so we're constantly making, you know, those shifts and adjustments. We just had our sales kickoff. And we award our top three sellers. And we pride ourselves at having some very sophisticated sellers. This year, one of the biggest highlights of the year, two of our top three finishers were, SDR resources, professionals with us five or six years ago. That's awesome. So you think about net new capabilities, aligning the different buyers. I think that demonstrates how we're being agile on the go-to-market side. And when I say go-to-market, it's sales, SEs, customer success, marketing, business development. Great. So we've gotten in the weeds of, like, you know, product, AI, tech, differentiation, RAG. Let's simplify it and, you know, kind of uplevel the conversation. Fundamentally, you're targeting sustained growth for a long period of time, what you called out 20%+. You're talking about getting to free cash flow positive by fiscal year 2026. You're going to get profitable by fiscal year 2027. Maybe if you just simplify, like, how you're going to, you know, like, what is the, like, the one, two, three, if you will, on how you're going to get there and deliver those types of fundamentals to investors. We're going to stay committed to the foundation that's made us so great, which is highly differentiated technology meeting modern application needs, continue to focus on Capella, and then leverage this market transition of AI to levels of prosperity and market dynamics that the world has never seen. Awesome. Let's leave it there. Thank you so much, Matt and Greg, for sharing and updating us on the Couchbase story and coming to the TMT conference once again this year. Really appreciate it. Thank you.