Twilio Inc. ($TWLO)

Awesome. Welcome, everybody, to the fourth JPMorgan TMC Conference. Great pleasure to be up here with Aidan Viggiano, CFO of Twilio; and our VP and Field CTO; and Rodney, Investor Relations. Why don't we just start with the 30-second introduction of you.

Yes, great. So Aidan, I'm the CFO of Twilio. I've been with the company 7 years, CFO for about half of that, before that, I was at General Electric in various roles, but based in Boston in my final role at General Electric.

Hi, everyone. Andy O'Dower, Field CTO here at Twilio. For the last 5 years, I've been leading voice and video conversational products at Twilio as well. Before that, about 10-year customer of Twilio and previous businesses like Segment, SendGrid as well. So been leveraging and depending on the Twilio platform for years before leading product and now leading field CTO.

Rodney, Head of IR, I've been here for the last 3 years. But my history with Twilio actually goes back to the first 7 or 8 years of my career on the sell side. I actually covered Twilio for the first 3 years as public. So it feels like I've spent a decade here, which has been lovely.

And to start off, to has been on a remarkable journey over the last 2 years. I think arguably stronger today than it has ever been. A lot of investors who maybe now forget the tougher times in 2022, 2023 reset leadership transition, operational review divestitures, and it's taken a while for the market to kind of understand the opportunity you guys have ahead of yourself. So can you just walk us through -- some of the changes we've undertaken an where you guys sit today?

Yes, absolutely. I think you characterized it right. It's it definitely was a journey. It was a multiyear journey, one that started in about 2022. So if you think back to that time, right? We're coming off the pandemic, zero interest rate policy was no longer the thing. And what we saw in the business was growth started to slow. And unlike most other software businesses, we're usage-based. And so we saw growth slow, I'd say take than other business models may have. And at the time, we weren't profitable. We were using cash, definitely losing money, a lot of money on a GAAP basis. And we knew we had to get curious, right? We had to shore up the financials of the company. We had to grow up in that sense. We really needed to, I'd say, shift the culture of the company from one that was really oriented to growth to one that balanced growth and profitability. So you named the -- you kind of called out a lot of different things that we did. Maybe I'll focus on 2 of them, but I can answer any questions on the others, if you like. So the first, I'd say, is really just driving financial discipline. And what I mean when I say that is there's a lot of actions that were embedded in how we did that. So the first was kind of in '22, '23, rightsizing the workforce. And that was really difficult thing to go through, but we rightsized, we reduced our workforce by about 40%. And since then, since 2023, we've held that head count flat. So we've been roughly flat for 2, 2.5 years. In addition to that, we made other changes, right? We rightsized our real estate footprint, we reduced ports. We did other things to kind of optimize OpEx. And as a result, if you look at our track record, our non-GAAP OpEx was down in '23. It was flat in '24. It was down 1% in '25. We've proven over that time that we can really be disciplined in how we manage costs and how we invest. I'd say the other big lever on costs that we went after was stock-based compensation. So when we started our journey, when I started as CFO, we were 22% of revenue, SBC as a percent of revenue. We're 10%, less than 10% today. And we did a number of things there, obviously, rightsizing the workforce helped. But we also restricted participation for certain levels and certain functions in the organization and shifted compensation to cash. We introduced a cash bonus program for the first time in the company's history in 2024. We basically were able to reduce equity across the board in a little cash. And then we actually most recently, shifted our refresh brands from 4 years to 3 years. So a lot of different actions over the course of, I'd say, 4 or 5 years from an SBC perspective, that allowed us to reduce that expense line. And we look at burn as like our metric for how I like how we track performance there because SBC is a little bit backward looking. And we're targeting burn in less than 3% range, we were 1.5% last year, so doing better than what a committed from a framework perspective. So all of those things really allowed us to get the cash flow of the company up. We got the GAAP profitability last year for the first full year. And obviously, our non-GAAP operating margins are expanding were near 20% in Q1. So that was 1 bit of work. The next I'd say is really narrowing our focus. I think there was a tendency during like the growth heydeys of the company to want to do more than we should have. Kind of wanted to do everything. We've spread our bets maybe too thin or too widely. And I think what we did was we really buckled down when our new CEO came in, in 2024, we narrowed our focus for the company. We kind of understood who we are and what we did well. We're an infrastructure player. We're a platform player. We abandon any aspirations to kind of move up stack to the app layer. And we really focused on bringing our communications channels together with the data asset that we had acquired in Segment in 2021 and AI. And last week, we actually to cool products, that I'm sure Andy will talk about that brings all those capabilities together. And so what did that do? That kind of narrower focus on innovation really allowed us to execute better and reaccelerate growth. So we got cost kind of where it needed to be and profit where it needs to be. And then recently, as you saw in Q1, we accelerated growth to 16% organic.

Yes. Yes, I think that's a great list of accomplishments in a very short amount of time. And definitely, some aspects will come back and touch on. Andy, if we kind of think about the very successful SIGNAL you guys had. And I think Khozema called it the most consequential since Messaging itself launched, which seems like a big deal for Twilio. Can you help us understand the 3 new conversational products, conversational orchestrator, Memory Intelligence, how do the pieces kind of fit together? Where does the Twilio stack start and stop for customers? And which one of those pieces do you think kind of matters the most in the next 12 to 18 months?

Sure. And it was significantly controversial for our customers. you think about the macro environment that they're operating in, any business that is communicating with the consumer. I'm assuming many of us in the audience do has been conversing with 1 AI model or another on your phone, OpenAI, ChatGPT, Claude, Anthropic, gen AI those other things. You can communicate with it conversationally, ask any question. It remembers you, it remembers the context and you can pick up seamlessly where it lets off. But then if you try to have that same type of conversation with any business, health care, finance, car, automotive, small and medium-sized business, you have yet to have that amazing conversational experience 24/7, 365. And so our customers are operating in a world where they communicate with consumers on all of these different channels, SMS, e-mail, voice, WhatsApp, video others. And they want to offer that type of experience to their consumers. And so at the same time that we've essentially trained a generation to be able to just talk to or yell at computer and a device and get exactly what they want anytime, anywhere businesses now want to offer that to all of their customers and consumers. And so we've launched these 3 products to enable them to do that. Both our enterprise and our ISV customers that essentially want to bring the power of AI models, whichever ones they are and conversationally eye to every business out there that exists. And they've been customers of messaging, e-mail and all the channels that we offer at Twilio. And so we offered 3 things. One is conversation orchestrator, which automatically helps you orchestrate across all of these channels because in many cases, the business communicates with their consumers on multiple channels. They might be marketing to them on search and social and then driving e-mail campaigns or messaging campaigns or voice calls in the case of it's health care, real estate, higher end retail and the like where a voice call is a make-or-break moment to have revenue-generating type event. So the conversation orchestrator helps you orchestrate across all the Twilio channels that exist right now. developers and builders spend less R&D time doing that work and more time focusing on their differentiators for business. Now when you're orchestrating across these different channels, you want it to be personalized across all of these channels as well. So we leveraged all of our insights and knowledge from the segment acquisition that we did about 7 years ago, I believe. And all of that was around customer data profile and all the understanding about your consumers' profile from your advertising channels all across to your website clicks and mobile ad clicks and understanding there. All the event data of what a consumer does and [ navely ] built that into our platform. So conversation memory now is created passively just by a customer using the voice channel or using the messaging channel or the e-mail channel. So as those communications happen, there's no friction anymore for a customer to add and use memory. That's real time and in a conversation. So for example, a consumer could be on a call to schedule a test drive at a dealer they're talking to the dealership, they're mentioning the makes and models of the cars they want to try and they might get disconnected or they might say, I'm walking into a meeting, switch to text messaging. I don't want to do a phone call anymore, but I want to seamlessly pick up right where I left off. remember me, remember the state, remember everything about that. And so conversation memory powers that aspect and that is a channel too. So it might start with a messaging thread or a web chat or a lead form on a website to complete a mortgage and it might escalate to a call our view and our customers' view that should be seamless and easy and personalized all along the way, and it should remember who that customer is. So to transition from the days of having segment as a CP that is a more stand-alone to passively working across all these channels automatically. The third is Conversation Intelligence. And as you can imagine, you're having a conversation, which could last a minute or 10 minutes or a day or 6 months or 9 months with a consumer that you have intelligence about what was mentioned, what was talked about the sentiment analysis, the understanding how positive was the interaction with that customer. And you want to attach that to memory as well or you might want to trigger because the sentiment is going south in a customer service call and you spent $1,500 to acquire that customer, you might trigger in real time a notice to send a promotion, escalate to a human agent, any number of things that you might want to do to drive an outcome. And so those 3 things, orchestration across all channels again, they're glue for all the channels that our customers already know us and love us for memory to create memory that's active in real time for a conversation complementary with a data store like a Snowflake or Databricks or your CRM or CDP, but active in the conversation and then intelligence to really harvest all of that rich data after all of these channels. And that's a different era and a shift for us. And most importantly, for the customers' adoption and the builder and developer adoption is it's in the Twilio stack already. And it's easy to incrementally add versus a separate buying pattern and a separate department and friction and the like.

And I think it was implied in there, but is there a lot of virtuous flywheels in that whole process? I mean you have data kind of being gathered continuously as it goes across, easier for the customers to integrate all these products together. Can you just talk a little bit about -- that just sounds like something is going to kind of build and snowball over time.

Yes. And I think that's the key is you're moving away, especially with this new agentic world from the traditional, especially in the business consumer space of, I acquire customers online, they click, they go to the thing, they fill it out on the web. They enter a marketing funnel. They go through business processes and business rules that might trigger messages or calls and that kind of very approach throughout the organization. You're moving to an era where it's conversational throughout the entire time. And to that point, that virtuous cycle can be created where you're not only getting the data from a top of the funnel type of experience, you're able to actually converse at that point in time because you might complete a transaction in a conversation early on. You don't have to go to a website point, click, you might be convening the transaction in a messaging thread, which was why we introduced things like RCS messaging or Branded Calling that you might write at the top-of-the-funnel, say, well, give me a call. So before I complete the mortgage application, I want to know if my credit score is hit. Well, great. Now it's a branded call from the mortgage company, you instantly solve that via voice. And now you have data that once you've got the intelligence of that, I might say on the phone call, I also want to open up an account on savings. Well, now you automatically have that virtuous cycle so that data can create to open up more revenue with our consumer. And then you can use that data and send it back to a longer-term data store for other types of marketing activities. But we view that conversation and sense is that new modality and by nature, it's self-perpetuating richer and richer data source over time.

That's very exciting and very well said. And if we kind of go back you guys had a great quarter, 16% organic growth better than a lot of other software companies out there we've seen this earnings cycle. And that's even given the fact that Q1 is usually a little bit seasonally slower for you guys. So can you just help us understand what drove the acceleration where did you see the most strength and differentiation versus your plan? And how the seasonality kind of figures into it?

Yes, it was a good quarter. So 16% growth organically for us, that means ex the new U.S. carrier fees. And that's like the highest growth rate in 3 years for us. And it was quite strong. I think through out of the business in kind of 3 buckets when I think about growth. So first, from a product perspective, messaging is our biggest product. It's of our revenue. That business grew 18% ex fees, 25% on a reported basis. So really strong continued strength in our messaging business Second is voice. Voice grew 20%. That product has been accelerating. A lot of it on the back of AI natives kind of building on our platform. 20% growth is the highest growth rate in that business in 19 quarters. So really seeing the acceleration in voice. And then our software add-ons, which we talk about quite a bit, we're 20% plus. Those can be messaging and voice add-ons, but all very high margin. So from a product perspective, it was very broad. And then from a sales channel perspective, I'd say two, that we've been talking about quite a bit, self-serve and ISVs, those grew 25% plus. They're a big focus for the business. We've done a ton to make our self-serve process much simpler for developers to come in and get up and running on to the faster, get through the compliance process faster to obtain a phone number and to utilize multiple channels. So that's been great to see. And then the last bucket I kind of think about it is like industry verticals customers play. And across all of our big industry verticals, financial services, tech professional services, health care, like they were all very strong as well. So point being, it was pretty broad-based. And then you did mention the fact that like bit seasonally stronger than other Q1s. Your Q1 revenue was greater than Q4. That's the first time in a couple of years. And I would say Q1 is just generally our hardest quarter to kind of calibrate because you're coming off of peak holiday season in Black Friday, Cyber Monday, Christmas all of that. And so you're kind of trying to recalibrate a bit coming into Q1. So it's a little bit more volatile. But what I say that 5% beats are kind of the new norm. What I would say is it's a usage-based model, and this was an instance where we had more usage on the platform than maybe a little bit more than expected.

Yes. We'll definitely stay away from 5% at becoming the norm. Kind of carrying on that investors always kind of find something to net about this quarter was the Q2 guide 10.5% organically, deceleration from Q1 to look like as you said, broad-based strength across the board. Is this a refresh of conservatism? Is there anything we should be kind of mindful of there that you have mentioned yet?

I think it's pretty consistent with how we've guided. We're usage-based. I've said that a couple of times now. But because of that, we plan a bit more prudently. And so I think it's just a little bit more of the same in that regard. 10% to 11% growth. That's consistent with how we guided Q1 and at the time, it was our highest guidance in quite some time. So I feel really good about the opportunity ahead of us. I think our teams are well, and I feel good about the setup for Q2 and the balance of the year.

Great. Great. Andy, coming back to you. You did a great job, I think, of just using these different layers of technology we pulled together. I think one of the central narratives that you've been making is a lot of the value and the bottleneck exists in that orchestration memory infrastructure layer versus just intelligence. Obviously, there's a big debate out there. So can you kind of talk a little bit about that? I mean a lot of the customers -- excuse me, partners we speak to say that you guys have the access for customers to get agentic solutions to get AI solutions. But what does the architecture look like with you guys without you guys? And what becomes possible for them utilizing your technology?

Sure. I think to that point, we see that customers are -- they're building their AI agents, and they might be wed to a certain hyperscaler or AI model company that they want to build their AI agents with. And they might switch those over time or they might have a mixture of different cloud providers or AI model providers, small models, large models and diversify there. So to communicate with their customers, they're going to need those and that might change. The two other pieces of that ingredient list, if you will, is the communications and then the contextual data to be able to provide it. Because we know a generic agent isn't going to be able to solve all the problems that you might have in servicing a customer. You need to reach them where they are any time, where they are on any channel. So that's the key ingredient and foundation that we've built on over and over again for coming up on 20 years. And they're all programmable. So all those channels are programmable in that sense. They're not basic channels. We've called them programmable for a reason. They're API-based, they're configurable. They've got dozens and tons of different types of configurable features, be it the API, and AI loves that. They love the configuration, the malleability of how I can divert a call or a channel or a message or threat or anything else like that. So we're purpose-built for this age of interoperating with these agents. And you need the contextual data to make that work. Otherwise, you just have a generic AI agent trying on any channel to communicate. And that's why we introduced the conversation memory aspect continually feed that context back in to have a super personalized experience. And our customers want that AI to reach the last mile, which is all of our phones, which is all of our phone numbers and our inbox and WhatsApp and everything else like that. So we we're sitting in that middle of the value chain and right at the end of the last mile where it actually matters where the agents can connect. So we also launched a product called Twilio Agent Connect, which is an interface, it's a self-hosted [indiscernible] for our customers to be able to access what I just described, the communication and the data with far less work to bring in their agents from different hyperscalers or small models or large models because we know that's going to change. They want future proofing the next -- every 5 minutes, there's a new, faster, cheaper, different model that exists out there. And we're going to continue to be agnostic, but we're going to continue to introduce those layers of abstraction and orchestration so you can plug and play. So as that plays out, we'll continue to be agnostic because that's where we see our customers wanting us to go.

Yes. I want to bring out a quote that you had during one of your interviews at SIGNAL. And you said 1 of your customers mentioned to you that everything that Twilio's building, I don't want to build any more. I'm sure you're not unfamiliar with the AI being the depth of software narrative. I think you have to understand that's not true for Twilio at all. But it would be great to get your perspective from a vantage point. What are you seeing in those regards -- because we hear this concept of the customers want to [ buy code ] of our interactions with customers and partners seems to push back a lot against that, but it would be great to kind of get your perspective there?

Yes. I think the timing is everything, and that's saying is true for a reason. If you think about everything that's happened the AI models. Everything I've been talking about is how those AI models can be deployed to help power a conversation. At the same time, all the agentic coding models that exist out there, and we're so close to this because of our millions and millions of developers over the years. We're tracking and seeing the trends of how software is built, and you can accelerate it by using all these great agent coding tools to be able to do that. So there's interesting benefits is now with those agentic coding tools, you can build more with more pieces of Twilio, far faster than you would have before. We're helping you accelerate that by introducing things like conversation, orchestrator and memory and otherwise, which you don't have to build anymore. You don't have to create that stitching layer of software anymore for you as a customer. You don't have to spend your R&D budget doing that stuff anymore. At the same time, a lot of these leaders like the one you cited that said, I give up. I tried to build my own Conversation Relay and Voice Relay back and forth a year ago, and I boomeranged back because why do I need to be building that stuff anymore. I need to be spending my R&D budgets, especially with foundational model companies may be coming for my layer of app, I better focus my R&D budgets on my differentiators of my business, not infrastructure, not Twilio's Super Network across 4,800 carriers globally, not at the onboarding and compliance layer where we get all customers around their ability to own and port in phone numbers and e-mail addresses and all of that trusted identity and verification. They already trust us for the verification to verify all of us consumers when we're logging into mobile apps and banking and everything else like that. And they trust us for the channels, clearly. And so now they're thinking about where do I put my R&D now when I talk to the CIOs and CTOs and CPOs, up until a month ago was that product leader thinking where do we put our R&D budget, our process time and energy and better be on our differentiator up here and offload the rest of the infrastructure to trusted providers. And they'll try that there's so many new great AI start-ups that all come to Twilio because they know I need to reach consumers where they converse the channels where Twilio exists, and so they all come to Twilio first. So we have the luxury of working with many of them early stage, but they trust that the R&D must be spent on their differentiators and offload the infrastructure to trust partners that are going to be durable.

And did I hear you say that like that some of that customer realization that they need to focus on their own differentiation that's happened over the last few months?

I think we've seen that over the last couple of years, as the first AI models came out, everybody thought I'm just going to deploy them everywhere. And when I say that, I mean out to customer service layers, support layer and things like that, but they were generic. They didn't have the context and the data, and then they realize coming back, I need to be surgical with my approach to how I apply AI in service. And so when you see that much more all or nothing to a more surgical approach than over the last year, we're starting to see the changing in the R&D budget, of offload the infrastructure, focus on my differentiators. And I think now specifically with things like voice AI, as we see customers bend the curve and do the testing and evaluation and move into production, that's even more the case of spending your R&D budget because I make that a differentiated conversation. And to that, I need to spend my time and energy there and not at the infrastructure layer.

That's a great segue because I don't think we can get away without talking about Voice AI. Nice thing about that, it's still early days. AI negatives growing pretty fast. Like you said, things going into production. We -- 1 person we spoke to a partner, had an auto retailer that scaled from 500 calls a day to 25,000 calls a day in less than a year. So can you help us understand the opportunity moving forward? What are the current hurdles for the customers? It seems like they're kind of moving forward, but what are those challenges they need to overcome? And is it any different in some of the more regulated verticals?

Yes. It's also interesting that some of the customers we recently published a case study, I think, last week on a customer an ISV partner is called [ Posh ] and they automate customer service calls for credit unions across the U.S. And so they're in a regulated vertical. They're in an environment with demographic calling in and high volumes of calls and they need to be able to handle it. I think the thing that is interesting, also AI impacting is the ability to start, build your proof-of-concept and then move into production quickly. That last part to move into production quickly is the trickiest part. But what we're seeing is a lot of advancements in the testing and iterating of those types of things. And specifically, I mean, you can spin up using AI, fake consumers. And you can spend up 1,000 fake consumers with 1,000 different scenarios of complaints in new business and customer service inquiries that happen and battle test your AI agent that you just built. So that test and deployment cycle is starting to compress more and more because you can use AI to test AI, real-world scenarios before you deploy out to production. And so I think that's an interesting collapsing of that R&D time cycle. And in the Voice AI space, where we see our customers offloading more and more of that orchestration and development is just a natural progression from where we built programmable messaging. We've observed customers for years and years, use speech recognition and then build their own solution or use generative AI voice and build their own solution. And we're agnostic there in the stack. We partner with the best of for speech recognition and for generative AI voices, because we know, just like the foundational models, every 5 minutes, there'll be a new better faster on each of those technologies. That's a configuration for our customers. Not a new vendor agreement and a new procurement cycle, we already bring those players in. So for Voice AI, again, we view ourselves at that later of abstraction built on top of the 18-year-old foundation and learning how customers use programmable voice, so they can get up and running much more quickly. And the AI agent aspect of testing is compressing time line cycle, which is really interesting for customers to go into production and move beyond proof of concept where many of them were a year ago.

Yes. I'll touch on 1 more quote that a partner said, saying, you guys are doing great Voice AI is on fire. They said most customers have relatively simple use cases. When I asked them about it, I was like, is that initial technology? What is it? He said, no, not at all. It's customer sophistication operationally and with data and he's like the art of the possible with Voice AI is kind of beyond even some of the customers' imagination, they're not there. So maybe a little bit if you can give us like what do you see because I'm sure you have a great vantage point of what's possible. And years do you think customers need to kind of climb their own learning curves across the organization to be able to use those?

Yes. I think when you think about going from this all or nothing approach, let's just put an AI agent across everything on our website, and everything to now have a surgical approach. The natural place where you see customers go is inbound customer support for a specific use case. We have a legacy IVR that's press 1 for this, press 2 for that. We have 25,000, 50,000, 100,000 calls a day that happened, they cost on average maybe $15 a call because you've got human agent answering calls and everything else like that. And with AI agent, that cost can drop to $0.15. And we had our SIGNAL conference last week and [ Bret Taylor ] spoke and cite that statistic of when the cost goes for a phone call from $15 to $0.15. And he's got an interesting viewpoint being the Chairman of OpenAI and launching a company that automates customer service in that sense, when you see that economic disparity, you naturally didn't expect the volume to start to go up because now you can handle more calls faster, better, easier, 24/7, 365. Anecdotally, we see some customers putting the 1-800 number that used to be buried on 5 different clicks down on the website up further the visibility chain because they can handle that faster and easier and cheaper. You see Voice AI start-ups built on top of Twilio buying billboards on the 101 of a phone number to prove how good that AI is. So I think we're early in the sense that we're starting to see those customers bend the curve and they're bending it in that customer service inbound customer service place. But to the point I made early, conversation can happen at any time of that funnel. And so maybe they start with inbound customer support, nail a use case on a traditional IVR of where most of the calls go to what department most of the time. And realize once we add intelligence and memory to that, what if we map the memory from that phone call and the conversation to all the customer acquisition data that we had in the marketing side of things. And so you start to see these -- the departments start to blur because in an older area where the marketing team just did their thing and the customer service team did their thing. If you don't have full visibility of the effectiveness, you could be really burning through cash on your acquisition if you don't service the customer the right way. So as those start to blend, I think over the next couple of years, you'll start to see, and that's obviously the bet with these orchestration offerings across conversations as, we become glue for additional channels and then buyers that are crossing departments. Naturally, we're seeing CEOs and you have CFOs and CPOs thinking, wait a second, this is one customer journey. All this data needs to be seamless together for this to work. And I think that's the curve over the next year or 2 where you start to see this move into production, not just for voice, but across departments inside of business. And that's where it gets really interesting and I think much more effective for a business.

Yes. Well, that implies by when you hear on funded we're kind of getting close to the end of it. It's been fantastic to host you guys. One thing we always love to leave off on is when we're back here a year from now. What do you think that we're going to be talking about that maybe you guys are seeing now, but is going to be a surprise to the people in this room?

All right. I'll take a stab at that. Maybe I won't predict the future. I don't know that that's going to serve us well. So what I would say is, in a year from now, I think -- I'd hope we'd be saying that investors and must be saying the same things about Twilio, they're operating with financial discipline they're an innovative company, and it's a company that did what they said they would do over the last 12 months. I think if that's the story, then I think that would be a good one.

Yes. I think I always try to look at what are all the builders on Twilio's platform doing because they're all at the cutting edge, and we get the luxury of seeing what are all the olders' doing with all the latest and greatest technology out there. I think that different than in the past is our customers that I talk to, especially at the CIO, CTO, CPO level, have shifted their thinking about Twilio from spot solution to a platform. And now I have a menu of all of these different services that I can buy and use and deploy and now you're introducing product solutions Twilio are introducing these solutions to help me do better together. So we often say, I can't wait to see what you build. Years ago, that might have been isolated to a singular channel. I might see what you build in the e-mail channel and messaging and others. And now we're offering this orchestration. So I think that's going to be the very interesting is what have you built across the entire platform, not just individual products and services. And so that's where it gets really interesting. And I think the acceleration on the AI front will happen both with how they can apply AI to communications and data but also is helping them accelerating building faster and building more on Twilio, because of the agentic coding tools that millions and millions and millions of developers are using, which now creates a new market for us in terms of what a builder means. A builder using natural language to yell at Claude replace my old school IVR, make it omnichannel, make it messaging, make it personalized and use Twilio and then port my phone 500 numbers over from my business over to power that. Doing that in natural language is far different than 5 years ago of having stitched together all these disparate services. So that's what I'm really excited to see is what that -- that terminology, what a builder is for us, that hits right at the essence of what Twilio has built all of our products is to really open up the imagination of what a builder could be. And now these agentic coding tools are meaning there's far more builders that can build far easier. And so that's what will be interesting to see as the depth and breadth of what they build in the ecosystem.

Yes. It's been very exciting to watch you guys and excited to see where you go. Aidan, Andy and Rodney. Thank you so much. I appreciate it.

Thank you.

Thank you.