Awesome. Welcome everybody to the 54th JP Morgan TMC Conference. Great pleasure to be up here with Aidan Viggiano, CFO of Twilio, Andy O'Dower, VP and Field CTO, and Rodney, Investor Relations. Why don't we just start with a 30-second introduction of you guys?
Yeah, great. Aidan, I'm the CFO at Twilio. I've been with the company seven years, CFO for about half of that. Before that 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 five years, I've been leading voice and video, conversational AI products at Twilio as well. Before that, about 10-year customer of Twilio and previous businesses like Segment, SendGrid as well. Been leveraging and depending on the Twilio platform for years before leading product and now leading as Field CTO.
Rodney, head of IR. Been here for the last three years. My history with Twilio actually goes back to the first seven or eight years of my career on the sell side. I actually covered Twilio for the first three years it was public, it feels like I've spent a decade here, which has been lovely.
Aidan, to start off, Twilio's been on a remarkable journey over the last few years. You know, I think arguably stronger today than it's 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 yourselves. Can you just walk us through some of the changes you've undertaken and where you guys sit today?
Yeah, absolutely. I think you characterized it right. It definitely was a journey. It was a multi-year journey, one that started in about 2022. If you think back to that time, right? We're coming off the pandemic. Zero interest rate policy was no longer a thing. What we saw in the business was growth started to slow. Unlike most other software businesses, we're usage-based. We saw growth slow, I'd say quicker than other business models may have. At the time, we weren't profitable. We were using cash, definitely losing money, a lot of money on a GAAP basis. We knew we had to get serious, 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. You kinda called out a lot of different things that we did. Maybe I'll focus on 2 of 'em, but I can answer any questions on the others if you like. The first I'd say is really just driving financial discipline. What I mean when I say that is, you know, there's a lot of actions that were embedded in how we did that. The first was kind of in 2022, 2023, right-sizing the workforce. That was a really difficult thing to go through, but we right-sized. We reduced our workforce by about 40%. Since then, since 2023, we've held that headcount flat.
We've been roughly flat for, you know, two and a half years. In addition to that, we made other changes, right? We right-sized our real estate footprint. We reduced perks. We did other things to kinda optimize OpEx. As a result, if you look at our track record, our non-GAAP OpEx was down in 2023. It was flat in 2024. It was down 1% in 2025. 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 cost that we went after was stock-based compensation. 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. We did a number of things there.
Obviously, right-sizing the workforce helped. 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 lieu of cash. We actually, most recently, shifted our refresh grants from four years to three years. A lot of different actions over the course of, I'd say, four or five years from an SBC perspective that allowed us to reduce that expense line. We look at burn as, like, our metric for how I, you know, like, how we track performance there because SBC is a little bit backward-looking. We're targeting burn in less than 3% range.
We were 1.5% last year, doing better than what we had committed from a framework perspective. All of those things really allowed us to get the cash flow of the company up. We got to GAAP profitability last year for the first full year, and obviously our non-GAAP operating margins are expanding. We're near 20% in Q1. 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 heydays of the company to want to do more than we should have, kinda wanted to do everything. We spread our bets maybe too thin or too widely. 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 abandoned any aspirations to kinda move upstack to the app layer. We really focused on bringing our communications channels together with the data asset that we had acquired in Segment in 2021 and AI. Last week, we actually launched a lot of cool products that I'm sure Andy will talk about that brings all those capabilities together. What did that do? That kind of narrower focus on innovation really allowed us to execute better and re-accelerate growth. We got cost kind of where it needed to be and profit where it needed to be. Recently, as you saw in Q1, we accelerated growth to 16% organic.
Yeah. Yeah, I think that's a great list of accomplishments in a very short amount of time. Definitely some aspects we'll 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 three new conversational products, Conversation Orchestrator, Conversation Memory, and Conversation Intelligence? How do these pieces kind of fit together? Where does the Twilio stack start and stop for customers? Which one of those pieces do you think kind of matters the most in the next 12 to 18 months?
Sure. It was significantly controversial for our customers. If you think about the macro environment that they're operating in, any business that is communicating with a consumer, I'm assuming many of us in the audience too has been conversing with one AI model or another on your phone, OpenAI, ChatGPT, Claude, Anthropic, Gemini, any of 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. If you try to have that same type of conversation with any business, healthcare, finance, car, automotive, small and medium-sized business, you have yet to have that amazing conversational experience 24/7, 365.
Our customers are operating in a world where they communicate with consumers on all of these different channels, SMS, email, voice, WhatsApp, video, others, and they wanna offer that type of experience to their consumers. At the same time that we've essentially trained a generation to be able to just talk to or yell at a computer in a device and get exactly what they want anytime, anywhere, businesses now wanna offer that to all of their customers and consumers. We've launched these three products to enable them to do that. Both our enterprise customers and our ISV customers that essentially wanna bring the power of AI models, whichever ones they are, and conversational AI, to every business out there that exists. They've been customers of messaging, email, voice, and all the channels that we offer at Twilio.
We offered 3 things. One is Conversation Orchestrator, which automatically helps you orchestrate across all of these channels, because in many cases, a business communicates with their consumers on multiple channels. They might be marketing to them on search and social, then driving email campaigns or messaging campaigns or voice calls, in the case if it's a healthcare, real estate, higher-end retail, and the like, where a voice call is a make or break moment to have a revenue-generating type event. 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 the business. Now when you're orchestrating across these different channels, you want it to be personalized across all of these channels as well.
We leveraged all of our insights and knowledge from the Segment acquisition that we did about seven years ago, six, seven years ago, I believe. And all of that was around customer data profile and all the understanding about your consumer's 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 natively built that into our platform. Conversation Memory now is created passively just by a customer using the voice channel or using the messaging channel or the email channel. As those communications happen, there's no friction anymore for a customer to add and use memory that's real-time and usable in a conversation. You know, for example, a consumer could be on a call to schedule a test drive at a dealership.
They're talking to the dealership. They're mentioning the makes and models of the cars they wanna try, and they might get disconnected. They might say, "I'm walking into a meeting. Switch to text messaging. I don't wanna do a phone call anymore, but I wanna seamlessly pick up right where I left off. Remember me, remember the state, remember everything about that." Conversation Memory powers that aspect. That is across channels too. 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. In our view and in our customer's view, that should be seamless and easy and personalized all along the way, and it should remember who that customer is.
To transition from the days of having Segment as a CDP that is a more standalone to passively working across all these channels automatically. The third is Conversation Intelligence. As you can imagine, you're having a conversation which could last 1 minute or 10 minutes or a day or six months or nine 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.
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, you know, any number of things that you might wanna do, to drive an outcome.
Yeah.
Those three things, orchestration across all the 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 a Databricks or your CRM or your CDP, but active in the conversation. Intelligence to really harvest all of that rich data after all of these channels. That's a different era and a shift for us. Most importantly, for the customer's adoption and the builder and developer adoption, is it's in the Twilio stack already. It's easy to incrementally add versus a separate buying pattern and separate department and friction and the like.
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.
Yep
as it goes across, easier for the customers to integrate all these products together. Can you just talk a little bit about, you know, that just sounds like something that's gonna kind of build and snowball over time?
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 a 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 siloed approach throughout the organization. You're moving to an era where it's conversational throughout the entire time. 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 completing the transaction in a messaging, thread.
Yeah
Which was why we introduced things like RCS messaging, or Branded Calling that, you might right 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 gets 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 then be created to open up more revenue opportunity with that consumer. You can use that data and send it back to a longer-term data store for other types of marketing activities.
We view that conversation in and of its sense is that new modality, and by nature, it's self-perpetuating.
Yeah.
Richer and richer data source over time.
That's very exciting and very well said. Aidan, if we kind of go back, you guys had a great quarter, 16% organic growth, better than a lot of the other software companies out there we've seen this earnings cycle. That's even given the fact that Q1 is usually a little bit seasonally slower for you guys. Can you just help us understand what drove the acceleration? Where did you see the most strength and differentiation versus your plan? You know, how the seasonality kind of figures into it?
It was a good quarter. 16% growth organically. For us, that means ex the new U.S. carrier fees. That's like the highest growth rate in three years for us. It was quite strong. I think about the business in kind of three buckets when I think about growth. First, from a product perspective, messaging is our biggest product. It's nearly 60% of our revenue. That business grew 18% ex fees, 25% on a reported basis. 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. Really seeing the acceleration in voice.
Our software add-ons, which we talk about quite a bit, were 20%+. Those could be messaging add-ons, voice add-ons, but all very high margin. From a product perspective, it was very broad. 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%+. 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 onto Twilio faster, get through the compliance process faster to obtain a phone number and to utilize multiple channels. That's been great to see. The last bucket I kind of think about it is like industry verticals. Where do our customers play?
Across all of our big industry verticals, financial services, tech, you know, professional services, healthcare, like they were all very strong as well. You know, you did mention the fact that like it was a bit seasonally stronger than other Q1s. You're right, Q1 revenue was greater than Q4. That's the 1st time in a couple of years. Q1 is just generally our hardest quarter to kind of calibrate because you're coming off of peak holiday seasons, Black Friday, Cyber Monday, Christmas, all of that. You're kind of trying to recalibrate a bit coming into Q1. It's a little bit more volatile. I wouldn't 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, you know, maybe a little bit more than expected.
Yeah. We'll definitely stay away from 5% beats becoming the norm. kind of carrying on that, investors always kind of find something to nit about. This quarter was, you know, the Q2 guide, 10.5% organically deceleration from Q1, despite what looked like, as you said, broad-based strength across the board. Is this a reflection of conservatism? Is there anything we should be kind of mindful of there that you haven't mentioned yet?
No, I think it's pretty consistent with how we've guided. We're usage-based. I've said that a couple of times now. Because of that, we plan a bit more prudently.
Yeah.
I think it's just a little bit more of the same in that regard. You know, 10%-11% growth, that's consistent with how we guided Q1, and at the time, it was our highest guidance in quite some time. I feel really good about the opportunity ahead of us. I think our teams are executing 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 discussing these different layers of technology you pulled together. I think one of the central narratives that you've been making is, you know, a lot of the value and the bottleneck exists in that, you know, orchestration memory infrastructure layer versus just the intelligence. Obviously, it's a big debate out there. 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 are the access for customers to get agentic solutions, to get AI solutions. What does the architecture look like with you guys, without you guys, and what becomes possible for them utilizing your technology?
Sure. I think, you know, to that point, we see that customers they're building their AI agents, and they might be, you know, 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. To communicate with their end 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 AI 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, anytime, where they are, at, on any channel. That's the, you know, the key ingredient and the foundation that we've built on over and over and over again for, you know, coming up on 20 years. They're all programmable. 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 dozens of different types of configurable features via 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 thread or anything else like that. We're purpose-built for this age of interoperating with these agents. You need the contextual data to make that work.
Otherwise, you just have a generic AI agent trying on any channel to communicate. That's why we introduced the Conversation Memory aspect, is to continually feed that context back in to have a super personalized experience. 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. 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 AI agents can connect. We also launched a product called Twilio Agent Connect, which is an interface.
It's a self-hosted SDK 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 agent from different hyperscalers or small models or large models, because we know that's gonna change. They want future-proofing. The next, you know, every five minutes there's a new, faster, cheaper, you know, different model that exists out there, and we're gonna continue to be agnostic. We're gonna continue to introduce those layers of abstraction and orchestration, so you can plug and play.
Yeah.
As that plays out, we'll continue to be agnostic because that's where we see our customers wanting us, wanting us to go.
I want to bring up a quote that you had during one of your interviews at SIGNAL, and you said one of your customers mentioned to you that everything that Twilio is building, I don't want to build anymore. I'm sure you're not unfamiliar with the AI being the death of software narrative.
Yep.
I think people understand that's not true for Twilio at all. It'd be great to get your perspective from a vantage point. What are you seeing in those regards? 'Cause we hear this concept of the customers wanting to vibe coding. A lot of our interactions with customers or partners seems to push back a lot against that, but it'd be great to kind of get your perspective there.
Yeah. I think the, you know, timing is everything, that saying's true for a reason. If you think about everything that's happening with 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, we're so close to this because of our millions and millions of developers.
Yeah
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 agentic 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 accelerate that by introducing things like Conversation Orchestrator and Conversation 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, 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, you know, foundational model companies maybe coming for my layer of the 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 vet all customers around their ability to own and port in phone numbers and email addresses and all of that, you know, 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.
They trust us for the channels, clearly. Now they're thinking about, "Where do I put my R&D budgets now?" I talk to the CIOs and CTOs and CPOs. I, you know, up until a month ago was that, you know, product leader thinking, "Where do we put our R&D budget, our precious time and energy? It better be on our differentiator up here, and offload the rest of the infrastructure to trusted providers.
They'll try that, you know, there's so many new, great AI startups that all come to Twilio because they know, "I need to reach consumers where they converse," and that's the channels where Twilio exists. They all come to Twilio first. 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-
Yeah
to trusted partners that are gonna be durable.
Did I hear you say that, like, that some of that customer realization that, you know, 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 years. You know, when, as the first AI models came out, everybody thought, "I'm just gonna deploy them everywhere." When I say that, I mean out to customer service layer, support layer, and things like that. They were generic, they didn't have the context and the data, and then they realized coming back, "I need to be surgical with my approach to how I apply AI in service." When you see that much more, all or nothing to a more surgical approach. Over the last year, we're starting to see the changing of the R&D budgets of offload the infrastructure, focus on my differentiators.
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 is how does I make that a differentiated conversation? To that, I need to spend my time and energy there and not at the infrastructure layer.
That's a great segue 'cause I don't think we can get away without talking about voice AI. Nice thing about that is it's still early days. AI natives, growing pretty fast. Like you said.
Yeah
you know, things going into production. One 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. Can you help us understand the opportunity moving forward? What are the current hurdles for the customers? Seems like they're kind of, you know, moving forward, but what are those challenges they need to overcome, and is it any different in some of the more regulated verticals?
Yeah. 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 of ours called Posh, they automate customer service calls for credit unions across the U.S. They're in a regulated vertical. They're in an environment with, you know, 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. What we're seeing is a lot of advancements in the testing and iterating of those types of things.
Specifically, I mean, you can spin up, using AI, fake consumers, and you can spin up a thousand fake consumers with a thousand different scenarios of complaints and new business and customer service, inquiries that happen, and battle test your AI agent that you just built. You know, 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. I think that's an interesting, you know, collapsing of that R&D time cycle. 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 voices 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 min. 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. For voice AI, again, we view ourselves at that layer of abstraction built on top of a 18-year-old foundation and learning how customers use programmable voice, so they can get up and running much more quickly.
The AI agent aspect of testing is compressing that timeline 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.
Yeah. I want to touch on one more quote that a partner said. You know, he was saying, "You guys are doing great. Voice AI is on fire." He said most customers have relatively simple use cases. When I asked him about that, I was like, "You know, is it an issue with technology? What is it?" He said, "No, not at all. It's customer sophistication operationally and with data." He's like, "You know, the art of the possible
Yeah.
with voice AI is, you know, kind of beyond even some of the customers' imagination. They're not there." 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. How many years do you think customers need to kind of climb their own learning curves across the organization to be able to use those?
I think, you know, when you think about going from this all or nothing approach of let's just put an AI agent across everything on our website, and it's gonna handle everything to now the surgical approach, the natural place where you see customers go is inbound customer support for a specific use case. You know, we have a legacy IVR that's press one for this, press two for that. We have, you know, 25, 50, 100,000 calls a day that happen. They cost on average maybe $15 a call because you've got a human agent answering the calls and everything else like that. With AI agents, that cost can drop to $0.15.
You know, we had our SIGNAL conference last week, Bret Taylor, you know, spoke and cited that statistic of, you know, when the cost goes for a phone call from $15 to $0.15. 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 then 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 in the website up farther up the, you know, the visibility chain because they can handle that faster and easier and cheaper.
You see voice AI startups built on top of Twilio buying billboards on the 101 of a phone number to prove how good that AI is. 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, you know, inbound customer service place. To the point I made early. A conversation can happen at any time of that funnel. 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 then realize once we add intelligence and memory to that, what if we mapped the memory from that phone call and the conversation to all the customer acquisition data that we had in the marketing side of things?
You start to see these, you know, these departments start to blur because in a, you know, older era 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, you know, really burning through cash on your acquisition if you don't service the customer the right way. As those start to blend, I think over the next couple years you'll start to see, and that's, you know, obviously the bet with these orchestration offerings or cross conversations is we're become glue for additional channels and then, buyers that are crossing departments. Naturally, we're seeing CEOs, you know, CFOs and CPOs thinking, "Wait a second, this is one customer journey.
All this data needs to be seamless together for this to work. I think that's the curve over the next over the next year or two, where you start to see this move into production, not just for voice, but across departments inside a business.
Yeah.
That's where it gets really, really interesting, and I think much more effective.
Yeah
for a business.
Yeah. Well, time flies by when you're having fun, and 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, you know, when we're back here a year from now, what do you think that we're gonna be talking about that, you know, maybe you guys are seeing now, but is gonna be a surprise to the people in this room?
All right, I'll take a stab at that. you know, maybe I won't predict the future. I don't know that that's gonna serve us well. What I would say is, you know, in a year from now, I think, you know, I'd hope we'd be saying that investors and analysts would be saying the same things about Twilio. They're operating with financial discipline. They're in 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.
Andy?
Yeah, I think, you know, 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 builders doing with all the latest and greatest technology out there. I think that the different than in the past is our customers that I talk to, especially at the, you know, 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. Now you're introducing product solutions. You, Twilio, are introducing these solutions to help me do it better together.
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 email channel or in messaging or others, and now we're offering this orchestration. I think that's gonna be the very interesting is what have you built across the entire platform, not just individual products and services. That's where it gets really interesting. I think the acceleration on the AI front will happen both with how they can apply AI to communications and data, but also how AI is helping them accelerating building faster and building more on Twilio because of the agentic coding tools that millions of developers are using, which now creates a new market for us in terms of what a builder means.
Yeah.
You know, a builder using natural language to yell at Claude, "Build, you know, replace my old school IVR, make it omni-channel, make it messaging, make it personalized, and use Twilio, and then port my 500 phone numbers over from my business over to power that." Doing that in natural language is far different than five years ago of having to stitch together all these disparate services. That's what I'm really excited to see is what that, you know, the terminology, what a builder is for us. That's, you know, that hits right at the essence of what Twilio's 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.
Yeah
that can build far easier. That's what'll be interesting to see is the depth and breadth of what they build in the ecosystem.
It's been very exciting to watch you guys and excited to see where you go. Aidan and Rodney, thank you so much. We appreciate it.
Thank you.
Thank you.