All right. Hello, and thank you all for joining us. I am Josh Yankovich, Vice President of Investor Relations and Corporate FP&A here at Q2. A brief note before we begin. Some of the comments today may include forward-looking statements that are subject to risks, uncertainties, and assumptions that could change. Should any of these risks materialize or should our assumptions prove to be incorrect, actual company results or outcomes could differ materially from these forward-looking statements. A description of the risks, uncertainties, assumptions, and other factors that could affect our financial results or outcomes is included in our SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements. With that, I am glad to be joined again by Adam Blue, our Chief Technology Officer, and Hima Mukkamala, our Chief Operating Officer. This is the second conversation in our AI series. The first earlier in the year was a deep dive on our strategy and architecture, and today we are focused on some of the questions we have been hearing most from investors right now. What is the rise of personal AI agents mean for the role of digital banking? How is AI reshaping the fraud landscape, and where does Q2 continue to have the right to win? With that, I am going to go ahead and start with a question with Hima. Hima, let us start with personal agents. Recently, with Muse rolling out, there has been a lot of momentum in the conversation around using agents to connect with disparate applications, including digital banking, and what that might mean for those respective industries. Hima, where do these agents actually integrate with respective financial institutions' digital banking platforms, and where does it leave us as their digital banking provider? Yeah. Thanks, Josh. When we think about the evolution of how users, consumers, commercial users interact with their financial institutions, personal agents are the next banking channel. We have had branch, people used to go to branch. We went online, web, and then mobile. I look at this as a new front door and not just a replacement for a bank or a replacement for digital banking and a fraud platform. In our technology, just like we have enabled these interactions coming through mobile web and so on, it enables these personal agents to come and interact with a consumer or a commercial institution's financial information, and that is the evolution we are going to go through over the coming years. There are a couple of ways we think about this. A bank can keep the AI experience inside the channel it owns. This is what we do today, where you can go log into the website. There are agentic ways in which consumers can interact with the bank or the back office. The second approach, which is emerging with Muse-like application or Dot-like applications, is how do they support the channels they do not own? It could be a social agent, it could be apps like Instinct, which use messaging applications, an iMessage app or a smart device, or the cloud and the ChatGPT. That can happen in a couple of ways. Through the platform, we expose what is called MCP, which is a new way of API integrations. We expose MCP endpoints on most of the digital banking stack, and these personal agents can use that to talk to the digital banking platform. The second approach in this subset is not just use MCPs, because MCPs are just APIs, and the banks want a richer experience and want us to facilitate making this agentic channel an extension of the digital channel, and these two need to work in harmony. You cannot have all of the digital channels working one way and the agentic channels work differently in terms of security, entitlements, policies, and so on. So what we are working on is delivering this end experience whichever way the user wants, but give the control to the banks so that ChatGPT has this thing called intelligent user interfaces. We want to work with them to continue to create, retain the financial institution's brand experience, give the consumers the comfort that they're interacting with the right financial institution. That is the value we bring as a technology partner, and we are on the hook to deliver these services, because the platform is still in the middle. The digital banking platform is in the middle, where we talked about it last time. It's got the context, it's got the integration, it's got the orchestrations, and this new interaction model is leveraging all of that stuff. Finally, the relationships, the data, and the controls all sit within the platform. The agents are orchestrating, but still are interacting with the platform in however the financial institution and the consumer want the agent to operate. Ultimately, the control is within these two layers. Adam, would you add anything to that? Yeah, I would. We talk with banks and customers and end users all the time, and I think it may be natural to think that bringing an external agent to the digital banking experience would tend to flatten or commoditize the experience. I think actually the opposite is true. What we're starting to see, as Hima mentioned, is that the surface for exposing the personality of the bank, the brand of the bank, the capabilities, the MCP surface, it's wider than previous mechanisms. We've dealt with IVR as a channel. We've dealt with web as a channel, mobile as a channel. We've dealt with the Apple Watch as a channel. We've dealt with SMS as a channel. The agentic channel is really interesting because it gives you a much wider surface and a broader context that you can bring to the agent. If you built a really boring experience, you would deliver balances and transfers and maybe bill pay. Given that the agent actually has some level of discretion and the agent is operating with an intent on behalf of the end user, it is possible to continue to personalize the experience, and the agent still represents a proxy for the end user's intents and desires and behavior. I am excited at the width of the channel that agentic banking produces. Realistically, all the things Hima mentioned, entitlements, permissions, security, authentication, authorization, all of that is clearly table stakes for this space. We will work through the agentic protocols that come available and the evolution of that space, and we will help our banks step into an agentic world. The upside is that the broader, wider aperture for interacting with the agent and driving the agent to communicate the capabilities of the bank to the end user and the account holder through the agent, and to create this richer, broader behavior, I think is still present. Actually, it is more present than an FDX open banking interface or an Apple Watch interface, or some of the other kind of aggregation methodologies from the past. I am really excited for the opportunity that this new channel exposes, because for the past 20 years, we have done a great job of helping banks absorb new pieces of technology and mapping those technology onto their channel strategy while preserving the brand of the bank, the promise of the bank, and the differentiation of the bank in the market. When I talk to investors, I think they share a lot of the enthusiasm that we have for exploring that agentic channel with our customers and the promise that we could ultimately help them deliver on. Simultaneously, there has been news in the headlines recently that some large banks have signaled they are not going to let outside agents connect to their institution at all. On the face, that could potentially sound like something that is difficult for the end market that we serve. Adam, I will start with you and ask, how would you want investors to think about that news and what it means for a company like ourselves and how we serve regional and community banks with our partnership? Yeah. I think to the extent that a financial institution says, I don't want to have any agentic surface available, and I don't want agents to connect, it underscores the thesis about how crucial we are to the bank and how the mobile and digital channel really drives a lot of that behavior. At equilibrium, I think this looks a little bit more like the aggregation story that started 20 years ago. Banks and credit unions said, maybe I don't want to be aggregated. Maybe I don't want to provide data to Intuit or later on to Venmo or to Autobooks or other kind of partners. Then end users, they vote with their feet and their wallets, right? They say, if it is important to them to get that connectivity, if it is important to them to get agentic banking, they will provide that feedback to the financial institutions, and they will make decisions that are reflective of the capabilities that their bank supports. I think it is rational for some set of institutions to say, I am not ready to have agents connect until I have a technology strategy that allows me to roll off the incremental risk of the agentic workflow. If you think there is a bank in the U.S. that is going to take the position of, I am never going to allow any agentic connections, I am not sure that that is durable for the long term. If a customer in our base wanted to do that, we would absolutely support it. I think this is a for now kind of decision and not a long-term decision. There are a lot of questions to be answered around how to manage the risk in the channel, to secure it effectively, and to make sure that the experience is aligned with the way that the bank wants to show up. That is where the value is. For an FI that needs some time to do that, it totally makes sense. Hima, would you add anything from your perspective? Yeah, maybe I will connect what Adam said, right? It is a matter of when, not if, and it depends on when do the banks get comfortable, and they are going to take their own pace at which when they get comfortable with exploring the strategy and making it. There was recently a good blog from Satya Microsoft on what do financial institutions or any other enterprise trying to make personal agents or a model integral part of the strategy, what is the expectations, right? Observability, auditability, control, containment, incident disclosure. There is a lot of these things that, again, this exposes a surface area, and our financial institutions are looking for us to give that confidence and then use the technology, the digital banking, and the fraud stacks to go expose the information to these personal agents, right? That train has left, as in they are using it, they are using it through experiences that are flat, like aggregators. They are going to want richer experience, but they are waiting for us, the platform providers, to continue to enhance our technology strategy. We are working with them to continue to deliver that capabilities through the MCP endpoints that we announced a couple of weeks back at our Dev Days, more ways for them to go on this journey. Great insight there. Let me shift to our next theme, a little bit where we talk about our risk and fraud business. Adam and Hima, when I talk to investors a lot this year, cybersecurity has been a pretty strong thematic trade this year, and it is not hard to see why. Demand story rather than a cyclical one. AI is raising the threat floor permanently, and buyers are consolidating onto platforms instead of building their own defenses. That same AI of being weaponized is what these vendors sell defend against, and we see these forces at work in our risk and fraud business. Adam, maybe I will start with you with how has AI changed the fraud landscape, and more specifically, where do we have the right to win relative to that ecosystem of core processors, payments names, and maybe even pure play cyber vendors that are in the space? That is a great question, Josh. If you will permit me a brief metaphor, I think of the way fraud happens almost as a market clearing activity, where the threat posture of financial institutions represents the supply of available, achievable targets. The tooling and the capabilities and the desire of threat actors to commit fraud and exfiltrate funds represents demand. AI is interesting in that it moves both curves, because in the same way that AI makes it faster for an attacker to create a chained or complex exploit to try and drive cyber or to execute fraud with deepfakes or social engineering, that AI tooling is also available to the defenders on the other side to reduce the supply of available attackable targets. At equilibrium, I think we end up with a shift that doesn't really move the needle much in one direction or the other for institutions that effectively take advantage of AI. This is where our right to win is so crucial. The first piece is, if you are deploying software that is open to the internet and that software is authenticated, you want to be a company that does that all day, every day. For an FI that says, maybe I can build digital myself. Maybe I'll vibe code it. Maybe I'll get a toolkit and I'll host it myself. The current threat landscape makes self-hosting, self-deployment, self-securing an application very, very unattractive. That really works in our favor because we are able to more rapidly apply AI to resolve issues. Just today, there's an exploit for PHP, which runs about 70% of the public web-based internet, that everyone is going to have to go patch and address. Every one of our customers is going to call us and ask, when are you guys going to have those patches in place, and what's your mitigation strategy? Instead of turning to their internal team and saying, are you prepared for this? Can you do this? Are you ready? This is the beginning of a new form of weather and climate in the space. This is not a one-time activity. There will be more exploits. We will have to be aggressive with them. Our right to win comes from our strong operational foundation and our focus on it every day. The other piece that happens here is that the application of AI to the security workflows, application security, social engineering resistance, payment security, long-form identification of compromised accounts. There's a lot of complexity there, and it takes two things to do this well. One is the kind of talent that you have to attract en masse to a traditional technology company, and then the second is enough data to drive those models effectively. For our customers, the point of interdiction of the payment or the login, it really sits with Q2. The operating, orchestrating infrastructure that allows us to step into a workflow and safely secure an end user, and then also let them clear a payment that maybe was identified because of a behavior that was not fraudulent, but simply anomalous. All of those things live at the orchestration layer and the system of context that we deliver. Then we have a breadth and wealth of data that a core provider or a standalone cyber provider doesn't have. If you're someone that works at the perimeter and you're doing things like bot detection through keystroke cadence identification. That is a fantastic technique. We have partners that do that. But they don't have the data that underlies end-user behavior inside the application, end-user behavior across applications, or end-user behavior across the financial ecosystem. Whether it's the data, the talent, or the operational workflows that actually require securing, the fraud position that we are in is as strong or stronger than we've ever been. The advent of AI, even though it makes attackers and defenders both stronger, creates velocity that is going to be a real tailwind for us. Our customers are expecting and really needing us to win in this space to help keep them safe and minimize fraud losses without ramping friction through the roof for their customers. That intersection is where the right to win starts for us. That's great. Hima, maybe you can add a little bit of color too on that and be specific around the products and the business lines that we're attacking with that opportunity. Absolutely. Fraud is a great business for us. It's one of the fastest-growing product lines. We talked last time about when we think about AI, the account holder's experience, the back office experience, but then the fraud experience where we launched an account takeover product called UAM. It's probably one of the fastest-growing products, both from how we are building it and how fast we are taking customers live. It is all driven by the fact that as there are more channels getting in, the account takeover gets to become a bigger problem. As an example, account takeover works by taking signals from various data streams coming in, and we didn't have a detector for agentic interface, and we were quickly able to add that detector because the customers were seeing fraud coming from that channel. This is an example of how our fraud products are able to catch these by getting the product and the signals into the customer hands quickly. If I simplify this from my own sake, every new channel that gets added to how customers, consumers interact, when people had to walk into a branch, there was fraud, but minimal, because you had to depict someone else. When web came in, when mobile came in, it increased because of the number of channels and the approaches you take with social phishing and all of that became bigger. Now with the agentic channels, the fraud operators have a bigger surface area, so it becomes a much bigger opportunity for us because now we are looking at signals that are coming in at 20x, 30x, because these personal agents are actually kicking off a bunch of sandboxes or virtual machines and using those to come into the banking financial institutions. Naturally, the fraud operators are going to go, I don't know, social agent phishing, whatever the new term's going to be, and start trying to use that channel. I look at this as even becoming more important as the surface area gets bigger for us to make that an integral part of how we think about fraud. As Adam said, now we are integrating with the cyber endpoint because that signal also becomes very important in deciding whether this is a fraud actor coming in or a legitimate action. So we are working much closer with this endpoint cyber. This merge of cyber signals coming in with the traditional, what we considered user signals coming in, is happening more and more. That enables us to do a better job, but also makes us a lot more stronger in this space as we think about our fraud business and how fast it's growing. Yeah, a lot of good color there. I appreciate that. So, maybe an adjacent conversation to that one is security posture. Investors talked a lot about this with me. As we think about the threat environment getting more sophisticated and AI raising the stakes on both sides of the equation, both how people want to understand a provider thinks about it, like the liability that we may have serving our customers, as well as our own architecture and our resilience. Adam, how do you think about how important security posture is, what it means for the demand environment for our digital banking business, and what customers are looking for and asking for us right now? Yeah. So security posture is really fundamental for us. What does Tommy Lee Jones say in men in Black? There's always an alien invasion. If you don't work in this space, you may not realize that for incident response teams and incident preparation teams, there's always a new CVE. We've had two substantial 9+ level CVEs this week, one around breaking out of virtual hosts into the host operating system, and that's a hyperscaler level problem that everybody's working on patching right now. Then the second is this PHP issue that's come up in the last 48 hours. At Q2, that cycle of identify the risk, mitigate the risk, clear the risk, make sure the risk doesn't recur, there's a team of people that doesn't really do much else. That is their day, every single day in and day out. Turning that into business as usual is really nontrivial. What is changing is the velocity with which you have to get the patching done. That is impacting Hima's team to some extent about the way the SDLC is operated. We have a strong partnership between the operations organization that drives cloud operations, Hima's team on the engineering side, and then the internal teams around compliance, regulatory, and security. The more deeply they can partner and the faster they can turn, the more quickly you can close whatever gaps there are in the exploit chain that attackers are seeking to pursue. This is not something you build in a month or six months or even a couple of years. This is something that has taken us years and years to build of operational expertise and repeated time on task among those teams. Our customers ask us constantly about that posture for both cyber and fraud. We are refining it continuously, and we have a substantial labor investment of some of the best people in the business in doing that. In addition, they are using AI to evaluate our systems. They are using AI to improve our SDLC, and so we are working to match or potentially even exceed the velocity of attackers because posture is not static anymore. In the same way that your lead against the attacker is something that ebbs and flows as new information comes to market, you have to be running every day, even when there is not a new exploit or a new attack. In addition, there are new capabilities that we are bringing online. We just recently completed a posture measurement of our agentic approach around the Q2 Assistant product, and that was done with a third-party independent auditor, the AIUC, and we have completed the AIUC-1 assessment for Q2 Assistant. I am sure that is the first of many new standards that will come about for assistant safety and sanity and quality. Being at the front of the curve and close to market on those elements is how we establish credibility with our customers because they manage risk, and they manage risk with standards and practices and controls. Leaning into that set of capabilities and exposing to them our controls, our practices, and then the way we operate is how we build trust, and that trust creates stickiness for them with us. That trust also creates a reference ability that allows us to go and win new business. We have always talked about our investments in security posture, cybersecurity operations, and fraud operations. I think it is actually, again, becoming more important going forward because of the changing landscape, and we are comfortable that we can match the velocity of attackers and continue to win on that in the market. Hima, any color from your side? I will give one example reference to what Adam said as how the SDLC, the software development life cycle, is sort of moving at much, much faster pace in the context of security as more vulnerabilities are being found. The pace at which we have brought in security agents that look at the vulnerability, figure out the updates that need to be made to take care of that vulnerability and automating that pipeline, that is an example of how we are leveraging this technology to strengthen our posture. As the PHP, as an example, came out, we are able to now fix it much faster. One of the things, I am going to quote Satya again, the most trustworthy super intelligent system will not be the one with the model we trust most. It will be the system that enables us to trust the model the least. The financial institutions are looking for a system that assumes there is more inherent risk in the technology, and what is built around from a control, security, auditability, observability, containment. I think that is where our posture is continuing to strengthen more and more, because that is how we have been working, not just about how we operate the system, but it starts from how we look at requirements, how we do our software development life cycle, how we then operate the system, and how we look at our fraud SOC centers that give us feedback back into the product and the engineering teams. It is this continuous life cycle that is core to how we deliver the system is what is getting more and more important as this technology goes forward. Great color and perspective from both of you on that. Appreciate that. Let us go into something that we talked about continuously this year, starting from our first session in the year, which is some of the AI solutions that we have actually put out into the market this year. Hima, we are in early access, have customers across UAM, Q2 Assistant, Q2 Code. Maybe talk a little bit about what we are seeing now that we have put them through that cohort and what are they valuing from these solutions? Yeah. The last conversation, we talked about those three rails, from how we are using AI agentic and assistants to drive a developer environment, a back-office environment, and the fraud capabilities. Two of the solutions are the furthest along. Q2 Assistant, which is our AI agent for customer care, enables our financial institutions to take on their workflows that are manual or that involve spending their time across multiple tools for making things like entitlement changes, password resets. This product is enabling them to use the agentic way to get it done in less than a minute, things that would have taken them sometimes an hour or even longer. We are seeing a significant interest from the market because it ties back into their operational efficiency and how their CSRs are working today. That is our first agent that is out there, and we are seeing a lot of traction. The second one we talked about in the fraud space is our UAM product, which is our account takeover and fraud solution. It watches various signals coming from digital banking, but also outside with various detectors. We have a technology that enables us to build these detectors much rapidly as we get the feedback. One of the significant changes we have made is how fast it can get deployed into customers' environments and how fast they see the value. These two were in early access, significant traction, and we are pretty close to general availability before the end of the year. That's the couple of solutions that are furthest along. One of the things we are seeing more and more, I talked about when you used to talk about cloud a couple of years back when we were on that journey, there was a lot of hesitation and so on. But with our customers, when you think of the adopter curve, early innovators, early adopters, early majority, we are able to cross a chasm, which the software folks talk about, from early adopters to early majority in a lot of these AI products. That is a lot of this kudos to our financial institutions who are thinking about agentic operations of their financial institutions and telling us, asking us, and working with us to take these to go into production much sooner. They are deploying fast. Things historically, it would take a bunch of quarters to take a product, deploy it through our. Once engineering puts it out, the delivery team has to put it in the ground, work with the customer. That cycle for these two products, early access customers in weeks, not quarters, not months. It's come down to weeks. This combination of customers thinking about and using this as a competitive advantage. That is the key. They're looking at it as, if I can turn this on much faster than some other institution, I'm able to get that value to their customers much faster. They're looking at these agentic AI solutions as a way to defend their institution, get more efficient at their operations, and not just as a defensive box to check. Pretty excited about it. We showed a lot more of these agentic products and products that leverage AI but do not show up as agentic at our Dev Days conference a couple of weeks back. We are going to come back with more numbers, keeping it qualitative, but seeing good tailwinds on it. That is great. Adam, anything from your side? Yeah, just one thing, which is the AI-driven SDLC that Hima's team has, and the way that product managers can approach evolving and iterating a product is much higher velocity than it was with previous software development techniques. A lot of the feedback I am getting with customers when I talk with them is they are excited at how quickly we can go from a conversation with them to a prototype, or go from a prototype to something that really meets their needs, because we can turn on their feedback much more rapidly. As you shorten that cycle, it really rewards them for getting engaged much more deeply in the product delivery process. We are starting to see a lot more engagement from customers while we are building the product, as opposed to we go ask them what they need, we build it, we bring it back. They say, it is not quite right. We go away, we build it, we come back again. There is a much shorter cycle, and so the innovation pattern and the interaction pattern for that is, it has changed pretty dramatically. If you look at some of the things that are happening with Q2 Assistant or with UAM, and these are products with a lot of traction, a lot of demand. Part of the demand and traction, I think, comes from the fact that our customers are comfortable knowing that we can tailor these products rapidly towards their needs and adjust them on the fly. They are much more comfortable adopting early. Yeah. Great color. Clearly we have seen a lot of progress in a short amount of time with these solutions rolling out with our customers, and excited to see what is coming after that. I want to reground us with a conversation we had in our first session earlier this year, just to continue to reiterate with investors, although I think we have made a lot of these points already and just in conversation. But, I think it is worth repeating again for the investor community, and they are kind of circling on this same underlying question. I will ask a question I asked you all earlier this year and just see what thoughts you have on it, how your thoughts may have changed. But what does Q2 do to defend against a well-funded startup or a frontier model? Where would they struggle to compete with the Q2 business today? Hima, I will start with you. What is the advantage or some of the things you have already talked about just to underscore that makes it genuinely very difficult or hard to replicate what we do for our customers? Yeah. I am not going to repeat all of what I said last time. A frontier model is not a banking product. What it takes to create a digital banking and a fraud platform and a product is that integration layer, system of orchestration, system of context, and that extensibility that goes around it. Being able to now give, like I said earlier, a system that gives auditability, all the things that matter for a financial institution to be comfortable. A frontier model is a system of intelligence. That is about it, right? All the railing around it and all the layers around it are very important, and that is what we have been building over the last 20 years. Understand user preferences, understand how users move money, both as a consumer or as a commercial. That system is what is needed. Look, we use these frontier models all the time, right? We have partnerships with them, we leverage them, and they are also starting to see how to leverage and give that comfort to the financial institutions. I think about it as we both have to work well together to get the financial institutions comfortable with making this a channel. However, whether it is the consumers or the back office or the products. Adam, anything you would add? Yeah, I just think back on the last 20 years of building this business, and I would tell you customer intimacy and building domain expertise are a much bigger part of building the business than just writing the underlying code. As far as these competitors, I got introduced to one at Money20/20, and they told me how many Carnegie Mellon PhD candidate engineers they had on staff. I said, you guys ought to hire a couple people out of community college that are willing to get down in the ditch and dig around in the dirt with Fiserv, Jack Henry, and FIS, because the expectations of people that are brilliant CS people and the reality of what it actually takes to implement software in the financial services space are just two totally different things. I have used this metaphor before, but if you dropped all the basketball hoops to 6 ft, I could probably dunk. That does not mean I can play NBA basketball. I cannot run the floor, I cannot rebound. You could not slide a sheet of paper under my feet when I go to jump. So making one part of the process radically easier just increases the returns on being good at the other parts of the process. Having worked personally with Claude Code and Claude Cowork, I can tell you, if you are not a thoughtful engineer, not a software developer, not a computer programmer, a thoughtful engineer, you can get yourself out in pretty deep water with absolutely no motor in the boat by having vibe coding or even agentic coding drive a lot of the construction of software. There is a little bit of a concern in the industry that I think is warranted, that we may be building a set of new entrants that they do not understand what a race condition is. They do not know how to deal with data hiding and data safety. They do not really fundamentally understand security. I have faith that they are going to want to learn those things because that is what it takes to be a strong engineer. But generating code that works and generating a well-engineered application that executes crisply against your customer's needs, those are two different pieces. When you think about the subtleties in implementing the system of context and the system of orchestration, in managing user present and user not present workflows, in thinking about the design of applications. Just because I can draw screens faster doesn't necessarily mean I'm drawing the right screens. I'm excited that we can code faster, we can code better. That's fantastic. But it makes every other part of the business that we've built, the way we interact, the way we build and accumulate domain expertise, the way we solve problems, the way we engage with customers, that much more valuable than it was before. If you're a startup, I think, hey, that's great. Enjoy the vibe code. But you better belly up to the bar for all the other things you got to deliver to really drive an enterprise business in a complex integration environment across 15 or 20+ integration points. Then who knows how many channels we're going to have once agents start getting ramped up. I like our lead in the space. I like the way we've attracted talent and our relationships with customers and our existing capabilities. Maybe I'll ask you a question on the heels of that, Hima, which is occasionally, technology investors look at sectors, and while they appreciate the work that it takes to earn the right to be in that space, as you become an established player and you are longer, there's this potentially naive view or a fallacy that because you have existed for 20 years, like a company like ourselves, that now you are outdated and you have tech debt and there's architecture. If you field that question from an investor or potentially you field that from some of our customers, just by the age that we are, that somehow we are not the innovative company that we used to be. How do you address a claim like that points that our age and says that our architecture might be outdated? Actually, Hima, I'll start with you on this one, then I'll come back to Adam. No, this is something, as you all know, I am so passionate about. If they are referring to us being dated, yeah, we have 20 years of experience building these platforms. I go back to what I said with the two products that are having the most adoption, and it has been less than four months since we last talked, six months. If we had a dated architecture, we would not have had the ability to build a product, significant adoption, and we will come out with numbers, significant adoption in production, and we have not even gone GA. Think about a dated architecture cannot do this. It cannot build products so fast like Adam was talking about, leveraging agentic coding technologies and change our SDLC can still have the same controls and rails in place and deliver the products in production. That just one example of how, when people say, what is great about the architecture? That is just an example of the product, show how data architecture is, right? If you are able to ship products faster, get in ground faster, that is a reflection of new age architectures. The second claim I will make is, dated architectures do not show APIs, do not show MCPs, do not show how open you are. I will stand next to any other product that is in the market and compare the APIs that are exposed, the surface area that is available for integration into the product, extend the product, and how public we are in that, right? We had our second largest Dev Days ever, right? Doubled the size from last year. Every year we keep doubling. Developers are a good signal into how new the architecture is, how great the architecture is, because developers do not accept old technologies. If I put an old mainframe in front of them, not a lot of new developers know that. They are only going to work with technologies that are new, that are enabling them to upskill also. That is a second claim I will make when people talk about how new is the architecture, how modern is the architecture, right? The third one I will claim is, I was meeting with one of the biggest hyperscalers, and they are asking for feedback. I was talking about six months back, one of their regions completely went away. We were one of the only software providers that they have on their platform that was continuously up and running because we have a very scalable, active-active architecture. A lot of people said, including me, said, no one does that." This was us thinking so far ahead and saying, this is what our financial institutions expect from us. It costs us a lot to do that kind of things, but we invested in that. When we did the cloud migration and we went cloud native and we built stuff that enables us to deliver this kind of operational stability and value to our customers. These are some signals that should tell architecture is new. Developers are excited about it. It is operationally pretty scalable, and you can only do that with this adopting newer operating principles. Finally, all this usage of AI, both on the front, on the account holders, the back office, and the fraud side of it. With 200 partners, 2,000 developers that are building on it every day, they do not do that with old architectures, right? They want to adopt and build on new architectures on the least amount of friction they have on it. If someone wants to have a conversation on architectures and how new or old we are, you are always welcome. All right. Adam, anything you would add? Yeah, I think Hima covered that brilliantly. The thing I tell you is architecture is a broad word, and it can mean a lot of different things to different people. If it is just a list of buzzwords in your tech stack, then I do not know why people would spend time talking about architecture at all. The other thing I would tell you is the architecture of a product is really in what happens when a downstream call to a database fails. What happens when an end user suddenly hits a pocket of latency on their mobile phone? What happens when you have to switch from one AWS region to another? Those are the things in architecture that we think about, which is how do we design the information flow, the operational stability, and the resilience of the system. The way we express that architecture is which components do we choose, what languages do we write in, how do we code things. That ends up, in my mind, being less important than the underlying set of fundamental design principles. There is a cathedral in Iceland, in Reykjavik, and it is a staggering building. It is probably 400 years old. It is still standing. The same principles people used to build that building, we use to build modern buildings today. Probably different techniques, different materials, but I defy you to go look at a building that stood for 400 or 500 years in a part of the world where it fits in and claim that that's old architecture. I think everything we say here runs the risk of coming off defensive, but I'll tell you, the way we think about architecture is in terms of the way it manifests in the reliability, efficacy, and ability to solve problems with the system. That is as new as the thoughts we had last week. That's the way we think about it. That's great. I got one final question for both of y'all, and to round things out a little bit, I'll come back to where we started at the beginning of the year in the first session with this. We talked about our belief here at Q2 that we obviously believe AI is a huge opportunity for us. As the years progress, I'll put this to both of you, where do you sit and how do you think about that now? Do you feel the same way? What has changed in your assumptions over the last six months? Adam, I'll start with you on this one. Yeah. I think the advent of AI represents both a very concrete risk and an extraordinary opportunity at Q2. The risk is a risk of inaction and a risk of inertia and a risk of continuing to think about the problem the same way, even though we have new tools for dealing with the problem. That is the risk, is not embracing AI. The opportunity is if you embrace AI around moving faster, building code faster, taking customer feedback and running it through sentiment models and understanding, building a context for our relationship with the customer that everyone in Q2 can interact with. Those are extraordinary opportunities to solve problems we've never been able to solve before. The technology shock that AI brings both raises the bar and raises the set of capabilities that we can take advantage of. Our biggest risk is the risk of inaction and not absorbing that. To be fair, applying AI to some of the problems that we've dealt with for 20 years, it is literally like a breath of fresh air. There are a certain set of problems like analyzing 200 support cases over three months with a particular element of a product where you can tease out some analysis. You can do bulk work that would've been very expensive to do and maybe you would've just skipped over it previously. The capability to understand at scale and derive inference from broad data that we've been collecting is extraordinary. Sometimes I feel like we've had this data and we've done a good job with it, but somebody brought us just an entirely new tool for looking at and understanding the data. The same way we have an entirely new tool for trying things. I will tell you, about two-thirds of the stuff that I write with Claude Code I just discard because it is really cheap to discard it because I can always have Claude do it again. We are much more thoughtful about the way we curate and the way we approach things, and we are much less focused on the sunk cost or the opportunity cost of trying something new. Man, if there is anything that kills a 20, 25-year-old company, it is it being very expensive to try something new. It feels a little bit like being a startup again, net of obviously compliance, regulatory, operational scrutiny, et cetera. All those things you get when you get bigger. It is this nice mix of we can take three people and we can put them in a room and they can come out two days later with a prototype and we can say, It is a fascinating prototype. It does not work or it does work. If I can try 20 things in the time that it used to take me to try two of them, I get much, much better answers for the customer, and that is what drives the actual value. All of this comes down to identifying hard problems, producing customer solutions, and then capturing revenue as a result of delivering the solution. AI is a tremendous lever for us to pull on in that respect. The biggest risk? Doing things the way we always did them. That will be our biggest risk with AI. Great answer. Hima, same question to you. When the time we are recording this, we are bringing a lot of our customers for our advisory board meetings. What I said last time was our customers are looking to leverage AI through us, not around us, not by themselves, through us. Yesterday we did the customer advisory board for AI transformation. Packed room, so much conversation about what they are trying to solve, what do they want us to do, how do we give them that comfort that the nondeterminism or the intelligence that could go in different ways, has the right guardrails, all the stuff that we talked earlier in this conversation. I am excited even more than six months back about how we are able to leverage it internally from a productivity, efficiency, quality standpoint, but also to Adam's point, deliver the products much faster, as we talked earlier with some of the products we have seen. Like Adam said, I am giddy as hell with all the excitement that is there. Startup-ish. We are building new products. The best part is customers are adopting it. That is what excites me. That is the best place to be. It is a significant accelerant to how we build, how do we deliver, and how customers are getting value. Man, this is a great time to be in technology. Great answer. With that, I will go ahead and close our second session here. Hima, Adam, really appreciate both of your time again and all the insight and candor you shared today. It is exactly the question investors are asking right now, so I appreciate you being able to explain these things clearly with them. To everyone that is joining us, thank you for being here. Thanks again.