Welcome, and thank you for joining today's Asana investor webinar. Here is our forward-looking statement. You can also find it in our published deck after the webinar concludes. Over the next 60 minutes, we have a lot to cover. Let me give you a quick agenda. You'll hear first from our Chief Executive Officer, Dan Rogers, who will set the context of why this moment matters and what Asana has built to meet it. Our Chief Product Officer, Arnab Bose, will walk you through a live showcase of four new agentic apps we launched last week at our customer event in London, the Work Innovation Summit. Our Chief Financial Officer, Aziz Megji, will connect the product story to the financial opportunity. We'll open it up for Q&A. Please send in your questions through the Q&A chat box in the webinar. With that, I'll hand it over to Dan. Thank you, Eva. Exciting times for Asana. Last week we had our Work Innovation Summit in London. What I thought I'd do for you all today is talk you a little bit through the strategy that we shared, the differentiation of our platform, and also, as Eva mentioned, our brand new products that we're bringing to market. Let's discuss that. The first is our strategy. It all begins here with this idea that the future of work is changing. We're going to want to work faster than ever, plan better than ever, ship more than ever, launch bigger, and in fact, get even more stuff done. The reality is, our personal productivity has indeed increased with AI. Our personal productivity has gone up manifold. We're producing more documents, more code in our everyday lives. As you all know, that hasn't actually translated into productivity in our organizations and for our teams. In fact, some stats show that as little as 5% of organizations can note any particular improvement in their productivity. This is the great AI gap, and that is what Asana is going after. Because the way to actually create that productivity is through the workflows. It's agentifying these workflows. If you think about any company, any company is just a collection of these workflows. When I speak to our customers, they have a long list of potential workflows that they want to agentify. These are workflows that hitherto have been very manual. These are the things that actually affect their productivity, that actually slow them down. Why aren't more companies agentifying those workflows? What's been holding them back? As I spend time in the field around the world, the first thing I hear is it's very hard to get started. It's hard to discover agents. Most companies don't have a menu of agents that every employee can just pull and pick from. Most companies are worried about producing such a thing. How would they even deliver that to their employees? They're also worried that if they do so, that those agents have no framework in which to operate alongside their team members, that those agents won't be necessarily good team players, that humans won't be in the loop in the right way. They don't know how to coordinate those agents. They also worry about the programming of those agents. Who's going to onboard these things? Who's going to ramp them in the right way to make sure that they follow our way of doing business? Finally, if you're a CIO or you're an IT enterprise leader, you're really worried about AgentPalooza. You're worried about agents running amok that don't have the right data controls, security controls, or even cost controls. These are real impediments, and this is where Asana comes in. We announced Asana as the operating system for human agent teams. This is a place that your teams can achieve the real productivity and get the real work done that they wanted to do with AI and with agents. This is the place where you can agentify your enterprise. What is it that allows us to do that? I use an example here. I'm a tennis fan, personally, I just finished watching the French Open. I get to roll right into Wimbledon. I wanted to show a fictitious example is, say, the Wimbledon merchandising manager wanted to launch a new jacket. What does that look like in a world where humans and agents are able to work together? With Asana, the first thing that happens is we have onboarded ready-to-go teammates. If you remember, I said it's super hard today for people to discover agents and trust that those agents are ready for their enterprise. We have 30 pre-built agents that we have built based on the patterns of usage that we know from our customers. These are agents that hit all of the middle-of-the-bell-curve scenarios, whether you're in marketing, operations, IT, product teams, across the board. We did more than that. When anyone invokes any of these agents, the first thing that they do is they consume the Work Graph. If you look here, we imagined Houston, our launch planner, instantly starting to see as someone is writing in a task that they want to launch a new jacket, and they need to do so in the next couple of weeks. Our launch plan is going to kick into action and figure out from all the past tasks, past projects, past interactions between people, how did we launch products in the past? Is there a playbook? Is it either codified specifically in a written document or inferred from how we've done this in the past? From that inference, the launch planner gets going. It's actually able to create, from day one, a real project plan pre-populated with the tasks that it's going to take to launch this jacket. We talked about blocker number one, hard to discover, hard to get going. Our agents are out-of-the-box productive, ready to go. The second piece that we talked about is, in many organizations, they don't really have this notion of multiplayer mode. What does multiplayer mode look like? This is the place where a given agent, in this case, a brand consistency auditor that Houston, the other agent, invoked and recommended. This is to make sure that the design is done exactly on spec, the messages are done exactly on spec. Houston recommended that we bring this agent into the fold, brand consistency auditor. What's amazing with Asana is because it's multiplayer from the get-go, we automatically know who needs to program this agent, who needs to set the rules for this agent on what it should do. Whose work should we look at? You see here three people interacting with one agent to program and onboard this agent to make sure it follows exactly the specifications. This is an architectural choice that Asana has made, that all of our agents are going to be multiplayer. If you go a little bit further, the other differentiation is a thing called shared memory. What does shared memory look like? Shared memory is the promise that each new run of a project is going to be better than the prior run of the project. What you see here is one of these agents, this agent is called Sentry. Its job is to scan any notifications or any regulations that might affect this particular garment or any garment in general. It looks like there's some new, in this example, labeling requirements. Sentry picks up this labeling requirement, it does a little bit more than that. It knows that the last time that we had this labeling requirement, we actually had to change the labels out. In fact, we had to do 12 bespoke labels that complied with the EU regulations, depending on the region. Sentry's now come into this workflow and recommended that we use these new sets of labels in the jacket instead of the old set of labels. This is shared memory. Shared memory is every new run of the project is better than the last one because we learned either from what the humans said or even how the agents interacted and where agents recommended efficiencies for the next run. The final differentiation is this idea of governance. We said that IT leaders are really worried about AgentPalooza. All of our agents are governed. They're governed in terms of the data that they can access, the permissions that they have, and the human approvals that they need to go through. In this example, Tally, which is the production ordering agent, wants to order 10,000 units based on forecasting. When we built Tally, we pre-described that a human will always be in the loop on any orders over 5,000 units, and only Sarah has the permission to do that run. Now that agent that was in that gallery is fully scoped and fully permissioned for the organization. Within, it actually describes how the human is going to be invoked. This is where our differentiation comes to bear. Four differentiators hit the four key blockers that are inhibiting the agentification of the enterprise today. As a result, when I presented this at WIS, most of the people in the audience said, "We need to get going. We need to get going tomorrow." Over time, we're going to get even smarter with these teammates. These teammates are going to recommend themselves as you go about your work. Instead of even having to go to a library to discover them, they will be ready and available and make themselves known to you. FedEx was one of our beta customers, as I described in earnings, FedEx have put agents into their AI Studio workflows. These agents hit both their sales teams, their marketing teams, and some of their ordering teams as well. As a result, they're able to go to market nine times faster. This is humans and agents working together in a workflow. Arnab's going to walk you through some of the products that we announced. Not only have we created this framework, this operating system for humans and agents to work alongside each other, we actually lit up that framework by launching five net new applications. If you think about Asana, we really had one historic application, which was collaborative work management. Well, starting today, we actually have five applications. Agentic Work Management, which is for all cross-functional teams, which evolves collaborative work management to now include all of those AI Teammates, working alongside, as well as the AI system, which we'll show you in a second. Asana Service Management for service teams, Asana Client Management for any teams delivering client work, Command by Asana for any developer teams. With our acquisition, Stack AI by Asana, now we have the ability to create these mission-critical cross-functional workflows across applications in an organization. To go a little deeper, we are going to have Arnab pick up from here. Awesome. Thanks so much, Dan. Hi, everyone. I'm Arnab Bose. I'm the head of product here at Asana. I want to pick up in one particular part where Dan left off with respect to Asana's differentiation, which is the Work Graph. We've been investing in this system which tracks who does what, by when, and how for well over 17 years. It's this interconnected graph of tasks to projects, to portfolios, to company-level goals that has clarity around the individuals involved in those particular Work Graph objects. Now we've introduced AI agents into that Work Graph as well. What's really interesting is not only the ability for the Work Graph to connect human beings, but to also connect AI agents on that same real-time shared ledger of who does what, by when, and how. On top of that, from a platform level, we've been adding in new primitives into the Work Graph as well. It's not just restricted to projects and tasks. We now have timesheets and budgets. We've got notes and meetings. We've got calendar items. We've got the ability to synchronize chats and a lot more. I'm going to pay that off in demos showcasing how these agentic applications take the power of these differentiators, like the Work Graph, like shared memory, like the human AI experience that we've got within Asana, and enterprise-grade governance to create real differentiation and new value for our customers. Let's dive a bit deeper into Agentic Work Management, which is the easy button for getting AI productivity into every team. As Dan said, it's for any cross-functional project. Think of this as the evolution, the AI era of collaborative work management. At Work Innovation Summit London, we talked about several customers who are already on their way in terms of adopting Agentic Work Management. You heard from Dan about FedEx. We had the Chief Digital and Technology Officer, of course, a global retailer on stage talking about how they've invested in Asana as their standard AI productivity tool to get to 90% faster campaign setup times. We also talked about interesting customers like Washmen in the United Arab Emirates, as well as Acerbis in Italy, which is a manufacturing company, who've all started using AI Teammates live in production. I would love to kind of bring this to life to you in terms of what is actually available within these Agentic Work Management products. Agentic Work Management is a combination of not just collaborative work management, the Work Graph, and teammates, but of four different technology innovations that we've built over the last year. The first is Dash. Asana Dash is your AI chief of staff. Asana Dash is a way in which you can interact with Asana's Work Graph, tasks, projects, and other elements in a chat-based way. It also has your back no matter what's happened in terms of giving you next best actions. I'll show you how this works in a demo. It's fully plugged into many different sources of data, not just Asana tasks and projects, but also your Slack, also your email, also your meetings and your calendar to glean what is the next best action that you need to work on in order to stay in your zone of genius and get your work done as an individual. There's a lot of productivity increases that come from investing in an AI chief of staff like Dash. The second is Asana AI Teammates, your pre-built, ready-to-go AI agents. You've seen examples of how they work in Dan's section, how they present themselves and suggest to take on work, and how they're pre-built. I would love to sort of go a little bit deeper and showcase exactly how Asana Dash and Asana AI Teammates work side by side to help you get work done. The third block is Asana's built-in automation and AI Studio. This AI-powered cross-functional workflows and helps you schedule tasks or trigger actions when events happen within Asana. Finally, we've increased our depth of integration, both inbound into Asana and from Asana into other third-party applications in a massive way. We've got MCP applications available already for Claude and ChatGPT Enterprise. We've also got plugins for Google Gemini and Amazon Q. On the integration side, there's a whole host of different important business critical applications that we are plugging into as well from Asana AI Teammates and Asana Dash. All right, now, I would love to show you how all of this works with a demo. In this setup, I'm playing myself. I've traveled to Warsaw, where we have a very large engineering team, and I didn't have Wi-Fi on the flight. When I land in Warsaw and I turn on my phone and it connects to the network, my lock screen is blowing up with notifications. I've got Google Workspace notifications, I've got Asana notifications, I've got Slack notifications. Because I've been out of touch for about 10 hours, it's going to be very hard for me to go through all of this and catch up on the workday. Now there's a moment of zen. You'll notice that there's a notification from Asana saying that my morning briefing is ready. This is a morning briefing from Asana Dash, my AI chief of staff. Dash has looked through multiple sources of data. It's looked through what I have due within Asana today. It's looked through my email inbox. It's looked through chat. It's looked through calendar. It's noticed that there's an email that's unread in my inbox that's associated with the Dash Launch creative production project. It's a note from a vendor saying that they can no longer support what we asked them to do. They've gone dark because they've been double-booked. In this situation, before AI, before all of this tooling of Agentic Work Management, I would have to maybe call up my team, find out what alternative vendors we could use, look through multiple different databases. With Dash, I can simply ask Dash that question. Again, because the approved vendor list is tracked and available within Asana itself, it can go ahead and glean that information. It has already got access to historical project product launches we've done in the past, so it knows what are the vendors we've used in the past and does a match of approved vendors versus vendors I've liked, and suggests that I should go with Brighton Company. I can simply talk to Dash via chat or voice-to-text and tell Dash to go ahead and post a decision directly on that task to unblock the team. I've gone from a complete lack of clarity, where my notification screen was blowing up. I might have even missed the fact that the vendor is now no longer going to make it, to being alerted about this critical gap for a project that is directly tied to one of my strategic goals for this quarter, to making a decision that unblocks a team that helps them move forward. There's one more thing that comes up, which is, there's a team, the Asana AI team, that's been waiting on a EMEA regional approval from me. Again, this is something that I missed because I was planning my trip. I can simply say, "Approved," and this is going to go ahead and update that Work Graph object, update that task, and unblock that team and get them off to the races. Super interesting way in which for an executive, for a senior leader, how Asana Dash works on their behalf to keep them in their zone of genius and help unblock their team across multiple sources. Not just Asana data, but emails, Slack, Teams, Calendar, and more. From the perspective of the team, what happens going forward is that they're unblocked, this triggers an Asana AI Studio workflow that sets up a bunch of different tasks that will kick off Asana AI Teammates. What this screen is showing is Asana AI Teammates not only run on the context of the Work Graph and the context of the individual that they provide within the task, but with every single run, they have this concept called shared memory, which makes them better and better going forward. If Aziz, Dan, and I all have access to the same Asana AI Teammate and we are using them in our tasks and projects, the really interesting thing is the three of us are coaching that Asana AI Teammate as if they're a member of our executive staff and getting them up to speed. That improvement in its ability is not restricted just to me or Aziz individually. All three of us can get advantage of it. It's literally like having a new person on the team who you're enabling with all this knowledge, all this context, and all this feedback. All right, what's happening now is, now that I've unblocked the team and I've asked them to go ahead and draft that campaign brief, Launch Planner is already working on behalf of everybody in San Francisco. They might have been sleeping because it's 10 hours separate from Warsaw. It's gone ahead and created that campaign brief, looking at historical runs, looking at all of the data in the Work Graph, and assigned it out to Stephanie and Christie to review. Perhaps Stephanie and Christie are on either the legal team or maybe they're in a different team that's sort of dissociated from marketing, and they don't actively work within Asana. They prefer working out of comments in Google Docs. Asana AI Teammates are plugged into Google Docs as well. When they create that brief, and when Stephanie and Christie go ahead and provide feedback as comments on that doc, this multiplayer experience where multiple human beings are interacting with an AI artifact, all of that can be incorporated by Asana AI Teammates. Asana AI Teammates work in a multiplayer way, not only inside of Asana, but also on artifacts like Google Docs that are outside of Asana, which is super cool. You'll notice that Kirk, who's on the Asana AI team, asked for that feedback to get incorporated. It's got incorporated, this particular campaign brief task is complete and off to the races. That was a good way of showcasing how Dash can trigger some work that can automatically generate results via Asana AI Teammates, then Asana AI Teammates work in this multiplayer way. Let's take a look at how Dash can help you with unforeseen issues, something that's a risk to your project plan. This actually happened to us within the R&D team. One of our PMs who was leading Asana AI Teammates was expecting a baby. The baby came early. Everything is fine. The baby is happy and healthy. It means we now have to find coverage that we were not expecting. You can simply talk to Dash and say, "I need a creative brief. I need competitive research. I need copy because we're getting really, really close to Work Innovation Summit London. Please help me out." It can analyze the work and start creating subtasks that can be handed off to AI teammates. Again, this is going back to what Dan was calling out, where we want to take the guesswork for the knowledge worker out of trying to understand how should they bring in AI agents, what AI agents to bring in, what AI agents are approved for use within my company, to you can simply talk to your AI chief of staff. Your AI chief of staff has your back. It knows all of the approved AI teammates that you have access to. These AI teammates with shared memory and the Work Graph context are constantly being improved by your entire organization, your team, and you can hand a task, and it'll go and build that first cut for you. So it's handing off all these tasks. What's going to happen next is if you say go, the competitive market researcher will be scanning across both deep web search as well as historical data. The copywriter will be generating copy, the creative spec writer will be drafting specs, and it could be in Word documents or Google Docs. Your campaign hero assets could be created. This is showcasing one of our deeper integrations. This is with Figma Make, where social assets are created directly within Figma for the Dash launch. I think I clicked one back too far. This is a really interesting vignette that's showcasing orchestration of multiple AI agents, and again, the AI agents being recommended directly by your AI chief of staff across the set of AI agents that that individual within your company has access to, all within enterprise-grade governance and auditability, all within the context of the Work Graph and all powered by really interesting concepts like shared memory. Now I wanted to end this demo vignette for Agentic Work Management by talking a bit about how Asana's data is available across a variety of other AI applications as well. In this part of the demo, let's say that Kevin, who is our Chief Revenue Officer, is heavily on the road, and he needs to stay up to date on what R&D is up to. He needs to know if he can pitch one of our upcoming products, like Asana Dash, to Danone, who's a customer in EMEA. He doesn't know for sure if this will be available in EMEA as yet. He can simply pull up Claude on the phone. Claude is connected directly into Asana, he can ask Claude, "Hey, what's the latest status on Dash?" All of this data that you're seeing on the screen is being pulled directly via Asana's MCP connector. You can go ahead and pull out status on whether the PRD is complete, what the risks are, and if he can actually pitch Dash to Danone during his customer meeting. The reason why we would have this is for single-player use cases where you've got an executive or somebody who's not directly in the project, and they just need to get status updates or things like that out of Asana. We want Asana to be available in all of those canvases as well and not restricted just to things like Asana Dash or Asana AI Teammates, where somebody has to make a conscious decision to dip into the app. Again, we want the entire enterprise to get the value out of the Work Graph. Get the value out of what we are able to accomplish with Asana's AI Teammates and the other AI features. So that in a nutshell is Asana Agentic Work Management, a completely reimagined way to go ahead and think about collaborative work management. It's now no longer just human beings coordinating projects and tasks. It's human beings and AI agents. It's no longer just projects and tasks. It's chat, it's email, it's documents, and it's built on these four fundamental features, Asana Dash, Asana AI Teammates, AI Studio, and MCP connectors and apps. That was just one of our five agentic applications that we want to talk about today. I'm going to cover off three more and then hand it back to Dan for Stack AI. Let's take a look at Asana Service Management, which is our AI-native enterprise service management desk for HR, IT, facilities, and legal. All right. A question would be like, "Hey, what is unique? What's interesting about Asana Service Management?" First of all, we are leveraging all of the AI infrastructure work we've built and all the integrations into chat tools to provide instant AI resolutions in the flow of work. It's a 24/7 AI agent that automatically deflects about 50% of routine requests, and it can be present in Slack or Microsoft Teams or email or in Asana portal. The second thing that's even more interesting is for questions that actually become tickets that a human being has to go ahead and resolve, we've built a self-learning knowledge base. The process of resolving that ticket automatically gets codified as a knowledge base article that a human being can read or can be leveraged via instant AI resolutions. Again, the process is building on the foundational platform work that we've done for things like shared memory that you saw earlier on. One intuitive intake for every team. There are multiple internal teams that have help desks or service desks. It's not just the IT team for break/fix IT issues. It could be your legal team, it could be your finance team, it could be your creative team. This is something we've historically seen a lot of in Asana. There's a lot of Asana customers today, I would say about 20% of our existing enterprise customers, where Asana sold into the office of the CIO or the IT team. They're using us already today side by side with ITSM products because Asana is really good at providing this single desk for all of the enterprise service needs. It's also really good at the last thing, which is when a ticket is no longer a break/fix ticket, but actually has to be a project, like you're rolling out an upgraded product, or maybe you're moving from one CRM product to another. Anything that's a project is really, really great to track in Asana. We see this use case today where we are already being used side by side within these IT deployments when requests turn to projects. Asana Service Management will have that seamless integration where you can go from request to projects in one click. Of course, project management will be part of the package as well. Let's take a quick look at what this would look like for a customer who's deployed. The IT desk or maybe people within these various departments, like services or workplaces or legal, are drowning in a sea of inbound Slack messages. That's happening because nobody particularly wants to go ahead and raise a request via the IT ticketing portal. The historical legacy IT ticketing portals are places where questions kind of go to get stuck, takes a long time to get a response. The IT teams or the help desk teams themselves are overloaded. We have to get to a better way. We have to get away from this legacy enterprise service management where things are just sitting in these queues and they're costing a lot of human labor to go and get a resolution. With Asana Service Management, when that ticket gets raised, and that ticket could be raised in a variety of places, via portal, via Slack, via email, the first thing that happens is our AI infrastructure catches it, automatically routes it to an expert AI agent, and tries to go ahead and resolve it without it ever reaching a human being. This is, again, via all of the AI infrastructure work that we've built for Agentic Work Management. We've been deploying Asana Service Management internally already, and we are seeing pretty good AI deflection rates. We believe by the time August comes around, when this is going to be in early access, we can get it to that 50% number that we are pitching. The first thing is, okay, all of these input channels, how do you go ahead and automatically deflect them so that they don't become a ticket, they don't even hit a human being? The next thing is for something that actually requires review by a human being. This legal review for a vendor's NDA, this is probably something you don't want to get auto-deflected right off the bat. When it gets to a person, what happens is that interaction with the person is codified in Asana's Work Graph, and we can go ahead and incorporate all of that learning directly back into the finance knowledge base. The next time a question like that comes up, the Asana AI Teammate can take a first crack at getting to a 90%, 99% good resolution. The amount of human interaction time, even for a ticket that requires human oversight, can be driven down massively. There's a sneak peek early preview of what we've been doing with Asana Service Management. Again, this is selling into existing customers that we have, as well as growing our base in terms of new accounts we could target with a specific job to be done. We've also got a whole host of design partners we've been working with. As I said, we've rolled it out internally and we're seeing really great agentic AI resolution rates. We've also got NYU, Callen-Lorde, UpGuard, LEAP, Array, and Rycor as design partners for Asana Service Management. The second product I want to talk to you about is Asana Client Management. This is all about building lasting client relationships on an AI-native platform that's built for agency work. What does this mean? Let's dive a bit deeper into what we've got here. Something that you may not be aware of is we have a large set of existing Asana customers today who are already using us for agency work. They're using us to track resource management and capacity planning. They're using us to track their project work internally across different teams within their agency work. What we haven't provided till date is this branded client portal to complete the journey. How do you do intake? How do you have a clean, branded client portal so the client can log in and see the status of their projects? Again, how do you connect up these newer Work Graph elements like meetings? How do you connect up these newer features like time sheets and budgets? All of that new Work Graph content, as well as all of the new AI platform capabilities, are being combined together along with this new branded client portal so we can complete the journey for client work. Unifying all communications, ensuring multiple agencies are productive with AI agents, accelerating work across the business with agentic capacity planning, statement of work creation, client-ready asset production, status update drafting. All of these jobs to be done are now connected under one single umbrella. It's super cool. This is also going to be available in the August-September timeframe. It connects the dots, not only for these existing customers who've been using us already for project work within their agency businesses, but also attracts net new customers who might be concerned about, "Oh, I don't want to bet on multiple products. Asana is great for project management, but I need the client portal." Now we're eliminating all that choice. Just go with Asana Client Management and complete your end-to-end job to be done. Oh, sorry. This is a slide that talks about all of the existing professional services teams that are managing client work in Asana today and clarifies why I am excited about it from a product strategy perspective because there already is clear indication of product market fit, and we know who the ideal customer profile is. All right. Great. Now I want to take a little bit of time to talk about Command by Asana, which, from an R&D point of view, is super interesting because it's a way in which the Asana research and development team has been working probably for the last year, where we have gone all in on Asana to track the entire product development life cycle, to trigger coding agents, to trigger code review agents, to do our security and compliance processes. We've been seeing phenomenal improvements in productivity and cycle time. Because this was a highly customized way of deploying Asana, it was not something that we were able to bring to bear for our customers in market. Command by Asana is a productization of that end-to-end experience. A good question would be, what is the value prop for Command by Asana? From a customer's perspective, why should they change now, and why should they change to Asana? A really interesting thing that's happening in market today for engineering teams is the rate at which you can generate code is faster than ever before with these really cool coding agents like Codex and Claude Code that are available in market. The problem that most companies are running into, and there's widespread coverage of this, where people are running out of AI budget. There's some commentary from Microsoft and ServiceNow and Uber about the amount of spend that they have, but they're not really seeing truly improved product delivery and cycle time. The reason why this is happening is coding agents are currently really good at plugging into your GitHub repo or your source code and then learning from that. What's not happening is an agentic way to improve the entire product development life cycle, from ideation to PRD creation, to ticket creation, where the ticket has all of the context required to then run the coding agent effectively, to take all of the decisions that happen in those loops, where you might decide to change the spec slightly or you might decide to react to a bug once you evaluate the first initial PR. None of that gets recodified back into the PRDs of the tickets. Ultimately, the final product that gets delivered is not connected to the rest of your planning and development life cycles around product launches or scheduling downstream activities and so on and so forth. We want to create that software development factory where you go from ideas to shipping products that your team can sell in the fastest and safest way possible. Ship faster with humans and agents in sync. There's three different things in here from a feature perspective. Cleaner tickets with f aster agentic output on repeat, no manual reconciliation of things like sprint planning and capacity planning, and always-on visibility into risk, drift, and dependencies. Because, again, this is all powered by the Work Graph and shared memory, as you do more and more projects within Asana, it can detect when you are running into a risk, when there might be drift between the PRD and the PR. What are all of your cross-team dependencies, where if you look at the Gantt chart of everything required to go deliver your product, how do you reconcile those issues? Those are the three key features that are part of Command by Asana. I'll kind of walk you through a flow over here, which is everybody within Asana, we all love to build. We've got product managers who've been building prototypes as well as fixing most of the customer issues. Of course, our dev team is all in on the latest tools like Claude, Cursor, and Codex. Our designers are also fixing defects and shipping visual updates as well. How are we doing this? What is this Command by Asana way of working? It's like a totally new way of going ahead and building product. We want to take this process of requirements, plan, code, coordinate, and ship, and convert every single step of the process into an agentic workflow. Requirements and planning are scattered across multiple different artifacts today. You might have a live meeting with your team. You might have a Word document that's tracking a PRD. We want to agentify that entire process, again, leveraging the platform components of Asana. When you're coding, again, once the PR comes out, coordinating across multiple people for code review or evaluating the security views is something that, again, happens in a disparate system. Finally, when you're shipping, that product marketing team or that actual executive leadership team within product is disconnected from the systems today. When they ask a question, let's say when Dan asked me a question of, "Hey, when is this thing shipping?" That's a very reasonable question, but it often becomes this sort of multi-pronged access request to figure out, okay, what does the engineering manager and one team think, and is the product marketing manager on that project in sync with them, and so on and so forth. We believe there is a better way. The better way is Command. Command helps you go ahead and author PRDs directly from those meeting minutes and notes. It helps you iterate over those PRDs so that you can go ahead and break them down into tickets that are ready for coding agents like Codex and Claude Code and Cursor to pick up with the appropriate amount of context provided by the Work Graph. We do capacity planning in a way that is highly coordinated and agentic, so you can coordinate across both human and AI agent tasks. Finally, you can plug all of that into Asana's project management tooling, and things like AI Teammates. If you ask a simple question like, "When does this ship?" Something like the Houston project planner teammate that Dan called out way before, and it is a part of the talk track, can instantly respond by saying it's still on track for June 4th. All right. That's a preview into a Command by Asana. We've got our R&D teams using it actively today, and I'm super excited about bringing this to market again in that September timeframe. With that, over to you, Dan, to talk to us a bit about Stack AI. Thank you, Arnab. Yeah, Stack AI is really the missing piece to the puzzle. We described this on our earnings, and I'll go a little bit deeper here. This was our acquisition. It turned out that most of our customers want to agentify these workflows. That many of these workflows, the most complex workflows, actually span across multiple systems, databases, CRM systems, order management systems, you kind of name it. What Stack AI has built is this ability to quickly visualize and automate any workflow with no code. You kind of see here a little bit on the right, this is literally the UI. They can drag and drop any of these workflows that hit multiple systems with pre-built integrations. They have literally built hundreds of integrations. They can build net new integrations very quickly. What this allows you to do is create rules that kind of move from humans to various other systems, and in this case, back to Asana teammates and Asana agents. What you end up with is that ability to visualize and imagine a workflow and how you want to automate it, and the rules that you want to set in place, and which bits you want to agentify and which bits you want humans to take care of. Stack actually, as a standalone product, is going to be commercially super viable. It's already a commercially viable product. It will also feed into all of those other products that Arnab just showcased as a logical extension of how you want to do service management, how you want to do some of your developer workflows. Stack AI both becomes a product and a capability across many of our other products. These are all governed, they already have met the highest requirements for federal and enterprise customers. That's Stack, and really, I sometimes describe it as the missing piece to the puzzle. Let's go to the next slide. At this point, we will talk a little bit about our right to win and our differentiation. Again, we covered a little bit on this in earnings. We described this in a much more visual way in some of the keynote that we just delivered. Just to set a little context here's kind of the journey that we've been on, our multi-product journey. Back in June, we launched AI Studio. AI Studio has had a very nice commercial ramp. Monetization really started to take hold. As you get towards the December timeframe, we start hitting some decent commercial milestones on AI Studio with many customers spending over $100,000 on that capability. Launching of AI teammates. We go from the beta of our AI teammates to GA of our AI teammates. At this point, we really have a couple of other products in our portfolio. We acquire Stack in June and launch Agentic Work Management. Through Agentic Work Management, AI teammates in AI Studio will be discovered now in the line of your work. They will recommend themselves as you go about your regular daily tasks. As we look then a little bit forward to the second half, our new product portfolio, which is all agentic workflows, all built for human-agent teams, is Agentic Work Management, Command by Asana, Asana Service Management, Asana Client Management, and Stack AI, all of which allow us to not go just further into other buying centers, but also deeper into the buying centers that we're already in today. Touching our differentiation a little bit. The first is these are all underpinned by our platform. Our platform has four very unique architectural differences. The Work Graph, which we think of as a ne ural network of the connections between all of these primitives of people, tasks, projects. This living plan that allows everyone to know who's doing what by when, and by everyone, I mean both humans and agents. Our multiplayer mode, which is the ability for humans to train, guide, improve, provide feedback to any of those agents. Our shared memory, which essentially self-improves every run of every project. Finally, our enterprise governance, which means every agent is automatically scoped and permissioned in terms of what data it can access, what costs it consume, and which approvals it can make on its own, and which ones humans are going to have to make. Built on top of that platform are five AI capabilities, and these AI capabilities all serve our products, which is how we'll go to market. These are the five applications that we will go to market with. This is the new lineup. This is the new Asana. We're now going to hand over to Aziz, who's going to describe what the financial implications of this are. Thanks, Dan. While we're still early in this journey, the initial proof points of our multi-product strategy give us confidence we're moving in the right direction. As we shared last week at our Q1 earnings, in quarter NRR has improved for four consecutive quarters and reached 97% in Q1. A lot of that improvement has to do with the expansion and retention that AI Studio is driving within our base. We also saw our technology customer base returned a year-over-year growth in Q1. That was after eight straight quarters of decline and then stabilization in Q4. Our AI product bookings represented 17% of net new ARR in Q1, which was ahead of our FY 2027 target of 15%. Our AI products are contributing faster than we had expected. At the same time, productivity improvements and operating velocity are translating into meaningful margin expansion, demonstrating that we can invest in innovation while improving profitability at the same time. Now m oving to our pricing model for this AI multiproduct platform. It's really about meeting customers where they are with flexible monetization models, ranging from seat-based subscriptions with AI-powered expansion paths to request and resolution-based, workflow-based, and credit-based offerings. The common threads between this is that custo mers can start with predictable platform subscriptions and expand as AI usage, workflows, agents, and outcomes grow. This approach provides customers with predictable costs and no surprises, while enabling Asana to align monetization with customer value and better matching the outcomes being delivered. This creates a scalable growth model with greater visibility into unit economics and margins as AI adoption grows. Want to just touch upon this reinforcing growth model that we're creating as we've transitioned into a multiproduct company and expanded into new buying centers and TAMs. Historically, Asana was a single-product collaborative work management platform with growth driven primarily by seat expansion, package upgrades, and then adoption concentrated in a handful of buying centers and departments. Over the past year, beginning with AI Studio and Teammates, and then significantly amplified by the announcements at the Work Innovation Summit last week, which we shared today, Asana has evolved into a multiproduct platform for human agent teams. We have multiple ways to land customers, expand across workflows and departments, and monetize value through both seats and consumption. That evolution expands our addressable market, increases workflow depth and customer value, and creates growth vectors beyond traditional seat expansion. The result is a reinforcing growth model with more paths to land, more opportunities to expand, deeper customer engagement over time, and really setting the foundation for durable growth acceleration and long-term value creation. With that, we'll open it up for questions. Eva? All right. Thank you. I guess what a lot of investors have in their mind is why is Asana launching these new agentic apps right now, particular Asana Service Management and Command by Asana. It feels like a change in your multiproduct and adjacent TAM strategy. Can you kind of talk a little bit about that? Yeah. Why don't I take that one? It turns out that we had been serving many different buying centers with our horizontal platform already. Marketing teams, IT teams, product development teams, operations teams. As they got more deeply embedded with our products, they began to describe workflows that they wanted us to build, agents that they wanted to bring to bear on their work as these new capabilities made themselves possible. We began a design partner progr am with each of these areas to try and figure out what they wanted from us next. It became obvious that they wanted bespoke applications, bespoke agentic workflows, and teammates that could operate within their teams. Hence was born, really an incubation mindset of bearing out these products for these particular buying centers, for these particular verticals. Yeah, through the design process and really how we launch products, we came to learn exactly what the requirements are and could build all of these off the same Work Graph foundation that actually makes everything make sense for the human agent teams. Great. Thank you, Dan. Another question we have is how do you win against ServiceNow, Atlassian Jira, and other incumbent with this new agentic apps? Arnab, you could take that. Yeah, sounds good. I'll break it down into maybe two different categories. Again, I'll choose Asana Service Management and Command. The framework that we use within the Asana product team is answering the question, why should the customer change? Why should they change now? Why should they change to Asana from whatever they're doing for the enterprise service management or current R&D processes? When you take a look at why should they change, within Asana's customer base, as Dan was calling out, we are already seeing about 20% of our existing customers be within the IT organization because they have a pain point around tickets that can't be serviced by those ITSM products when they become real projects. Th at was like an existing reason to change that introduced Asana into those companies in the first place. The second thing is, with the advent of AI capabilities, there's a massive push to go ahead and drive down internal operational costs. People want to agentify their workflows, they want to change now to something that actually provides that level of 50% ticket deflection, proactive coaching, and so on and so forth. When you take a look at Asana's differentiation in that area, well, first of all, not only are we able to deflect the tickets that can be answered by knowledge base articles with our AI infrastructure and capabilities, but we can build these self-learning kn owledge bases. We can connect up human interaction in a way which generates shared memory. We can connect up human interaction in a way that can elevate things that are no longer tickets into true projects. The project can work on Agentic Work Management. There's three levels of things. We're already in a bunch of accounts today solving the project management use case, even with our historical products. The second thing is AI is causing every single customer in the world who has a enterprise service management team to reimagine, reevaluate what would it take to make it agentic. The third thing is we're providing this connected, agentic way of solving that problem in a way that's not just ticket deflection, that's not just automatic knowledge base creation, but it's generating these end-to-end workflows, even for the most complex tasks. We believe strongly that we have a right to play and win a substantial amount of that market. The same thing can be applied to Command and the R&D processes. Again, historical tools are designed around sprint planning, ticket management, bug management for a largely human-driven process. That's human beings getting together, they're planning out capacity, they're doing things like story pointing, for those who have been in agile R&D conversations in the past. All of that is gone. There's a massive change in the way in which you work because the cost of actually gener ating the code is going lower and lower every single day. The problem that's happening is how do you set up the right context so that when that code is generated, that PR, that pull request, is something you actually want to ship. If you keep going back and forth with that PR because you're trying to prompt your way to the best possible outcome, you're going to burn through your tokens really fast, which is why you get all of these reports in the media today about people burning through their budgets as they've invested in AI coding. Again, Command is a totally different way of working, where you go from ideas to the entire product development life cycle in a fully agentic manner, contributing into Work Graph assets to create that company brain that makes it run faster and better every single time. Great. Thank you, Arnab. Maybe one question on go-to-market. You're expanding into IT, engineering, and professional service buyers. How will your go-to-market model evolve over time? Yeah, there'll be, I'd say, three themes. One is new buying centers, which means that we'll need to learn some new languages for those buying centers and we have the ability to do a lot more cross-selling within our accounts. The second is the criticality of the workflows that we'll be going after. We'll be able to, I'd say, go up in some of these accounts because we really are going to be attaching ourself to much more business-critical workflows that are the core of these enterprises. Then finally, because we'll be moving to some more consumption outcome type of meters, adoption will become even more important in making sure that we hold customers' hands to get those workflows lit up in the first place. Those are the ways in which I can see us evolving. Great. Thank you, Dan. Maybe just one last question for the group. If AI models continue to improve, why doesn't the value accrue to Anthropic, OpenAI, Microsoft or another platform company instead of Asana? Yeah. Well, sorry. Actually, Arnab, you want to go and then I'll go? Yeah, sounds good. Again, let's take a look at the advances that have happened in the models, even in calendar year 2025. They've gotten exponentially better. When you look at research reports from Goldman Sachs or McKinsey, actual productivity improvement within a company's outcome or job to be done, there's been no improvement. The reason for this is the reasoning models are amazing at going through tasks and sort of taking the context that they have and iterating through it. Most of the choke points now lie in all the scaffolding around it, the context, the shared memory, the human interaction. Like how does a human being even reason about the rate at which these results are coming out? We've already seen that data play out in 2025. Our thesis is that, okay, even if the reasoning models get better, the rest of the scaffolding has nothing to do with AI. It's actually hard data about context graphs. It's hard data about the multiple human-in-the-loop processes to get human beings to grok and understand what's going on, and so on and so forth. Dan, let me know if No, you're good. Please do say it. Yeah. That's fine. Thank you. That's good. Yeah. All right, that concludes our Q&A session. Thank you Dan, Arnab, and Aziz for your time today, and thank you for everyone who joined us. We covered a lot today, so we hope you leave with a clearer picture of what Asana is building and what we're positioned to lead this category, and how the financial models support this durable value creation over time. For any follow-up question, please reach out to me directly at ir@asana.com. We look forward to continue this conversation. Thank you. Thank you, everybody.