Figma, Inc. (NYSE:FIG) Q4 2025 Earnings Call Transcript

Figma, Inc. (NYSE:FIG) Q4 2025 Earnings Call Transcript February 18, 2026

Figma, Inc. beats earnings expectations. Reported EPS is $0.08, expectations were $0.07.

Operator: Well, good day, everyone, and welcome to the Figma Q4 2025 Earnings Call. Today’s call is being recorded. [Operator Instructions] I would now like to turn the conference over to Mr. Brendan Mulligan. Please go ahead.

Brendan Mulligan: Good afternoon and thank you for joining us on today’s conference call to discuss Figma’s results for the fourth quarter of and full year 2025. On the call, we have Dylan Field, Figma’s Co-Founder and Chief Executive Officer; and Praveer Melwani, our Chief Financial Officer. During the course of today’s call, we may make forward-looking statements, including, but not limited to, statements regarding our guidance and future financial performance, market demand, product development, growth prospects, business strategies and plans, partnerships, ability to attract and retain customers and ability to compete effectively. These forward-looking statements are based on management’s current views and assumptions and should not be relied upon as of any subsequent date, and we disclaim any obligation to update any forward-looking statements.

Actual results may vary materially from today’s statements. Information concerning our risks, uncertainties and other factors that could cause results to differ from these forward-looking statements are included in our filings with the SEC, including our annual report on Form 10-K for the year ended December 31, 2025. Our discussion today will include certain non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute [Audio Gap] for or in isolation from GAAP measures. Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation and certain other items. Reconciliations of non-GAAP financial measures to comparable GAAP measures can be found in our press release accompanying this call, which is posted to our website.

I would now like to turn the conference call over to Dylan.

Dylan Field: Hi everyone and thank you for joining today’s call. 2025 was a massive year for Figma, and the fourth quarter was our best quarter yet. I’ll share a few highlights. We delivered $304 million in revenue last quarter. This represents an accelerated year-over-year growth rate for the quarter, of 40%. Our net dollar retention rate for customers with more than $10,000 in ARR also grew 5 percentage points quarter-over-quarter to 136%. And we generated cash, with a non-GAAP operating margin of 14%, and an adjusted free cash flow margin of 13%, ending the year with $1.7 billion of cash, cash equivalents and marketable securities. Our growth and momentum show that our strategy is working. As AI gets better, Figma gets better and we’re shipping faster than ever.

In 2025, we expanded from 4 to 8 products and launched over 200 features, including new AI-native functionality. This momentum reflects amazing execution by our team. Thank you, Figmates. We’ve carried that same pace and product velocity into 2026. In fact, we’re accelerating. Just yesterday, we launched the ability to bring work from Claude Code directly into Figma. Let me show you how it works. Let’s say I’m a developer building an app that looks like this. Many developers using AI start in Claude Code. The terminal is familiar, fast, and powerful. So now I’ve brought this to a decent place. But if I want it to truly stand out, it needs to be excellent. I need to think about the ways to make it awesome. And that’s where things get interesting.

Part of me wants to keep polishing, tweaking spacing, adjusting colors, refining every last detail. And you can see, I’ve been painstakingly prompting AI, trying to nudge it toward perfection. But what I really need to do is step back and explore different possibilities. I need to see the big picture, to bring in the smartest people on my team and push toward bolder ideas. That’s what design is about. Design is about giving people the freedom to explore. It’s about asking what if? It’s about seeing the bigger picture and pursuing the best possible solution. And it’s hard to do that when you’re exploring one idea at a time, in a linear fashion, with one screen, one prompt, alone in a terminal. So, we’re changing that. We’re making design accessible even from Claude Code.

And I can do that by simply typing send this app to Figma. And when I open Figma, you can see the screen right there. These are fully editable design layers. I can adjust spacing, color, layout directly, which is much faster than all that prompting that I was doing earlier. So, now let’s go back to the app. I can capture any part of it and send it to Figma. Maybe I want to go to this specific state, so I can iterate on it more. Or perhaps I just want this card, because I’d like to explore how to make it better. In seconds, I can extract the key parts of the experience and send them to a shared canvas in Figma Design where my team and I can explore freely. And you can already see my teammates jumping in. Greg is exploring a completely different look and feel, it’s bold, and unexpected.

Anna is mapping the user journeys and identifying gaps in the experience. Now we’re not polishing one idea, we’re exploring many, together. I can build on their ideas using direct manipulation or even prompt AI for variations. What you’re seeing is the power of design in this infinite canvas, the ability to bring everyone together on my team to explore and riff on divergent directions, to refine ideas with the precision and speed of direct manipulation; now I can just use my hands to make edits, and I have the ability to zoom out and have the birds’ eye view of what’s going on, and compare things side by side. And once we’ve explored, we’ve aligned, we’ve landed on the best solution, we can simply go back to Claude Code and use our MCP server to bring those designs directly back into code.

Claude Code to Figma is one example of how we’re making it easier for teams to go from code to the Figma canvas, with a lot more to come. And of course, this builds on our existing Dev Mode MCP, which allows users to go from canvas to code. We’re excited about what we can do with additional partners via MCP to create a better roundtrip between design and production, wherever you start. And for many of our users, that work starts in Figma Make, either as a rough idea, a detailed PRD or an existing Figma design. And in Q4, usage of Figma Make surged. Weekly active users of Figma Make grew over 70% quarter-over-quarter. And, as of Q4, over 50% of paid customers spending more than $100,000 in ARR were building in Figma Make on a weekly basis. Figma Make has also unlocked new audiences and new use cases.

In fact, of all Figma Make files created in 2025, nearly 60% were created by non-designers. We’re talking developers, PMs, marketers and others inside the company, broadly. Let me share two stories from our customers that show how teams are adopting Figma Make. For the design and product teams at Cisco, deciding what to build and how to build it is a constant challenge. To move faster, they align by making, moving between Figma Design and Figma Make. Designers and PMs often work in the same Make file, passing ideas back and forth. PMs laying forth broad strokes, designers refining them in real time. That speed is grounded in a strong design system foundation in Figma, where teams work from a shared set of standards. Make templates kick off projects and can be adjusted to suit all types of purposes, increasing throughput across everything the team builds, from interactive research readouts to early-stage product explorations, and even custom internal tools.

Building on that foundation, a newly formed agentic design ops function uses Make to explore AI-native workflows often starting from static design files and turning them into interactive simulations. With Dev Mode now available through the Cisco App Store, many engineers who previously had view-only access have now adopted Dev Mode, improving speed and efficiency by working directly inside Figma. Together, these workflows form a continuous system in Figma bringing design craft, engineering, and automation into one connected flow. We’ve found that for many teams using Figma Make, speed becomes a compounding advantage. At Flexport, teams use Figma Make to solve company problems faster. Every year, they bring the top 150 leaders at the company together.

This year, they added a hackathon with this challenge stop coming up with reasons to choose Flexport. Instead, you have 24 hours to solve one of the reasons why buyers don’t choose Flexport. The competition run like a March Madness bracket had basically every team pitching their solution to one of those problems using Figma Make, showing working apps within a day. One of the winners completely re-did onboarding of factories to the platform, solving a longtime challenge. That idea is shipping to customers within the next few weeks. Another winning team used AI to process transcripts of customer conversations and then fed this data into Figma Make to automatically create custom diagrams. These diagrams made it incredibly easy for sales to contrast the before Flexport and after Flexport worlds for the customer’s supply chain.

Figma Make is the preferred tool for not only the design team at Flexport, but also for an even bigger transformation that’s underway, moving from a document culture to a rapid prototyping culture that solves problems faster. As the Flexport CEO told us the teams that do that with me are the teams that are doing really well. We’re especially excited to see how Figma Make is driving meaningful cross-platform adoption. In Q4, over 80% of Figma Make’s weekly active users on full seats also used Figma Design. To us, that means we need to go beyond features we’ve already launched. For example, the ability to copy UI generated in Figma Make as layers into Figma Design or, more recently, the ability to embed Make files as prototypes on the Figma Design canvas.

These are great, but we have an opportunity to drive toward more integrated capabilities that bring these surfaces even closer together. But going from code to canvas is only one part of the story. We’re also focused on completing the loop and helping teams go from design to production as well. When this happens, we want work started in Figma to flow easily into the tools developers use every day. With the Dev Mode MCP, which we launched last year, teams can pull design and codebase context built in Figma into their preferred agentic coding tools. Customers like GitHub have told us that Dev Mode MCP is a gamechanger. GitHub uses Figma to evolve and ship Primer, their design system, where even small updates can affect more than 7,400 design tokens and tens of thousands of lines of code.

And at that scale, tight coordination between design engineering is essential. GitHub uses Figma’s MCP server and Code Connect to surface real production design system code directly in Figma. Each component is linked to its canonical implementation, keeping design and engineering aligned. Changes can be validated early, before they cascade across thousands of tokens and components. Code Connect enables GitHub Copilot agents to generate against authoritative components improving accuracy and consistency from the start. What once required hours of back and forth during handoff can now move forward in just minutes. Beyond using Figma internally, GitHub is also partnering with Figma at the platform level. As a key partner in the GitHub MCP Registry, Figma makes its MCP server discoverable and ready to power AI-assisted workflows for developers using the GitHub product.

While velocity is critical, the best product teams are not defined by speed alone. You can go really fast and still get to the wrong place. These teams are also defined by their craft. And in a world where software is growing exponentially, design, craft and point of view are what makes the best products stand apart. But delivering high-craft creative work often means stitching together multiple tools, each optimized for a particular task. We’re working to bring more of these advanced capabilities directly into Figma, so teams can spend less time wrangling all these different tools and more time designing incredible products and staying in flow state. One way we’ve done this is through our AI Image editing capabilities, which we significantly enhanced with a new set of updates in December of 2025.

In just a matter of weeks, these AI image editing capabilities were used more than 10 million times. More recently, we launched new vector functionality in Figma Draw, Vectorize uses AI to transform simple images, like a hand-drawn sketch, into dynamic vector illustrations that you can then tweak, refine and scale in Figma. As one user put it, this kind of work used to be painful, and now it’s a click. It’s clear that our users crave more ways to do their creative work in Figma, which brings me to our Q4 acquisition of Weavy, now Figma Weave. Figma Weave’s AI image, video, animation and motion generation, alongside precise creative control, expands the creative work possible in Figma. Customers have told us they love how Figma Weave helps them enhance their creative process by bringing craft to everything from intricate compositions to show-stopping stage visuals.

One example of this is NVIDIA. For the NVIDIA CES keynote, the team set out to create a high-fidelity group shot of 20 unique robots for the massive 12K keynote screen. For a moment of this incredible scale, they needed a flexible workflow that allowed for rapid iteration without rebuilding the entire scene. The primary challenge was pixel density. Current generative models are limited to 4K or maybe 5K resolution, meaning that in a single pass, each robot would occupy too small an area to capture the fine detail. NVIDIA used Figma Weave to generate low-fidelity 3D models that locked composition and camera angles. Then they created detailed 4K versions of each robot to fit the final frame. A custom AI agent, also built in Figma Weave, enhanced rapid lighting exploration before the full scene was generated, upscaled to 12K, and selectively refined for detail.

The end result? A cinematic keynote visual powered by a modular, AI-driven workflow. In the future, we believe far more people will create across the Figma platform beyond the confines of traditional product development. To meet that opportunity, we’re pushing the boundaries of not only what you can create in Figma, but who can create in Figma as well. And we are accelerating into that future. AI offers a new creative starting point; it’s like clay that you can shape. The first prompt does not need to be the final output. That’s where humans come in. And whether that process starts in a terminal, a prompt box, with UI in the Figma Canvas, a hand-drawn sketch, Figma is the place where it all comes together. Design is where all of that connects.

With code and canvas; speed and craft; agents and human judgment. We’re excited about what this means for our users-and for Figma. We’re focused on building the platform that makes this future possible. With that, I’ll pass it to Praveer.

Praveer Melwani: Thanks, Dylan. We’re proud of how the team closed out the year with another strong quarter, punctuating a record 2025. Our total revenue in the fourth quarter was $304 million, growing 40% year-over-year and exceeding the high end of our guidance. For the full year, revenue was $1.056 billion, up 41% year-over-year, also above the high-end of our guidance. Sequentially, Q4 was our best quarter of net new revenue added and drove an acceleration in year-over-year revenue growth. Our new product launches supported both new customer acquisition and expansion-driving improvements across all of our key business metrics in Q4 compared to Q3. Our retention and expansion metrics outperformed expectations in Q4. Our Net Dollar Retention rate for paid customers spending more than $10,000 in ARR ended the quarter at 136%, an increase of five percentage points quarter-over-quarter and our highest rate over the last ten quarters.

Our Gross Retention Rate for paid customers spending more than $10,000 in ARR remained consistent at 97%, reflecting the overall durability of our customer relationships. Q4 demonstrated momentum across each of our customer tiers. We ended the quarter adding 951 net customers spending more than $10,000 in ARR and 143 net customers spending more than $100,000 in ARR, growing that tier by 46% year-over-year, a three-percentage point acceleration, relative to Q3. Breaking down growth across the quarter and full year, a few things stand out. First, we continue to see strong expansion dynamics, as our customers broaden and deepen their use of our platform, driving larger renewals. We now have 67 paid customers spending more than $1 million in ARR, growing 68% year-over-year.

Across tiers, customers are growing their seat counts, expanding into new functions and teams, and deepening their usage and engagement. Examples from last quarter include a hyperscaler doubling their footprint, with over a quarter of new licenses going to product managers, a top 10 global bank embedding Figma even deeper in key engineering workflows growing Dev seats by 69%, and a transatlantic airline going all in with Figma on a multiyear commitment to elevate all parts of their operations from booking and check-in experiences, their loyalty platform, and internal tools for crew and airport staff. The pull from our customers is real. Second, we’ve built deeper relationships at all levels within our customer base, focused on positioning and proving Figma’s value as a system of record across design and product development.

We are increasingly partnering not just with design champions, but with central IT teams on driving the adoption of Figma’s platform as a core part of their enterprise technology stacks enabling more teams across the organization to collaborate in one platform. And we are seeing growing demand across our customer base for our governance plus add-on, as enterprises place greater emphasis on security, compliance, and centralized governance. Third, we continue to invest in our international business. Our international revenue grew 45% year-over-year. While international users represented approximately 85% of monthly active users, they accounted for 54% of revenue in Q4, and we see meaningful runway for continued investment, with the most recent being our launch in India last November.

Finally, customers continue to renew into our new pricing and packaging through March of this year, which contributed a mid-single-digit benefit to full-year 2025 revenue growth. Turning to some key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release, which is posted to our website. Our gross profit for the quarter was $262 million, representing a gross margin of 86%. For the full year, gross profit was $931 million, with a gross margin of 88%. While customer adoption of Make and our AI features continued to ramp with Make weekly active users up over 70% quarter-over-quarter, improvements in infrastructure optimization reduced our cost to serve each user and led to stable gross margins quarter-over-quarter.

Our operating income for the quarter was $44 million, representing an operating margin of 14%. And for the full year, operating income was $130 million exceeding the high end of our guidance with an operating margin of 12%. On a year-over-year basis, our operating expenses increased as we invested in our people, infrastructure, and systems, to support the pace of our product development and strategic growth opportunities for our business. This was offset by the outperformance we recognized in our top-line and gross margin, which flowed through to our operating income. Additionally our full year non-GAAP tax rate ended at 14.5%, which we expect to remain consistent throughout 2026. Our Q4 Adjusted Free Cash Flow was $38 million, with an Adjusted Free Cash Flow margin of 13%.

We ended the year with $1.7 billion in cash, cash equivalents, and marketable securities on hand. As we previewed last quarter, Adjusted Free Cash Flow declined sequentially in Q4, driven by continued investment in infrastructure and AI, changes in the timing of vendor payments, and a one-time $25 million IP transfer tax payment related to our acquisition of Weavy. These impacts were partially offset by strength in customer collections. We remain confident in the long-term cash-generating profile of the business. Before turning to our outlook, I want to briefly address stock-based compensation and dilution. Stock-based compensation was elevated in 2025, reflecting the recognition of expenses attributable to the IPO, performance-based RSU vesting, the launch of our employee stock purchase program, and equity issued in connection with acquisitions.

These impacts were largely one-time and not reflective of our steady-state compensation framework. Looking ahead, as revenue continues to scale, we expect stock-based compensation as a percentage of revenue to improve. We remain committed to managing dilution responsibly. Now turning to our outlook for 2026. When we look ahead, we believe that Figma will continue to set the standard for how great products are designed and built. We are investing deeply in the business to define new AI-native workflows and better support our customers as they adapt to new ways of working. At the same time, we have always been disciplined as we scale our business with a focus on the long-term. For the first quarter in 2026, we expect revenue in the range of $315 million to $317 million, implying 38% growth at the midpoint.

And for the full year, we anticipate that revenue will be between $1.366 billion to $1.374 billion, implying 30% growth at the midpoint. Our outlook reflects the sustained strength and momentum in the business that we experienced in 2025 including benefits from our new products and offerings, seat expansion from new and existing customers, and international expansion. At this time last year, we had no customers consuming AI credits. Today, we’re seeing approximately 75% of paid customers with over $10,000 in ARR consuming AI credits on a weekly basis with adoption continuing to ramp. Our outlook reflects the seat adoption and usage patterns we’re seeing today. We’ll plan to refine our assumptions in the months ahead, as we continue to both learn from customer consumption behavior, and drive further AI adoption around new feature releases.

This March is when our model will shift to monetizing both seats and credits, a dynamic that is not reflected in our historical revenue results. We expect our full year non-GAAP operating income to be between $100 million and $110 million dollars. This represents a non-GAAP operating margin of 8% at the midpoint. In 2026, we plan to accelerate our investment in AI and inference, while building a world class team and go-to-market motion. As a reminder, while we are not issuing quarterly operating income guidance, there is some seasonality in our operating income. Our Q2 operating income has historically been impacted by our annual user conference, Config, and we anticipate a similar impact in 2026. We also expect adjusted free cash flow to be relatively consistent with non-GAAP operating profit for the full year.

To close out, we are energized by the incredible year we had in 2025. We added a record number of new customers, exited the year with accelerating revenue growth, while focused on product velocity. But we are even more excited about what is ahead of us, both for our customers and for the expanding capabilities on our platform. With that, I’ll hand it over to the operator for Q&A.

Q&A Session

Operator: [Operator Instructions] The first question comes from Arjun Bhatia from William Blair.

Arjun Bhatia: Perfect. Congrats on a very strong end to the year here. Dylan, if I can ask one just kind of philosophical question if we just step back a little bit. We’ve had, I think, a lot of noise made in the market about Agentic layer offerings like Claude Cowork and even OpenClaw. And I’m curious your perspective on what that means just for UI/UX broadly? Like does it make it more of a differentiator. Do you think like user interface gets pushed to the back as this new agentic layer emerges? Like what are sort of the puts and takes and the dynamics that you’re thinking about as these new tools emerge?

Dylan Field: Yes, absolutely. Thank you for the question for joining us today. So yes, I think right now, if you’re willing to hand off mission-critical work to agents and just to let them do it unsupervised, you’re a very brave person. But that joke aside, I think it is the case that humans will continue to use software and increasingly, agents will, too. And I’m excited about that. I think that this creates more surface for designers to work with and design and think through. I will say that I think that the discourse around UI and how agents will change UI or not change UI, it is a bit extrapolating from current state. And humans are really hardwired to think and process information visually. Even as agents take on more work, people still need to understand, audit, trust what’s happening, and that requires visual interfaces that are human readable.

Lastly, I would just say that we’re going to see new interaction paradigms emerge here. And they’ll have to be thoughtfully designed, adopted. For example, I think about Figma’s multiplayer interface for Figma Design or Canvas and how humans work alongside other humans. And I think that we’ll see agents also working alongside humans, both synchronously and asynchronously. And that, again, will lead to more intentionality around how to design software and what the surfaces are you need to design in the first place. And in a world where coding is just no longer a constraint, design and craft point of view, that’s the differentiator. And I’m really excited for that future.

Arjun Bhatia: Perfect. That’s very helpful color. And then, Praveer, I had one for you. Obviously, it seems like the business is firing on all cylinders. You had growth acceleration in Q4, NRR ticked up. This is all happening before your credit consumption monetization kicks in. And so I’m just curious, like as you think about the 2026 guide, how are you benchmarking the range of outcomes from credit monetization post March?

Praveer Melwani: Yes. I appreciate the question, Arjun, and good to hear from you. I think if I take a step back for a second and just think about what we’ve been doing as we’ve embedded AI across the entirety of our product suite. Everyone from a user who’s a starter user on a free plan has access to credits that we’ve embedded within their seats. So for some time now, we’ve already started to see usage ramp. We shared in the prepared remarks about 75% of our 10,000-plus customers today are actually consuming credits on a weekly basis. And this is an evolving number because we continue to introduce new AI features and surfaces that continue to draw an ever-increasing number of credits over time. We based our guidance on an understanding of current observed seat adoption behavior and usage trends.

We expect that to be refined as we both introduce new surfaces as well as really start to navigate that point after we’ve begun to enforce our seat limits. There’s an opportunity here to overperform as we build confidence in the observed usage behaviors, but we’ll continue to add additional value to our users along the way. So we’re excited here. I think we feel we’ve got some — we’ve got a whole bunch of irons in the fire here, and we’ll continue to refine our focus and story in the coming quarters.

Operator: The next question today comes from Michael Turrin from Wells Fargo.

Michael Turrin: I appreciate you making time. Dylan, I’d be remiss if I didn’t start with another bigger picture question for you. The stats you’re giving on Make seem to be hinting at new user types. Can you just speak to what you’re seeing from customers using Make and the user types that you’re seeing? I think it’d be interesting to hear you just articulate if this could be actually seat expanding for Figma in a world where investors are concerned around seat compression in most places.

Dylan Field: Yes. Thank you for the question, and it’s definitely something that we’re excited about and tracking. As Praveer mentioned in his remarks earlier, we are seeing customers that are bringing, for example, product managers into the life cycle. And certainly, as we use Figma Make not just internally, but also witnessed with some of our customers, internal tools, which can mean all sorts of different personas are quite interesting. So I think that overall, there’s a lot of opportunity to start to reach into use cases like UX researchers and other use cases around the team as well. And with that said, I think that there’s much more to do here, and we’re excited to go do that.

Michael Turrin: And just as a follow-up, Praveer, I’ve gotten some questions on just the free cash flow comment you made in terms of the guide. Are you saying dollar amount similar to operating income? And if so, that’s, I think, a bit lower than we were forecasting. So just any commentary on if that’s kind of Make consumption-based or just what the drivers in that comment were?

Praveer Melwani: Yes. I mean I think there’s a few things that will occur this year that are different from last year. And as we transition and as we continue to invest in the business, that was the spirit of the comment. So this will be a full year of us serving our AI features. We GA-ed them in the summer of last year. And as we start to see the continued ramp there, the expectation on what it does to margin is what we folded through to the guide. I think what is starting to get interesting here is as we start to introduce yet another monetization lever for us in the introduction of our AI credits, it starts to create a little bit more of a natural offset there over time. So I think we’ll share more with you guys as we start to observe it. But right now, I think that’s the best way to model it today.

Operator: Elizabeth Porter from Morgan Stanley has the next question.

Keith Weiss: Excellent. This is Keith Weiss sitting in for Elizabeth Porter. Congratulations on a spectacular end to what was a great year for Figma in 2025. Two questions, one for Dylan and one for Praveer. For Dylan, you announced an exciting new integration with Claude and Anthropic is doing a lot of great innovation. But investors are somewhat worried about kind of letting the fox into the henhouse, if you will, and trying to figure out where the dividing lines are of what is parts of the equation that are going to remain solely within kind of the Figma context and what is Anthropic going to be able to do? Do you guys — how do you guys see that question? Like how do you see the dividing line between what is in the wheel well of Figma and is always going to be in the wheel well of Figma versus what Claude or what Anthropic brings to the equation.

And then for Praveer, on the price increases, getting a lot of questions from investors in terms of we understand mid-single-digit impact for the full year. Can you give us any sense of how that ramped in Q4 and what type of contribution had in Q4? And how we should think about the price increase contribution to Q1 so we could better model kind of the slope for the coming year?

Dylan Field: Yes. Thank you for the questions, and I’ll start off with the first one. I would just say first that one thing that is interesting is how virtually every Frontier lab is using Figma to design how they bring their models to users and shape their product surfaces, and they are also been great partners with us. So that has been just interesting to see firsthand. I think zooming out, our AI strategy is pretty simple. We always want to be in a place where as models get better, Figma gets better. And easy to say, but you have to make sure that, that is the case for everything we do and also that we can have an edge. And I think that one thing that answers your questions directly around sort of where are the lines between is I would focus on tasks which are more verifiable versus non-verifiable.

Design is inherently non-verifiable. And I think that’s why you’re going to see humans in the loop and even more focus on design as well because as code becomes something that more people can do with the assistance of models, the value will move up the stack. And with the value moving up the stack, I believe we’re going to see an even greater focus on design. And we’re already seeing it, I think, with the hires people are making and the ways that non-designers are getting involved in the design process. Praveer?

Praveer Melwani: Yes. And I’ll answer your question on pricing and packaging there. So just as a reminder, we’re about 3 quarters out of the initial rollout of the changes that we implemented in March of last year. So the way that this is going to track to revenue as folks are filtering in through the renewals, you have a growing benefit there over the course of the year. We lapsed that anniversary in March of this year, and then you’ll start to see a waning benefit towards the back half of this year. So it’s a little bit like a bell curve there where it grows over the first 4 quarters, and then it will wane over the next 4.

Operator: Gabriela Borges from Goldman Sachs has the next question.

Gabriela Borges: I wanted to follow up on the conversation on Figma Make and ask specifically about some of the competition that you’re seeing in the prototyping space. Give us a sense of what you’re seeing in terms of perhaps consolidating budget within your customers away from other prototyping solutions? And are you still seeing fragmentation in that world where customers maybe using multiple tools for prototyping and then pull them into Figma when they’re ready to go to the next phase of the design process?

Dylan Field: Yes. Thanks for the question. I think that some of the broad strokes we’re seeing are really around the power of using Figma Make alongside Figma Design. And one stat that we shared in the earnings call is how over 80% of full seat users of Make are also using Design. And so I think that is an area that as we look ahead, we’re really excited to lean into more is to really try to unite these surfaces better. We’ve seen it already with things like copy layers from Figma Make into Figma Design or taking embeds from Figma Make and putting them into Figma Design. But it’s just a start. And I think that there’s so much more we can do here. And a big part of the platform differentiation we’ll have will come from the unification of the surfaces. I also think that it’s really important to remember that the round tripping between code and design can really set us apart here. And I am just very bullish on the opportunity that could exist with that round trip.

Gabriela Borges: Yes, that all makes sense. And a follow-up either for yourself, Dylan or for Praveer. I’m curious the budget implications. When you see a customer go all in on Figma, what does that mean for how they’re thinking about labor resourcing versus software resourcing? One of the things we’ve noticed as well, you put more powerful engineering type design tools into the hands of designers who may not know how to code. So how does the mix change between design-focused designers versus engineering-focused designers, if that makes sense? So I would just love to hear your observations broadly on implications of Figma adoption for customer design and labor budgets.

Dylan Field: Yes. I’ll start first. I think that some people are starting to call themselves design engineers, we’ve seen that in the past as well. There’s been sort of surges around even 8, 9 years ago, people getting really excited about calling themselves design engineers and kind of it went back to product design and now that term is coming up again. But I would say, overall, we’re not really seeing the roles blurring, more the responsibilities blurring between roles, not just between design engineering and design, but the roles more broadly as you go out to the product design life cycle, PM, engineering, design, research and marketing even, responsibilities are starting to blur. People are feeling the need to be more generalist. And so I think that it’s hard to split in a very accurate way because so many people that are non-designers by title are starting to really engage with design tasks. But I’ll hand it to Praveer to speak more.

Praveer Melwani: Yes. And then I think as it relates to the sales process and who we’re having conversations with, I think we’ve, over time, elevated the conversations to IT that gives us access to broader budget. And when you then kind of look at the types of users that we’re bringing in, there was a few that we spoke about in the prepared remarks the one that stands out to me is the hyperscaler that doubled their footprint with about 1/4 of their new seats going to product managers. And this is not a unique instance. We’re starting to see this happen more and more so throughout the customer base. And so our expectation is that we’re pitching wider, we’re pitching broader, and it’s the overall platform that’s ultimately winning here.

Operator: Next up is Rishi Jaluria from RBC.

Rishi Jaluria: Maybe 2, if I may. First, for Dylan. Just kind of expanding on some of the dialogue that you have mentioned that a lot of kind of next-gen AI companies and AI labs are working with you, and you’ve talked about some of the MCP integrations you have with Anthropic and others. How do we think about the opportunity for you to, over time, start building out more formal partnerships with them, having maybe even deeper integrations or kind of joint product development, maybe if that’s getting a little far. Maybe just help us understand what does that potential partnership opportunity between you and some of these other AI natives look like in terms of enabling success in your customer base? And then I’ve got a quick follow-up for Praveer.

Dylan Field: Sure. So I think that right now, as we think about our core with design, and just the opportunities that models provide as they advance with code, that is a big part of our focus. And the opportunity to partner deeply and to really make sure that we are thinking in the right ways about how models will continue to have new capabilities in the future and then to make sure that we are accounting for that in our product road map as well as working closely and integrating well with various model providers is something that we paid a lot of attention to. I think going forward, as we think about some of the things we’ve seen with for example, Figma’s apps on ChatGPT as well as Claude, there is definitely stuff that we’ll explore there as well.

But I think it is maybe secondary to the primary objective of just having that amazing ability to work and go from Code to Canvas and Canvas to Code and back again, that round trip is what we’re really focused on and making sure that we are always meeting the criteria of as models get better, we’re getting better.

Rishi Jaluria: All right. Very helpful. And then, Praveer, in your prepared remarks, you closed out by talking about March is kind of when we’re going to start seeing this more mix between subscription and consumption more of a hybrid. It’s very consistent with what you’ve talked about before and how the landscape seems to be shifting, maybe as we think about that mix, 2 pieces. #1, how do you expect, given some of the early traction you’re having with your AI native SKUs, how do you expect that mix to shape over time? And then alongside that, how do you — what tools in your arsenal do you have to at least have visibility and predictability into future revenue? So the model itself doesn’t become overly volatile as we navigate through this change?

Praveer Melwani: Yes. No, I appreciate the question, Rishi. I think the way that I’d frame it is we’ve already started studying this usage and utilization behavior, and we’ve been prepping for this hybrid model for some time. We basically have telemetry into the overall seat — rather the overall credit consumption on a per seat basis. And what we’ve observed is it tends to be a parallel distribution where a subset of users within an organization are receiving outsized value and as such, are going over the projected limits that we intend to enforce. Now our expectation is that, that will continue to evolve as we introduce more services for folks to be able to draw down credits will create more opportunities for us to have — continue to shift that distribution further and further right.

The way that our AI add-ons are structured, they’re structured as additional seat — additional consumption packs in addition to providing folks the opportunity to pay-as-you-go. So in the instance that you’re purchasing an add-on pack, it co-terms with your subscription, and we have more predictability in that. And on the pay-as-you-go side, that is more meant to be for burst type activity. So ultimately, it will be a mix. We’re studying it very closely. And I think as we get post the actual monetization date is when we’ll be able to further refine our assumptions.

Operator: Your next question comes from Billy Fitzsimmons from Piper Sandler.

William Fitzsimmons: The FY ’25 — or the FY ’26, I should say, revenue starting point was well above expectations. If I look at the operating income guidance, midpoint implies, I think, 7.7% non-GAAP operating margins compared to, I think, 12.3% in 2025. Just as we think about the drivers of this, what’s kind of the breakdown between expected gross margin compression from AI investments in the AI product ramp versus maybe some incremental investments you plan on making on the OpEx line. And I know you don’t guide to it, but any directional commentary on kind of gross margins in 2026 would be helpful.

Praveer Melwani: Yes. I think your point on us continuing to invest on the AI side is what’s showing up flowing through both through gross margin and ultimately will hit our Op Inc and op margin there. At this moment, we’re not kind of sharing more specifics on the gross margin side, but it is meant to signal that we do see that there’s a pretty large opportunity for us to take more AI features to a broader set of our users. And so that’s what we’ve used in our guide to express our confidence and excitement to further invest here ultimately with the goal of driving growth and ubiquity of many of our solutions and durable growth over the long term.

William Fitzsimmons: If I sneak one more.

Dylan Field: I was going to add like if there’s ever a time to put your foot on the gas and make sure that we are lean into the future, this is the time. So I just want to be clear about that. We can intend to invest here, do so responsibly, but make sure that we are setting ourselves up to capture the opportunity in front of us, which we think is very sizable.

William Fitzsimmons: And maybe on — super helpful and maybe just on OpEx, like a lot of companies this, call it, earnings season are talking about expected AI-related efficiencies on the R&D line or the potential to increase product velocity there. How are you guys just thinking about that in terms of 2026?

Praveer Melwani: Yes. I mean there’s definitely opportunity there for us. I think what we’re experimenting with is a whole bunch of different types of tools. We’re iterating on different ideas and then observing overall efficiency of the team. We don’t see that — we don’t see it as a tool that replaces our talent, but rather how can we augment the team that we already have? So we will continue to hire, but we will also be able to complement that with efficiency gained by some of the tools out there as well.

Operator: The next question today comes from Parker Lane, Stifel.

John McShane: This is Jack McShane on for Parker. Dylan, I’d love to hear you compare and contrast the benefits of your new Claude Code integration and Figma Make. Do you have any early indication on how customers are going to leverage all these tools that take you from 0 to 1 in the design process? And when will a customer be using the Claude Code integration versus Make? Is it usually — is it going to be a user preference thing? Or will some projects be more relevant to one or the other?

Dylan Field: Yes. I mean, I think it’s — there’s plenty of times where I hypothesize, but it’s probably not the format for hypothesis. And I would say that overall, this is very much in the too early to tell camp. We just launched this yesterday. And so I am excited to learn more. But right now, we’re still at a very early place here. I think though that if you look at the workflow overall, it used to be the case like even for sure, a year ago, perhaps even 6, 9 months ago, that a lot of people saw the workflow of product development is very linear. And you would do stuff like brainstorming and then design and then you’d code. And right now, we’re seeing it in a place where people might start anywhere, and they won’t be able to go everywhere.

And so I think this plays directly to our strengths, making it so that you can really go into the Figma Design canvas and with — in the case of Make, really couple up Figma Make with Figma Design and make it so that you can go and explore divergently and really have that bird’s eye view, zoom out and understand what’s possible. The way I think about it is you’re sampling these infinite possibilities space. And you’re trying to determine what are the right options to go explore in that space and then push them forward with design. And I think that you can do that through code. You can do that through design, but code is more linear. It’s more — you’re really advancing in one direction. And so you might be moving fast, but make sure you’re going to the right place before you go too far.

Whereas design, you’re really thinking about what are the range of possibilities I should explore and you’re weighing them and figuring out the trade-offs. And I also think the opportunity for polish and craft and design is quite high. And that gets me very excited because we’ve really tried to make sure that direct manipulation works so well in Figma design and the opportunity to use your hands and just being a state of flow, I think, is a big opportunity for our customers, and it’s so much more efficient than prompting a lot of examples. Overall, I would say Figma has the opportunity to be the place where all this comes together, the round trip, the direct manipulation, the divergence of different possibilities as well as picking a solution and then saying, okay, I want to go [indiscernible] this up.

Maybe that goes back into the agent development environment or IDE of your choice or maybe in the future with longer running agents and increasing model capabilities, you can just do that from Figma Design. So we’ll see how the future evolves. Hard to predict when these capabilities come online, but we’re really excited about our position here.

John McShane: Yes. That was really insightful. And then just one more quick one from me. Obviously, of the 4 products you launched last year, rightfully so, Make is getting the bulk of the attention. But I’d be curious to get an update on Draw, Buzz and Sites. What’s the usage been like, the feedback? And has there been any key — any big surprises since they’ve gone to market?

Dylan Field: Well, I would say for Make, obviously, getting tons of attention. You noticed that. And then as it comes to Draw, Buzz and Sites, I would say that Draw, I mean, definitely, the engagement with some of the features we mentioned in the prepared remarks has been really encouraging. And then I would — around Buzz and Sites, I would say these products are still early in their life cycle. And so we are definitely learning a lot here from our users as we always do. And we’re seeing promising early traction. And while I don’t have numbers to share, I think that there are definitely customer examples. For example, one is from a MAG-7 customer where with their creative team, they’ve been able to — really been able to run a global holiday campaign through Figma Buzz and produced just an incredible amount of assets, I think, over 5,000 across 30 countries.

And for — the amount of scale you can get from Buzz and also in some ways from Weavy too, which is a different use case, but has shared properties. We are really excited about how you can actually go create workflows for people. When it comes to sites, I would just say that there is a real need on the workflow side of going from a design and Figma Design to something that is published on the web. And that workflow need is incredibly important. And we’re excited to help people go from design to production in general, but this is a very particular path. And whether it’s Figma sites or Figma Make, we’re really watching closely how customers are completing that journey in Figma. And more broadly, across all these products, we’re watching the way that people use them, making sure they have what they need and also paying attention to the constantly changing environment and landscape that we’re in, in that way we can plan and build accordingly.

Operator: Up next, we’ll take a question from Alex Zukin, Wolfe Research.

Aleksandr Zukin: I’ve got Dylan, maybe one for you and then one for Praveer. Kind of building on some of the earlier questions that are at a high level. You have had the labs as customers, or you have them as customers. They’re deep partners. You’re watching from the front row in terms of how the entire software supply chain is changing. What products or what usage maybe that surprised you, Dylan, to the upside? I mean, maybe specifically on Dev Mode and Make. And holistically, how are you thinking about tailwinds to growth from these products in fiscal ’26? And a quick follow-up.

Dylan Field: I’ll actually punt that one to Praveer.

Praveer Melwani: I mean there’s a bunch of them that I’m excited about. I think we called out some of the momentum on Make there. We grow our weekly active users 70% quarter-over-quarter. And we start to see the adoption across our larger customers, the 100,000 customers going from 30% creating a Make — up to about 50% by the end of the year there. When I stare at Dev Mode, I think Dev Mode continues to be a very, very important part of the overall workflow. We see excitement not just from our — from folks that are upgrading for the seat, but for folks that want to make use of Dev Mode MCP. It’s an emerging trend that we found is really resonating with our customers. We now have this opportunity to really round trip given the integration partnership we launched with the Canvas — with Claude Code to the Canvas yesterday.

And our hope here is that what we’re taking to our customers is a full product platform and suite. And as we do so, it gives us an infinite number of ways to position how these things kind of come together.

Aleksandr Zukin: Got it. And then, Praveer, maybe just for you specifically on Figma Make. What’s in the guidance? Is Make — is it possible to think about Make or compare and contrast that contribution to growth relative to pricing in fiscal ’25? Is it — do you think it’s going to be more or less? And are there any pricing tailwinds still contemplated in fiscal ’26 in the guide?

Praveer Melwani: Yes. Maybe I’ll start with the back half of your question there. We’re still going through the last set of renewals here that are folks that are renewing under the new pricing and packaging that we launched in March of last year. So we’ll anniversary that in March of this year, which just so happens to coincide with the launch of our Make add-ons and credits. The way that we framed how Make shows up and broadly, our AI features show up in our guide is we baked it based off current utilization and adoption trends, both on seat adoption trends in addition to credit utilization patterns and trends. What we expect to see is as we introduce more surfaces for folks to be able to draw down credits that we’ll start to see more and more folks that would potentially land in the camp of needing an add-on.

So what I would expect over time is that it’s not necessarily going to be a fire out of the gate, but a slow build here with us wanting to make sure that we’re really serving our users and meeting their needs. And then the onus is on us to continue to deliver value over the long term.

Operator: And everyone, unfortunately, that is all the time we have for questions today. This does conclude our conference. We would like to thank you all for joining. You may now disconnect.