The Exchanges

Q Let's unpack some of it. So, let's start with features. You just mentioned Canva code. You guys had a very impressive last 12 months in terms of shipping velocity, and I wrote down Matic Studio, Dream Lab, Canva AI, Canva code, Canva sheets. Maybe give us a little bit of a Tour of what those different things do at a, at a high level? Uh, so Magic Studio to start.

A Yeah, so Magic Studio is a collection of AI-powered tools, uh, both text and visual. Uh, there are text-based tools that allow you to, for instance, um, uh, modify text to be in your, in your particular voice, or, uh, in a, in a brand voice, which is really powerful. There's text summarization, text expansion, Uh, we've got a whole suite of image editing that's really powerful, whether that's infill or outfill. Uh, we've got Magic Grab, which is an amazing feature, which basically allows you to treat a rusted image as, um, something that you can decompose. You can pick objects up and move them around. Uh, Magic Arrays uses similar technology to be able to remove and then infill, um, in a very smart way. Um, We did launch a Sheets product in, um, in April. Uh, that's our take on, uh, on, on a spreadsheet product. It is designed to be, uh, very, very easy to use, uh, fully integrated into that, into the visual communication experience of Canva. Uh, and it will be our kind of data backbone going forward. So when we want to do more data-driven products, we'll be using Canva Sheets as the kind of data source for that.

AI assessment note: “Magic Studio is a collection of AI-powered tools, uh, both text and visual.”

Q So that's very interesting. So it's 200, uh, machine learning slash AI folks, um, and so you're saying there is a central lab that does R&D research?

A Yeah, so we take a hybrid approach there. We certainly have, uh, teams that are dedicated to more foundational research, but we also have embedded, um, uh, folks embedded in product teams who are doing research. And, uh, they tend to be on shorter product cycles. Uh, and they tend to, you know, their output is usually a prototype, which a product will look at and make judgments about, and then we'll see if we want to turn that into something that's a production feature, and we'll try to turn those around very, very quickly. We've invested enormously in putting a platform abstraction over a lot of the third party AI that we use, uh, whether that's kind of like base layer infrastructure, Uh, like Bedrock or SageMaker, or whether it's third party AI providers like OpenAI, and that allows us to rapidly switch out models and experiment with different models. It allows us to augment models with our own proprietary tech, uh, and it allows us to really iterate very, very quickly when new models come onto the market to do something exciting. We can get them in front of users In really cohesive experiences very, very quickly. So we were able to, for instance, you know, Canva code is, is an interesting feature that we've just, uh, launched just back in April. That's a feature that allows users to build little intelligent, um, interactive widgets in their designs. That went from kind of fi…

AI assessment note: “Yeah, so we take a hybrid approach there. We certainly have, uh, teams that are dedicated”

Q number of companies that we all work with as, as VCs, early stage, um, startups that, uh, at some point graduate from that, uh, Early, uh, kind of PLG inbound motion to being outbound and enterprise focused. From an engineering standpoint and product standpoint, any sort of tips and tricks about, um, what took longer than you thought or was harder than you, you would have thought, would have imagined?

A Catering to an enterprise market, um, it certainly pulls the product teams in different directions. Um, enterprise customers want sophisticated admin controls. They want sophisticated auth. They want data residency. These kinds of considerations, if you haven't baked them into your product early, they become quite expensive to, to retrofit. Very early in Canva's, um, architectural journey, we put a, a quite good abstraction in over our, um, AWS infrastructure, but I do think back now and, and, and wonder, oof, we could have just spent a little bit more time Really abstraction, abstracting region-based storage. Uh, it would have been cheap to do then. Uh, we have got it now, but it was a, a massive engineering effort. Um, you know, back when it was 10 of us and a few services and a few databases, uh, it would have been relatively cheap to kind of build that culture in there, build that kind of tax, if you like, on every product that you have to think about what, what region shard You're gonna store the data in. Uh, having to retrofit it across hundreds of teams, um, hundreds of services was a, was a monumental lift.

AI assessment note: “having to retrofit it across hundreds of teams, hundreds of services was a monumental lift”

Q And, uh, you mentioned that, uh, you joined Atlassian through the acquisition of your company. How has, uh, having been a founder helped you, uh, as a engineering leader?

A I think it helps create agency. I think that any organization that grows beyond a handful of people, the bystander effect is a real problem. That it's too easy to think, You come across a problem, and you think, that's not my problem. But when you own a company, everything's your problem. And, ah, so that, having that kind of, ah, high agency when you're, when you're attacking problems, doesn't mean you're gonna solve every problem, but you recognize the problems, and you're very engaged, and you're happy to cross over the, the swim lanes, a lot. Ah, certainly at early stage companies, you've gotta be doing that a lot. You gotta be really a bit of a generalist. And, uh, so I think that's a real, a really powerful thought, um, that you really get ingrained when you, when you're kind of on the, on the line, on the hook for everything when you're running your own company.

AI assessment note: “I think it helps create agency.”

Q And you view this both as an opportunity, but also something to be potentially concerned about, um, in, in double clicking on what you just said, where, uh, Canva could be, uh, a part of somebody else's chain, as opposed to people coming to Canva, logging in, having a Canva experience. Uh, is that something that, uh, you'll worry about?

A It's not actually a concern. We see Canva as a destination. If you are doing any kind of visual communication, then there are going to be natural limits to a conversational interface. And, uh, people are going to want to be able to collaborate. They're going to want to be able to control for brand. They're going to want to be able to organize their content. Uh, there are going to be limits to how you want to interact with a design conversationally. So we think a future that we see is that if you If you are, if you do have your personal chatbot and you want to do some design, you might get a one-shot design there that, that then you can, uh, be transported into, uh, A Canva experience where you're actually able to stop talking about the design or asking a machine to do something and actually just play with it as you would normally with a, with a mouse and, you know, picking things up and moving them around. I think that that, uh, is the essence of kind of human creativity, and I think that that's not going to go away.

AI assessment note: “It's not actually a concern. We see Canva as a destination.”

Q That's an incredibly, uh, impressive list of, uh, product and features around AI that was shipped literally, uh, uh, over the last 12 to 18 months. Uh, how do you, how do you guys do it? Like, how do you manage to, uh, have this kind of velocity, especially at this kind of, uh, scale? And is there something, uh, different about shipping AI features versus regular features?

A So, thank you for saying we have high velocity. That's, uh, I'll take that compliment. Um, it certainly is, feels like breakneck speed at times. At the technology org, we're very focused on Uh, really thinking hard about the domain model that we are implementing, and then building a set of composable components, uh, with powerful APIs internally. That enables product teams to move very, very quickly because they're sitting on top of a rich set of functionality. Uh, it takes real care and diligence to build out that internally consistent, uh, set of surfaces and services that back those surfaces, Keeping control of the domain model, so the domain model doesn't just explode into this kind of combinatorial explosion of complexity, and so we spend a lot of time thinking about that. We want the service teams to be thinking very carefully about how do we, APIs, do we provide product teams so that product teams can move very quickly. With AI, it's more of the same. It's thinking very deeply about what's the AI platform layer that we can provide. Product teams can be getting the benefits of AI without necessarily having to go deep on the technology. Having said that, we are very focused on this kind of democratization of, uh, knowledge around AI in our technology org. We think that, you know, once upon a time, uh, in software teams, you'd have a DBA on the team, but now a DBA is not re…

AI assessment note: “With AI, it's more of the same. It's thinking very deeply”

Q Uh, very fascinating. Okay. Going back to, uh, AI behind the scenes at, at Canva. So you mentioned some elements of the stack. Uh, so let's start with, with models. So you, uh, it sounds like you're using some open AI and Anthropic for some things, and then you have your own, uh, foundation model. Efforts through Leonardo and, and others. How do you think about the build versus buy?

A We have an engineering value, strive for pragmatic excellence, and, and, and so we are ruthlessly pragmatic in whether to build versus buy, and that goes across all elements of functionality. I'm a huge believer in, uh, I think it was Jeff Bezos who came out with that famous saying of, you know, don't spend time on undifferentiated heavy lifting. Certainly we want to leverage best of breed models if If they're third party and they're available via an API, then we will. If they're third party open source models, then we can host them ourselves, then we will do that. But we do provide a platform, as I said, we put a platform abstraction over that so that we can chop and change quite quickly. We are investing heavily in our own model development. Leo has given us a great, um, foundation for that, no pun intended. Uh, and we have billions of very unique, um, opt-in data points Around design creation, design intent, ingredient selection. We're mining, um, to produce real insights into how to improve people's designs, how to help people in their design activities.

AI assessment note: “we are ruthlessly pragmatic in whether to build versus buy”

Q Fascinating conversation to, to, uh, zoom out, uh, maybe, uh, to close. Next, Few years at, at Canva. What does, ah, what's on the roadmap? What does, ah, success look like? What's your, ah, ultimate ambition as a team?

A So Mel, ah, has a two-step plan for, for Canva, which is, um, to create the world's most valuable company, and then do the, the most good in the world that we can. And I have to say that, ah, really helps me get up in the morning and, ah, keep coming into work. I think it's a, a really noble mission that is something different From a lot of companies who just focused on commercials. Practically speaking, I think we've got such a long way to go in building out the product vision that, that is in Mel's head. And I'm really excited to, to, to go on that journey. I think AI is really, really exciting. Uh, I think from a ways of working point of view, I'm looking forward to a new era of productivity. I don't think software engineering goes away. I think software engineering changes to actually a much more fun job. Uh, where a lot of the mundane kind of plumbing of software engineering is handled for you, and you're able to orchestrate software, uh, with these agents helping you, uh, and become much, much more productive. So I, I would expect our productivity as an engineering org to lift significantly still. You'll see that you, I can't tell you too much about what's coming down the pipe in terms of features, but Um, actually there's an announcement coming out this week, which is pretty exciting. Actually I probably can tell you about that. We are integrating VO three, which is Goog…

AI assessment note: “We are integrating VO three, which is Google's new amazing video generation model natively”

Q And you were saying, uh, right before we started recording this, that, um, you're based in Sydney, but, um, the, the team is still largely distributed, working from home with some hubs. Talk to that a little bit. Where, where are folks, and, um, What's your in office or out of the office stance?

A Yeah, so we do predominantly, oh, so our origins are Sydney, Australia. We have a large office there. In fact, we're building a new one. That's very exciting. Uh, we have, we don't, we have a hybrid working culture, so people can come into a local hub and work. We have, we set up hubs when there is a, a, um, a large enough number of people in a particular geography, um, Through COVID, we were still doubling in size in our engineering org, ah, every year. And, ah, we, we kind of realized that We can keep that pace and hire people that are just time zone compatible. So that meant that we spread up and down the eastern seaboard of Australia, across to Perth, across to New Zealand. Through acquisition, we have acquired engineering teams. So we have about 400 engineers right through Europe, um, through our acquisitions.

AI assessment note: “we have a hybrid working culture, so people can come into a local hub”

Q It does feel from the outside as a significant expansion, uh, going from a visual suite to starting getting into effectively data infra and, uh, but is the goal ultimately for the company is just like all around productivity, starting with design, but then expanding to just about everything?

A We see ourselves at the intersection between productivity and creativity, and we think that, um, increasingly in the workplace, visual communications just coming to the fore, And so we have been rounding out our feature set. We have a docs product, um, that allows users to, um, create online documents, collaborate on them, uh, but do so in a really visual way so they can embed rich visuals, they can embed graphics very easily, uh, and they can change, um, different doc types within the one design. So you can have, A, a quite text heavy document on one page, and then you can have on the next page, you can have a whiteboard, where you can be doing some collaborative whiteboarding. You can have, um, sections of a, a presentation in the same design, and that's an amazingly powerful way to, to collaborate, ah, on a particular project, because different contributors to a project need different assets, and normally it's quite hard to organize all those assets, and here they're all just in one design space.

AI assessment note: “We see ourselves at the intersection between productivity and creativity”

Q And after the pause, how do you think about that problem of, uh, junior engineers that, um, you know, will be vibe coding or whatever the better term is, uh, sort of natively? Do you, do you need to have like an internal program where you train them on some core logic that they will just not naturally know?

A I think so. I think there's this kind of, I read somewhere this kind of advice, what, you know, what do you do if you're, if you're graduating? I'll just focus on critical thinking, but, um, Critical thinking is something you can't really teach. It's something that you need to build around a domain of knowledge, and the only way you get a domain of knowledge is to, to work in that domain. So I think at Canva we'll be focusing on probably just more careful onboarding, more careful peer review of grads. We will be more picky. We will be looking for the, the grads who bring deep first principles thinking, Um, strong, really strong CS fundamentals, but also show us some of those human qualities. You know, uh, empathy in engineering is a, is a vastly underrated skill. Uh, and it is a skill. It's not a, it's not a talent. It's something that you can teach engineers.

AI assessment note: “So I think at Canva we'll be focusing on probably just more careful onboarding”

Q Does the productivity jump, um, impact your hiring plans in any way?

A Uh, that's a good question. We have slowed down hiring a little bit, uh, for, for a number of reasons. We are looking at, you know, we wanted to, to just take a pause and understand where the market's going with these AI tools. We are still hiring, but it's not hiring as fast. There's a challenge for our industry in that we do see kind of slightly bipolar results for these tools in the, in the hands of a senior engineer who can tell good code from bad code. They're very, very powerful, but for graduate engineers, for junior engineers, ah, they can be quite dangerous because they just don't know what they're looking at when they've generated a bunch of code. I think it's a challenge for the industry. We are, we do have a graduate intake program. We will still be taking, uh, grads in, um, at the beginning of the year, next year, but we're, we're just taking a pause now. I, I think the way that I'm thinking about it personally is that engineers are more productive. If you've got a lot of work to do, then why wouldn't you want more productive engineers to, to throw at that work? So, you know, I think we've got room to grow our engineering org.

AI assessment note: “We have slowed down hiring a little bit”

Q company. And, and two, in general, you guys seem to have a very different stance, uh, on, on that. Uh, so how do you all think about AI as an opportunity, uh, or possibly a threat? Have there been any moments where, you know, uh, despite being bullish on, on AI, um, you know, You all look at each other and say, oh, this one actually might be a problem.

A Look, we're certainly alert to the rise in visual AI, but we feel we're actually really well positioned. Uh, we can, um, Use third party models when they become available, integrate them into our platform very, very quickly, and provide a really rich, cohesive experience. Uh, we can facilitate collaboration. We can let you organize your content. Uh, we can provide, um, brand kit controls. Uh, all of these tools that, um, uh, perhaps your, your average AI centric startup can't. Uh, and indeed we have a very rich, uh, API layer, um, that is available for third party developers, our ecosystem offering. Uh, a lot of niche AI startups are finding is a fantastic distribution channel. So, they've got their niche, um, their niche product, they can come and build a rich integration into Canva, and then suddenly they get distribution, they get a lot of users. We've had a lot of success, um, and that's a win-win for us and for them.

AI assessment note: “alert to the rise in visual AI, but we feel we're actually really well positioned.”

Q And you joined from Atlassian, which, uh, at the time was already a, an incredibly successful company. What was the thought process and perhaps to generalize it, um, how does one as an up and coming engineering leader, uh, pick the next company to go to? Because clearly that was an incredible pick.

A How do you, how do you pick the winners? Ah, yeah, it's, it's, ah, look, I've been very lucky. I joined Atlassian back in 2007 through an acquisition. Atlassian bought my company, ah, and, ah, around about the time that I, well, 2014, I was, I kind of recognized that I was in a little bit of a rut. I had certainly enjoyed the ride at Atlassian. They'd gone through their own hypergrowth phase. And they were just leading up to IPO. Uh, but I really wanted to get back down to just building something. And, uh, I met through a friend, I met Mellon Cliff, and I was, I instantly fell in love with the business model. Um, I don't think I have great advice on how to pick winners.

AI assessment note: “I really wanted to get back down to just building something.”