Designing the Future: Inside Canva's AI Strategy with John Milinovich, GenAI Product Lead at Canva
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How does Canva define the balance between automation and augmentation in design?
At the highest level there's like automation and augmentation. What people want from automation is to remove the ick from something that's just super annoying to do. As a user, you know what you want the outcome to be. But you just kinda want it done for you. The other dimension here is augmentation, which is I am fundamentally in the driver's seat. I am working towards something that I can't quite see what it is in my head yet. And I I want a set of tools or a suite of capabilities that help me take that like fuzzy feeling and make it into something that's more concrete. One of the real original innovation of Canva was moving design from a world of pixels. to a world of objects. When you look at what AI is doing is we believe it's moving to a world from like object level manipulation into a world of like concept level manipulation.
I think generally our development flow is just like make it work, make it good, make it fast, and then make it cheap. That's I think about that really as the problem orientation versus the solution orientation. Oftentimes the outcome is like so clear that we can see it, but being able to actually deliver on that is is extremely, extremely difficult. If you're topping out of eighty one and we know we need to get to ninety eight, like it probably means that you need to maintain the problem focus but switch the solution.
Hello and welcome back to the Cognitive Revolution. Today my guest is John Milinovich, head of generative AI product at Canva. For anyone who's not already familiar, Canva is an online design platform with a mission to empower everyone in the world to design anything. Which has scaled to serve now more than two hundred million users globally with its highly accessible suite of design products. More recently, Canva has also become a leader in AI powered design experiences. With a mix of point solution features like their excellent image background removal tool, More horizontal features like their magic write tool, which attempts to write in your brand's voice across their entire product suite. And AI superpower features, like their new Dream Lab text to image product, which was derived from their acquisition of Leonardo AI, reportedly, although this is not confirmed, for some three hundred and twenty million dollars.
In this episode, John shares Canvas Framework for thinking about task automation versus human augmentation. Canvas approach to testing and evaluating AI features, insights on fine tuning foundation models, and a fascinating discussion on how AI might transform fields like architecture, where John began his career. We also dig into practical tips for AI engineering, with John emphasizing the importance of maintaining problem orientation rather than getting too attached to any particular candidate solution. This conversation was a super fun opportunity for me to trade notes with another generative AI product leader whose expertise has been demonstrated at global scale. I think there's huge value here for anyone who wants to level up their thinking about what sorts of experiences AI can unlock, and also how best to go about developing and deploying them.
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What framework does Canva use to decide which AI features to build for different user personas?
Now, I hope you enjoy this behind the scenes look at AI product development at scale. With John Milinovich of Canva. John Milinovich, head of Gen AI product at Canva. Welcome to the Cognitive Revolution.
Thank you so much, Nathan. I'm really excited to be here today. Big fan of the podcast and uh what you all are doing in Turkey Time Network. Cool, thank you, I appreciate that.
Well, right back at you too. I mean, Canva obviously has been a leader in the design software space and and helping people who are maybe not creative professionals, but still are at least a little bit creative to realize their visions for a number of years.
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Chapters
8 chapters
1
How does Canva define the balance between automation and augmentation in design?
0:00–3:14
2
What framework does Canva use to decide which AI features to build for different user personas?
3:14–6:34
3
How is Canva moving from object‑level manipulation to concept‑level AI interfaces?
6:34–10:37
4
What are the most impactful AI‑powered experiences Canva has launched (e.g., background removal, Magic Write, Dream Lab)?
10:37–19:09
5
How does Canva evaluate and fine‑tune foundation models for design tasks?
19:09–26:50
6
What cost‑and‑latency considerations guide Canva’s AI product development?
26:50–31:35
7
What qualities does Canva look for when hiring AI engineers and building its AI culture?
31:35–38:00
8
How does Canva envision the future of AI‑augmented design across industries like architecture and content creation?
38:00–1:18:45
Speakers
2 identifiedMore from "The Cognitive Revolution"
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