Navigating UX Research and AI in Design

Show Notes

Figma’s Head of Insights Andrew Hogan joins Peter and Jesse to explore emerging trends in design practice as AI transforms creative workflows. The conversation examines how role boundaries are blurring across product teams, where AI delivers real value versus hype, and design’s growing opportunity to lead strategic orchestration in increasingly complex digital experiences.

Find Andrew on LinkedIn at https://www.linkedin.com/in/ahhogan/.
Learn more about Jesse James Garrett and his coaching and consulting at https://jessejamesgarrett.com/
Learn more about Peter Merholz and his digital book “Design Org Dimensions” at https://petermerholz.com/

Transcript

Jesse: I’m Jesse James Garrett,

Peter: and I’m Peter Merholz.

Jesse: And we’re finding our way,

Peter: navigating the opportunities

Jesse: and challenges

Peter: of design and design leadership.

Jesse: On today’s show, design industry analyst and head of insights for Figma Andrew Hogan joins us to talk about just why Figma needs an industry analyst anyway, how he drives business impact as a researcher and key findings from his research on what’s changing about design and what isn’t with the advent of AI.

Peter: Andrew, thank you so much for joining us.

Andrew: Thanks for having me. Super excited to be on.

Peter: Awesome. So gonna start start with a softball, which is just like, well, you’ve got an interesting role at Figma. Head of Insights, I think is the title. What do you do?

What Does a Head of Insights Do?

Andrew: Thanks for this one. I don’t know if that’s a softball to be honest, but, my job is essentially to analyze the industry, the design industry, what’s happening, where is it going, what sorts of trends are going on. We do that through a lot of different means, whether it’s looking at our product research, whether it’s looking at, big state of design, state of the designer surveys, state of AI and design, a lot of states of, and then to figure out how to get that out in the world so that people have a view of what’s going on.

And so that Figma has a view of what’s going on because you always wanna design for like, the next biggest space, right? You’re designing for the world that you’re in and maybe where the world is going. So my job is to make that work better internally, working with our research team and share that out externally so that people can sort of see and plan and think a little bit with some different kinds of data that are maybe outside of their day-to-day experience.

Jesse: How do the questions that you pursue differ from what a typical UX research team might be taking on?

Andrew: I think ideally they’re extensions of each other. So, let’s take like AI. Obviously Figma wants to know, how are people thinking about AI? What are they finding value in? What do they want to be able to do? And then also, how prevalent is the usage? How might that compare to how across developers, designers, product managers are using AI?

But I don’t think there’s a huge amount of daylight there. Often it’s taking a slightly broader view than like, did people find value in this specific feature? But again, really good experienced researchers, they’re doing that, they’re thinking about it that way.

Peter: Some of what you do could be also considered market research, and I don’t know if it falls under that, Jesse mentioned UX research or if it’s a different kind of research, but I’m also intrigued… you mentioned how the value of the work you’re doing is for Figma as well as for the community.

But if you could share, I’m curious what insights you’ve had or that you’ve helped uncover that have informed what Figma has launched? Are there any through lines between anything you’ve worked on and, something that people have had a chance to use because your insight pointed out an opportunity?

Andrew: Sure. I mean, so there’s a lot of parallels here with what I did at Forrester before, which is where I was for seven years as an industry analyst. You’re always looking at the direction of, people are excited about, where they’re going, what they’re spending more energy on, what they’re spending less.

So I can’t give like a specific feature or anything, but certainly like one of the things we look at is, people feel like they’re a lot more efficient when they’re using AI in their design process, but they don’t always feel like it’s getting better, they’re doing better work. And so we think a lot about the tension between those kinds of things.

And so you can imagine the sorts of features that might lead to efficiency versus the sorts of features that might make people feel like their work is getting better. And so that’s a trend we’re looking at,we’re tracking over time.

And then, ultimately looking to do both, right? You want to help more people to be able to participate in the design process, and then you also wanna be able to make experts faster, better, all of those kinds of things.

Peter: You’re operating in an enterprise software context, which I think people in the design community often forget, right? Like, they just think of it as a design tool, but really you’re enterprise software. Is a role like yours typical in enterprise software? ‘Cause it’s curious to me that Figma would want to have a Forrester style analyst in-house, like, as opposed to just, partnering with Forrester or something like that.

What’s the logic or the intent of bringing that in-house?

Andrew: I mean, you get certainly lots of benefits in terms of day-to-day conversations, right? For like a Forester or an IDC or a Gartner, you have these very like specific engagements and you’re always thinking about exactly what to share and how to share it.

And I think we all would like to believe that those things are free and open, but the reality is you’re kind of always thinking it through, and in-house you can kind of just say like, Hey, are you just seeing this?

It’s a quick Slack and I think that’s the kind of benefit. And then you also have this benefit of, there’s sort of this context that I know about when it’s comes to like, future roadmaps or company strategy, that we can think about when we are designing studies.

Because you often need to have a really long view. And so the ability to partner with our research team and take a long view while also getting answers in the near term and then helping people who are thinking about where should their career grow? What sorts of skills should they try to pick up? If they’re leading a team, what sorts of skills should they encourage people to go do?

Or sometimes I think about it as like, filling out the strategy slides. That’s a sort of a glib way of saying it. You know, here’s the direction that we’re going.

You can often partner with customers to help them sort of fill out the strategy slides because they need to justify why they’re going in a particular direction. And, previously they might have only been able to engage with like a Gartner or only gotten like a Figma product perspective.

And there’s just a little bit more space and data to share. There’s like a broader view that I think you can offer. And obviously it’s a Figma view. I work at Figma. Like, it’s a very specific perspective, but I think people tend to find the triangulation of those perspectives to be helpful.

And I’m sure they take some of it, I’m sure they throw some of it away. But it can be kind of lonely trying to make these decisions and this role offers both inside Figma and outside Figma, like another view. And I think that’s what’s useful.

Then you still go to Gartner. You still go to Forrester, or you still go to IDC. None of those things go away. It’s just one more lens.

Jesse: It’s interesting to think about the investment in your role as really being an investment in supporting the decision making of leaders across Figma, really, because of that vantage point that you bring and that perspective, which is like standing just slightly outside the organization, right?

And I wonder what is the tension between your role as you talk about, like, having a value proposition that is both inside Figma and outside Figma, and what is your role as kind of being the person on the edge who’s gonna bring new things into the organization that maybe aren’t even things that people were asking for?

Agent of Osmosis

Andrew: Yeah, I am always trying to be like an agent of osmosis for information out, information in. You both have given me feedback and shared perspectives that I’ve brought in. That’s always the goal. You facilitate information sharing. And that’s a pretty helpful spot to be in. And it isn’t just helping people at Figma. It’s helping leaders outside of Figma. And I think that’s the unique part. So, often, “Hey, did you see this comment? These people are having this issue. I heard this discussion from somebody at a dinner. Like what do we think about that?”

And it’s a privilege to do that. And also like a big responsibility too, because when somebody tells you those things, that means they’re fired up enough to tell you this is something that they’re thinking about and they want someone at Figma to get back to them. They want someone at Figma to think about it more.

And so sometimes that’s the kind of position that I’m in. And frankly, a lot of people at Figma have those sorts of roles. It’s extremely customer centric in terms of taking feedback, thinking about it, acting on it, and just taking it really seriously.

And so, in that sense, it’s not so different from the other jobs, it’s just a slightly bigger spot. And then, the advantage of having a lot of other data to work with is that you can kind of triangulate: this is something that seems really common; this seems like an uncommon thing, but maybe there’s something else going on at this organization.

And we’re always trying to do that. And then again, the ability to bring things out that maybe people outside of Figma are not thinking as much about, or people outside of the design world.

I think design sort of takes for granted the idea that design is a differentiator for AI. But I don’t know whether the rest of the world always understands that the ability to whip up a screen really fast is not the entirety of design. That’s not it.

And so sometimes helping people understand, oh, it’s also about the information architecture. It’s also about the transitions between screens. It’s also about the fundamental value proposition of it. And so this role can kind of help us do that too. That’s the goal, right? You’re always trying to do these things better, but that’s sort of the goal of it.

Value propositions for design

Jesse: You touched on the notion of differing value propositions for design, and we’ve, in our previous conversations on the show, have talked about the way in which the impact of AI in particular is really a function of whatever that value proposition is for design within an organization.

And I’m wondering about what you are seeing in terms of the range of value propositions for design that are even out there right now. Because in my work as a leadership coach, I hear from leaders who come from a really, it feels to me, like a broad range of different, positions in terms of how the value proposition of design is a function, and therefore their value proposition as a design leader, is perceived in their organizations. And I wonder just kind of taking the broad view before we even get into how AI impacts all of it, what are you seeing from your vantage point there?

Andrew: So when people say design, right underneath that is like brand, visual design, information architecture, interaction, and I think that also broadly separates into like, marketing and brand design and then like digital product design. And definitely within organizations, you might differentiate based on something different within those different spheres.

But I also think that outside of design, not many people think about it that way. And so there is some like risk and danger in sort of like slicing it too thin, the different ways of differentiating. But the thing that you seem to have touched on there is also that it’s like part of the strategic value of the organization or the strategic set of choices.

And, hey, we’re gonna invest in being the best retail logistics, and we’re gonna do an amazing job at that. And we’re gonna design all of our internal software to facilitate incredible logistics. None of that sounds exciting. And yet there are some incredible businesses that create great experiences that are focused on that kind of thing.

And I think what’s really interesting right now is that more leaders are recognizing that that is how you do it. You don’t do it by generating a screen. You do it by thinking about how are we gonna use this to, like, support our strategic decision making and create software that’s incredible for helping us on whatever our competitive advantage is.

And so they do align. And what has been interesting to me is the degree to which outside of design that kind of isn’t… I don’t know… That… that recognition is not always there. And the idea that design is the differentiator is exciting to people. And then you sort of get down to it and you’re like, exactly how are we gonna do this? And what are we gonna do?

And then that’s where the job of the design leader is to say, “Hey, we should really align on this thing because strategically this is where we need to be as an organization.” And that seems like a big opportunity that more and more leaders can step into. That has been an interesting trend as well, because it’s not just about how the screen looks, it’s also like how helpful is it towards the goals?

Peter: I wanna reflect on what I’ve witnessed in terms of Figma’s relationship to design and how it might speak to some of these trends that we’re talking about, right? So Figma launches, it’s very much a design tool. It’s talked about as a design tool.

But then as Figma becomes more powerful, Figma is seen as a means by which designers can better collaborate and interact with non-designers, right? So product people, engineers, reduce the amount of coordination necessary for handoffs, and other kinds of just alignment.

You know in 24, Config was interesting in this regard. So Config, the annual conference, because in 24, Figma seemed to be positioning itself… on the tote bag, I think it read “for people who build products,” right? It kind of was moving away from a designer specific space, and I got the sense it was because it saw itself as part of a dialogue around product development, and design is part of that, but not, the only voice.

In 25, this past year, Figma seemed to go all in on actually no, we’re for designers and all the new tools and everything was, was really about design capability. I found that curious, and I suspect it has something to do with AI and maybe the way that AI is affecting role definition within product development environments, and like leaning more into like design as this activity actually makes sense again, with AI providing a different kind of power, a different kind of agency or capability for the people using the tool.

That was a long question with some threads in there, but, but I’m curious like how that relationship between Figma, at least the commentary, the positioning Figma as a design tool, as a product tool, as a design tool reflects some evolution that we’re seeing in design and design practice.

Design is everyone’s business

Andrew: So the two things I would say is that we have this saying design is everyone’s business. And that’s partially a reflection of what happens where more people want to work in design, on design, who are outside of a specific design role.

We have a stat, 56% of those involved in like the digital product process are doing a major, design, like, macro task, like prototyping as a big part of their job. So design is sort of everyone’s business, and it’s partially because it’s as we just talked about, like strategically become really important. People see it as this really important lever to creating great experience, to building a business that’s really successful.

And I think as part of that, you do have more roles sort of blurring where designers are doing things that maybe engineers would’ve done before. Like maybe they’re working on code, maybe they’re doing things that PMs would’ve done before where you’re sort of writing up a PRD, but you also have other people doing things that maybe designers would’ve done before. Like, here’s this prototype.

And what’s been interesting in this study that we’ve been running, which we’re gonna share shortly, is that it’s born out of a desire to sort of communicate across functions. These become like boundary objects where you’re trying to convey to a product manager, Hey, here’s why I think we should do this. Or the product manager is trying to convey to the designer, here’s why I think we should do this. And so I think you’re right, Peter, that AI tools are driving this sort of shifting and blurring of roles.

But it’s towards generally people trying to do work that they’re really proud of and that, achieves the goals that they’re trying to achieve and, helps their organizations and ultimately helps the people that they’re trying to support.

And I think we see that happening more and more. We see sort of like an acceleration of it, whereas before it was kind of happening. That’s one of the things that was interesting about Figma is more people kind of just got in as it was easier to do it through a URL.

And then more recently, more tools like Make which is our zero to one app creation tool. More roles are doing that kind of thing in an effort to create better products, which is to wind all the way back to your original question. We are always trying to figure out how to help people ship better products get those products out into market, and so they can figure out, are those the right products, should something else happen?

And I think what you’ve seen is an evolution in the understanding of exactly how to do that and who’s involved, and then also in the tools and their capabilities, which have certainly increased over the last couple years.

I’ll just give you one stat. 80 plus percent of designers and developers think that learning to work with AI well will be important to their success in the future. And I think leaders have to figure out how to navigate that because not everybody feels like they have the time and space to work and practice and try to use tools that are different or feel different, have different capabilities, and then also you have to figure out which parts of the process you should keep, which parts of the process you should change.

All while the pace has accelerated and the expectations of shipping have also accelerated. So I think that’s an interesting leadership topic to think about. Because, you’ve gotta provide a lot of air cover for teams right now.

Jesse: I’m glad you brought up the leadership angle because I really see this playing out in a lot of organizations right now where there is this tension between the freedom to experiment and the need to continue to deliver results, right? And the desire to have a strategy, have an answer right away about where you’re going, while also continuing to create the space for the unknown to come in because there’s still so much need for experimentation.

I’m wondering about, really, the big picture of how you think about how these technologies are impacting things broadly. We’ve talked about kind of where it intersects with various aspects and angles of design practice and design leadership. But as someone who has to think about this stuff now all the time on an ongoing basis in order to continue to deliver insights for Figma as an organization, how do you think about, thinking about AI.

Andrew: It’s so meta every time we do one of these reports, you’re like, what’s the best way to, use generative AI in this? Does it have a role? Should we generate something and then look at whether we like it or should we write it and then ask for input or should we just not use AI at all?

And you know, the truth is, I think this is true for designers as well, as the answer is: it depends. The answer is, it depends on what’s useful in that moment.

There’s this quote from one of our AI studies, it’s hard to run a restaurant when the menu keeps shifting. And that’s kind of how people feel. Which model should we be using, which tool is out. All of that is definitely true. And so I think from like a leadership perspective, you’ve gotta create some space for this, whether it’s like, “Hey, show me your latest way that you’re using AI in your process” and you have three or four people demo, that’s a super common thing.

Whether it’s filling out the strategy slide for your CEO, this is how we’re using AI in our process. And then kind of, maybe fudging your way into whether you’re really doing that a lot or not.

And then also trying to create a little bit of extra space for experimentation. The hackathon is very much alive and well. And I think organizations are using those things better than they have before.

But sometimes it also just means conveying to the team that, Hey, if you don’t think AI is really helpful in this, don’t use it. And that’s easy to say, but then someone says, Hey, the engineers are done, what does the next stuff look like? What should we build next? And so trying to create some space when, if it’s easier to generate code than it is to create designs, then you might have to figure out how to change the working process a little bit to make it simpler or to bring more people into the process.

So all that to say, I think my overwhelming thought. Is that it is uncertain exactly how to build all these things in. And so as a leader, you’ve gotta be pulling from a lot of different directions and studies and experimenting yourself at what maybe could or should work. But ultimately towards the goal of whatever your objectives are.

Like the goal isn’t like use AI usually. Actually that’s not true. The goal of many AI initiatives is use AI. That is, that was one of our findings from the study was overwhelmingly it was experiment with AI, or the other catchall is improve customer experience.

So I think that is partially true, but I think it’s creating some sense of, like, sort of stability, it’s okay to experiment. It’s okay to not use it. And figuring out also how to bring people along who are not using it at all because I think that’s a rough spot to be in right now, is not using any generative AI in your process. I think you’ve gotta find some way to do it. And, part of that is probably working with your engineering leadership at, ” What are you guys doing? How is this working? What could we do to make it simpler or plug into your workflow?”

The challenges of Generative AI

Peter: It’s interesting you say that, given, I don’t know, what feels like some of the news of literally the past week or so, where it feels like we’re starting to hear the early results of product development teams trying to use generative AI, and at least publicly, the commentary is not positive, right?

I think a lot of folks have put a lot of time and effort and money and are not seeing… I don’t know what they were expecting, but not seeing gains, not seeing, not seeing impact or results that they were expecting. And so, there’s definitely been a bit of a craze.

Andrew: But this is the opportunity. I’m excited you brought that up because I think this is the opportunity for design and design leadership. If things are not working, that is often a place to prompt a reexamination of, ” Well, what are we doing? Are we just like using this technology just because we could, like what are we actually trying to achieve” and then trying to design something, both internally, right? What is our process like?

There’s sort of this meta design thing that I think both of you are very skilled at and skilled at thinking about, how do we help engineers ship things? How do we ship better things? Let’s examine that. And then there’s also this sort of like, well, did we actually try to solve like a customer problem that they had or a user problem? Did we even conceptualize this thing in the right way at all?

And those are both amazing spots for design to step in and show, show leadership, because I look at that 80% stat and I think that this is not something that is going away. So 80% think that this is critical to their success in the future, and embedded in that is their workflow and AI powered products and a lot of other things.

But in general, these are people who are working with this stuff every day. There are probably quite a few skeptics in there. And so it says to me that we have not found all of the great use cases for this technology yet, and we have not designed things well so that people can accomplish their goals, whether that involves generative AI products or not.

And so it seems to me that in a spot, if there are things that are not working, that’s a great opportunity to step in and say, Hey, Design can help us make sense of this mess, and we have a set of tools or just I can help make sense of this mess.

You don’t even need to bring design into it. You could just say, I have a set of tools and tricks to be able to do this. You know, we saw it with mobile, we saw it with the internet. These things sort of repeat. They go in cycles and then eventually the application layer gets designed well and things become more useful.

Maybe that’s like too optimistic of me. But it seems to me that there’s an opportunity in that if there are areas where it’s not working well.

AI Wariness

Jesse: You touched on the skeptics, and this is an interesting part of it for me because what I hear from leaders inside organizations, when we talk about, you know, how is the experimentation going and are you getting any traction with your experiments? And they often describe a level of kind of a cultural resistance to these technologies that to me feels like it might be particular to design teams, and something about design as a process that makes the practitioners less willing to embrace these tools in the way that their product and engineering peers and partners are.

And I wonder if you’re seeing something similar in terms of cultural resistance to these technologies within design teams specifically and where that resistance is coming from.

Andrew: So the data we have from January is that like about 30% of designers have adopted AI into their regular workflow, and about 60% of developers have. So that’s a pretty big gap that would sort of support some of what you’re saying there.

I would expect that it would’ve changed from January to now, August. I would also expect that, if you put something in a Chat GPT and you ask it some questions about something, do you think about that as part of your design process?

Maybe, maybe not. So there’s maybe some usage that is not quite captured in that, the design process is sometimes just wrangling your collaborators and your stakeholders. That’s part of it, too.

But I remember the early days of both mobile and digital design, which you guys probably remember even better, where, do you remember the phrase above the line and below the line where the marketing campaign, the below the line things were the digital stuff.

And then you had the above the line. That was all the TV stuff. And then, there were people who said like, I’m never gonna make websites. I’m never gonna work on that. And then over time, you get a little more comfortable. You add some skills to your level of understanding and the things you feel good at, and then you start to branch out into things that maybe you didn’t feel as comfortable with to begin with.

And, I think this is always true to diffusion of innovation. There are people who are really early adopters to things. There are people who are early career and they’re just learning a way to do things from the beginning. And then you see it spread and the parts that are really useful tend to really stick. The parts that are less useful sort of fade away. And ultimately at the end, if something is really helpful, that’s a, major general purpose technology,.like many, many of us think that AI is.

Designers are ultimately also part of making that happen. And so I don’t know if it’s a distinct thing with design, but I do think there are sort of patterns that play out here.

Jesse: I think that it’s interesting because the work that we do, as Peter often likes to refer to, sits at the intersection of technology and the liberal arts. And a lot of folks came into this work from the liberal arts side.

And there is a bit of resistance, I think, to embracing too much technology in the creative process itself. It’s fine if we want to build technology with technology, but when we start looking to technology to provide pieces of what we think of as our creative value proposition, that starts to make people uneasy and it starts to make people resistant.

Andrew: I mean the fascinating thing there is if you look at other fields and other studies, there was this MIT study about if, if college students write essays with AI, they like basically don’t remember the essay later, and it gets progressively worse over time. And if you think about that for a minute, it’s because at the end when they’ve done this four times, no one has ever given them any feedback. They haven’t seen anything come of it. They sort of stop trying.

And sometimes you do have to like, try and work and think really hard and fire all your neurons and synapses and pull it in. And it’s like, as, like John Maeda would say, you have to think uphill sometimes.

And I think that’s partly where some of it’s coming from, that you know the answer is not generating a page that looks visually interesting. The answer is creating some solution to a problem, and sometimes you have to think through it and work through it really hard and sketch it out in whatever form you find easiest.

So that part totally resonates. People have very different creative processes, and if you want a novel solution, you might have to pull it out of some sort of generated, here’s a list of 10 possible solutions. But sometimes I think people would tell you they look at 10 possible solutions, they hate them all, and then they know what to do.

Peter: Mm-hmm.

Jesse: I want to come back to the notion of where this technology is best applied because, that I think is part of it for some of these skeptics, that there are places where they don’t see it playing effectively, and there are other places where maybe they might see a place for it.

And I’m curious about those broader patterns of high value use cases teams are seeing in these experiments. I know that it’s still early days and there’s not a lot of great data, but you’ve got, as we’ve touched on, maybe more data than anybody on some of this stuff, and so I’m curious about what you’re seeing about where people are seeing the value of these technologies in these creative processes.

How we use AI

Andrew: So I don’t have survey data that says like, this is it, this is the spot. What I do have are a lot of anecdotes that prototypes and ways of communicating an idea to people have become like a go-to place for generative AI.

And that’s because you can sort of do them quickly. You can think about what works and what doesn’t. And then, you know, a prototype is worth a thousand meetings. That saying is still very true.

And so the place that it’s helping most seems to be different disciplines communicating better with each other about what they’re thinking, in order to lead to a better solution at the end that actually gets shipped.

And that is an important nuance because it isn’t like you prompt the thing and then you get the final and then you’re done, right? You prompt like a potential change to a flow or something important and you get an idea from it, or you share it with someone and they get an idea.

So it’s like a midpoint in the process. That seems to be where teams are finding a lot of value here.

And then in addition, this is totally tongue in cheek, writing emails more quickly or responding to maybe some like feedback or something that seems to be like across every job role. Everyone seems to be using it that way.

And then, sorry, the other one is pulling out research insights and summarizing those things quickly. The risk there is that you don’t actually fully digest the research and really pull out what’s super important. But those summaries are done. And so that is the tension, right? If the summary needs to be done, you can do that very quickly now, but that is not quite the same thing as getting someone to care about it or getting someone to really fully get like, here’s the best answer, but it’s also a faster way to disseminate research insights. Here’s this clip that’s really helpful, you should look at all those things seem to be getting faster as well.

Peter: I’m gonna pull back a bit, and some of my own anecdata, but in my work with design leaders, I’m increasingly seeing, and I’m wondering, Andrew, if you’ve seen this, if you had the data to back up my hypothesis that’s your job is, to be our data repository.

But, there’s, like, been some recognition that the products that we’re creating have gotten complex and perhaps overly complex over time. Companies acquire other companies. Companies keep building things, and what I’m seeing more and more of is a desire for design at the highest level to be a kind of a more horizontal thread to cohere, to create something cohesive that spans an enterprise.

I’m having a conversation, one of my clients, an insurance firm, sizable insurance firm, and I was looking at the opportunities of service design to create something that feels like it’s member driven as opposed to corporate driven. Because members are going across the silos within this organization, and I’m wondering, 1) what you’re seeing, hearing in terms of that, and 2) what role does Figma play in something like that, right? One of, one of my challenges…

Andrew: we will take challenges. I like challenges.

Peter: With Figma is it gets associated with design, but, and I think you would recognize that it only addresses a part of a much larger design process or potentially process.

Now to the degree to which you can use diagramming and visual communication to help explain more than digital product design, and maybe there’s the solution, but, like, I get a little concerned that people associate Figma with design, but then they think of Figma as the thing where I draw screens.

And so two things.

How do we help these leaders with kind of this big tent messy end-to-end service experience? Or are you seeing that as well? And then, How do we think about supporting folks spanning enterprise wide challenges?

Andrew: So a couple things. I think certainly diagramming, storyboarding, a lot of times those things get communicated in decks as well, and Figma Slides is suited for that too. And it’s nice to be able to say, Hey, let’s take this software that’s part of this process and let’s contextualize how it fits into the larger way in which this gets passed from point to point. And so that’s how I would think about that.

Which is not too dissimilar from how it was done before, except now it lives in a URL, which is kind of nice. And you can participate with somebody around the world, different time zones. So probably more to be said there, but certainly you can contextualize the digital product or the software in a way that is I think, really helpful.

And then also you can get interesting feedback on it from people whether that’s fire emojis or whatever else. If that’s the kind of meeting you need to have, you can have fire emojis.

So, and then taking the other part, definitely as a stitcher-together of distinct interactions or products or goals and stakeholders and systems. I think design has probably always done that really well, distinctly well, just because often the people doing it understand the humans involved better, and then, if you understand how the information needs to flow, you can do all that better.

I don’t have any data to support that as something that’s happening beyond the same conversations I’ve had, but I think increasingly it will be really important, as these things get more multimodal, whether it’s input,either an image of the thing you’re trying to do or the text of the thing you’re trying to do, or click a button of the thing you’re trying to do and then, we’ll give you the answer back in audio form or here’s a video of whatever you were asking about.

When you start stitching together all those inputs and outputs, it becomes even more important. And then when you start needing to orchestrate agents to do any of these processes, you have even more inputs and outputs.

And ultimately, there’s still some human that’s responsible for the decision. And again, design is really critical to actually making sure that human can understand the decisions being made, can adjust it.

And so if you take what has always been done, which is the ability to stitch these things together to create a better experience at the end, ’cause you understand the humans and then you expand it to the complexity that is now possible, and then the agents that are also now possible and the new interaction design challenges. I think that our customers are saying design is becoming more important to doing those things well.

And the design, sort of, like, bag of tricks to use like a very, very reductive term, becomes more important.

I think all of that is very true and really happening and will become more important as the app layer and the interactions that we have with LLMs and with the software systems that are being built on top of them, as those things become more important, I think that design skills become more important too.

But, you know, that’s the view of the guy at Figma, right? Of course, the guy at Figma would say that would think those things. But, I don’t know. I’m not sure how else you do this other than diagramming it out and thinking about inputs and outputs to the systems and somebody has to do that.

Jesse: Mm-hmm.

Peter: Well, and that, kind of speaks to something I’ve been feeling and or sensing, which is, and Jesse and I, maybe coincidentally, in a couple months are speaking at the Service Design Global Conference, but service design, has a set of practices, service blueprints and whatnot that I think become increasingly valuable when, I don’t think much about our agentic future, but if there’s gonna be a bunch of things just kind of operating out there, coordinating, corralling, aligning, orchestrating that behavior becomes super important and doing so in a way that is responsive to user needs and…

Agent wrangling

Andrew: Well, then you can understand, just the fact… understanding what did the agent just do, you know? And I think, users, you can very quickly envision how they become like air traffic controllers that need like a set of effective dashboards to be able to orchestrate all of these things so that like they don’t book the $10,000 trip to Bali. They book the $1000 trip to Bali, or, their bill gets paid on time instead of being charged a late fee.

And as the gravity of the decision increases, the importance of the design increases where, you know, it’s kinda like running a power plant. You really wanna make sure the person running the power plant understands what’s going on in the power plant, and then the process by which that happens becomes more important then as well.

Jesse: Mm-hmm. I find myself wondering about the implications of all of this for design’s influence on product strategy, because you’re talking about an approach that potentially really kind of flips the equation in terms of requirements driving design, turning into design driving requirements.

Andrew: I mean, it’s an interesting provocation because if it’s simpler to generate features, which I don’t really mean that it’s simple, but if, let’s just say, it’s simpler to generate features, then how the features fit together towards a certain goal, and the context by which those features are shown, or how they’re shown, becomes more important.

Those things then become really critical and then the rest of it is maybe less critical.

And I think what, we’re talking about is, more of a future state, right? I think for most enterprises, you can’t just like generate and bang out a bunch of features at this point.

But if it is easier to create them, then how you feel using them becomes more important.

And so then the question is, how do we create the right feeling for what people are experiencing, and then how do we make sure that they’re successful? Which is design.

Quality and other standards of success

Peter: Well, we spoke around the same time that the AI report was launching and, you mentioned that insight that you shared earlier, where designers felt like they were getting more efficient, but they weren’t necessarily producing better work. At that point, we talked a lot about quality and defining quality.

Something, I think about it a lot is design organizations need to have more explicit standards of quality that they then can uphold through all this activity.

But then as we were talking about the backlash that we’re hearing in the last, just the last couple of weeks around some of these generative AI engagements, and I think a lot of that backlash is companies went nuts trying things out, but without a sense of direction.

They were just trying out for the sake of trying it so they didn’t have standards of success. And then when they finally took stock of what’s happening, it’s like, well, it’s not doing anything. And it’s like, yeah, it’s not doing anything, ’cause you didn’t have a point of view, you didn’t have a direction you were going and you were just throwing spaghetti against the wall in hope that stuff stuck.

So intent becomes very important. But then this last piece that you’re talking about around the coordination, this orchestration, all this activity that’s going on in the system and the role that design can play in helping manage that. I start now wondering about, what are the design skills, design practices that become increasingly important?

And I’m thinking about that in light of what we’ve seen over the last six to 12 months where every job description for a designer is talking about high craft, but what you were just mentioning is not high craft design in the way we think of it with like high polish, high UI, subtle micro interactions and all that kind of stuff.

it’s a lot of IA, it’s a lot of interaction design, it’s a lot of workflows, it’s a lot of conditionals, making sense of all that, with the interest of delivering value to a user.

I’m curious where you see the intersection of quality, craft, intent, new skilling. What are you witnessing?

Andrew: I mean, it, it’s gotta be both, right? And I think one of the reasons I focused on the product strategy, higher level experience is because that is often under-discussed.

And the point about craft and micro interactions is talked about a lot. And I think both are really important.

You can’t have an experience where, oh, it’s really great. I can see exactly, like, the way that my information got shared and it did this really interesting animation that now I know exactly what it means. But then like ultimately, on the other side, did it actually get action?Did whatever I was trying to accomplish, get accomplished?

You can imagine like an agent, oh, the agent, it’s really great. The agent said it was gonna buy the shoes that I was looking to buy, but like, then it doesn’t buy the shoes or it overpays by, you know, a hundred dollars on the shoes.

Those are like distinct things, and yet you can’t ignore one in favor of the other. But you do have to think about both.

So, I would imagine that some designers would specialize in one part or specialize in another. Potentially if the higher flows are not being thought about, someone will step in and try to think about the flows after the experience doesn’t work or people give feedback.

And so someone will do that, and it’s a question of who is going to do it. Who either feels like they have permission or takes the opportunity to do it. And so that’s kind of how I would think about it. And I do think it’s worth thinking about the definition of craft as helping people have, like, the feeling you’re looking for them to have with the tools that you have available.

I don’t know that that’s like a Figma definition, but that’s how I would think about things like craft.

Jesse: Along those lines, there was one finding from the January study that I found well, you know, almost counterintuitive, which had to do with how organizational scale impacts how these technologies are being deployed in organizations. I wonder if you can kind of recap what you found in the study.

Andrew: I mean the core of it is, really it’s the smallest organizations. So your, like, one to 10 employee organizations and how differently they think about AI to the success of their products, and even how they are thinking about work. And I think that’s not really that surprising, right?

Once you hit two-, three- hundred people, you have like some well-worn paths. And unless like the number of people changes dramatically, you probably would kind of keep going in the same way.

But if you’re a new company and you’re thinking about how to do something and you’re probably starting with the premise that you’re gonna be AI-powered in some way, those organizations are different.

And so then that also has implications for, if you’re a large organization trying to increase use of AI for the express purpose of increasing use of AI, splitting small teams out to go do it, and almost like telling them you’re going to either work this way or you’re going to build an AI powered product.

You might have more success with like a small, small team that is just in the work. That is just building.

And, I don’t know, it’s an interesting finding ’cause I think it speaks to the accessibility of the technology, like, you can do things, has never been greater.

And what we’re all trying to figure out is like the best way to do things. The most effective way to create products for users. Those are the things that haven’t really been figured out. Yeah, just trying them, it’s easier than ever.

The Power of Writing

Peter: Your role is the head of insights. I don’t know if that means you actually have a team that you’re leading, but there’s a leadership component to that.

And I’m curious, so ours is a podcast about leadership, and I’m curious, what leadership skills you’ve been developing, particularly within a place like Figma, right? Because as an analyst you were probably doing your analysis and some consulting.

Now you’re in-house, now you’re navigating organizations. Now you’ve got politics. Now there’s probably people who, if you’re delivering insights, you’re probably finding out things they don’t necessarily want to hear, right? ‘Cause it might go against what they think, what they thought the reality was.

And so I’m wondering what, are the leadership skills you’ve been leaning into to get traction to bring people along to your point of view, your agenda, within Figma and what that journey’s been like of developing kind of that leadership approach.

Andrew: One of the interesting things is the power of writing.

And I thought it would be less important because that was my job at Forrester. Like the core job is like you create insights and you put ’em into a report and then you do a lot of other things. That is not dissimilar to my core job at Figma.

And I think, I thought that writing would become less important because it’s such a visual company, it makes like a tool. And writing things down still has tremendous power. It still creates a lot of reach and then it forces you to think about what you think is really important.

And then ideally, you’re creating some other dissemination mechanism too. You know, you’re making a video, but the video’s gotta be really quick. It’s gotta be really engaging. All that.

And I think I, thought that was less critical. And it turns out that interviewing somebody about their insights can be a really powerful thing to do.

And then writing those things down is really critical. And so, I think leaders have to make artifacts and one of the key artifacts of leadership is writing things that people can then better understand your perspective and then force you to articulate what the perspective actually is and find out whether you are aligned with the people around you.

Jesse: Andrew, as a professional asker of questions, what are the questions you are most interested in exploring next?

Andrew: I am not tired of AI and design and what the interactions will be between those things. I just feel like you keep peeling back the onion and what are the great practices that teams are using? What are people finding success with? What are people excited about? What are people nervous about? Those remain really important questions.

And then I think importantly, what isn’t changing about that is still a really important question, because it still sure seems like getting a team to understand a user’s perspective and actually getting a real user perspective, not like, some version of it that they’re presenting to you, those things still seem really important and incredibly difficult. You know, AI just doesn’t do that. Other than maybe creating some more scale and more interviews, maybe summarizing it.

So what’s changing, what isn’t changing? I’m excited to keep researching it.

Jesse: Fantastic. Andrew Hogan, thank you so much for being with us.

Andrew: Thanks for having me.

Peter: Yeah, this has been great. Thank you.

Jesse: If people wanna find you on the internet, how can they find you?

Andrew: LinkedIn.

Jesse: That’s where it’s at.

Andrew: I am, I am a big LinkedIn fan. I do not engage in the other networks nearly as much. Find me on LinkedIn.

Jesse: Terrific.

Peter: Sounds good.

Jesse: Thank you.

Jesse: For more Finding Our Way, visit findingourway.design for past episodes and transcripts, or follow the show on LinkedIn. Visit petermerholz.com to find Peter’s newsletter, The Merholz Agenda, as well as Design Org Dimensions featuring his latest thinking and the actual tools he uses with clients.

For more about my leadership coaching and strategy consulting. Including my free one hour consultation, visit jessejamesgarrett.com. If you’ve found value in something you’ve heard today, we hope you’ll pass this episode along to someone else who can use it. Thanks for everything you do for others, and thanks so much for listening.