You’re an AI product designer now 💡

Summary

Dive Club Episode Summary: “You’re an AI Product Designer Now 💡”

Release Date: January 6, 2025

In this insightful episode of Dive Club, host Ridd delves into the evolving landscape of product design in the age of artificial intelligence. Entitled “You’re an AI Product Designer Now 💡,” the episode features a rich discussion with notable designers Maggie Appleton, Michael Wandemeyer, George Kedenberg, Joel Lewenstein, and Kyle Turman. The conversation navigates the integration of AI into design processes, the importance of understanding AI capabilities, and the philosophical shifts required for designers to thrive in this new paradigm.

---

1. Embracing AI in Product Design

The episode kicks off with Maggie Appleton sharing her unexpected journey into AI product design. Initially unaware that her product had AI elements, Maggie realized the pervasive influence of large language models (LLMs) as she delved deeper into her project.

“Over the last couple of months I've been designing a new product and I didn't think that it was an AI product, but the more that I work on it, the more that I can't help but notice all of the little ways that LLMs could be used.”
(00:00)

This realization underscores the subtle yet significant role AI plays in modern product development, often integrated seamlessly without explicit recognition.

2. The Necessity of Understanding AI Capabilities

Michael Wandemeyer draws a parallel between designers understanding AI and carpenters knowing their materials. He emphasizes that just as carpenters must comprehend wood to build sturdy structures, designers need to grasp AI’s potential to create robust, interactive systems.

“I need to understand the material I'm working with in the same way that like carpenters understand wood really well... what you are actually designing is a live interactive system. There's a ton the web can do that we don't take advantage of because designers don't know what's possible.”
(00:17)

Maggie Appleton echoes this sentiment, highlighting that while designers might not need to train AI models or write API calls, a foundational understanding of AI enables them to envision and implement innovative solutions.

“Having a baseline understanding of how things work allows you to see what's possible.”
(00:42)

3. Raising the Ceiling: The Art of the Possible

A significant portion of the discussion revolves around the concept of the “Art of the Possible.” George Kedenberg articulates this philosophy, encouraging designers to push boundaries and explore what could be achieved with emerging technologies, rather than being constrained by existing limitations.

“When challenged with a very difficult task... let's try it. And I think that that's a really intangible thing, but it is born of a place that you really are aiming for the highest possible end outcome...”
(01:27)

Maggie Appleton connects this approach to traditional design methods, which typically start by addressing user problems or business objectives. However, she suggests that with AI being a transformative material, designers must also consider what the technology itself can enable.

“Which means designers aren't just working backward from user problems anymore, we're also working backward from what this new technology makes possible...”
(02:15)

4. Designing with AI as a New Material

The conversation shifts to viewing AI as a novel material—akin to “alien space metal”—that designers must learn to manipulate and innovate with. Joel Lewenstein from Anthropic emphasizes the importance of experimentation and pushing AI’s boundaries to fully understand its capabilities.

“The only way you really understand a material super well is by just experimenting with it and like trying stuff and just like continuing to push the envelope...”
(02:28)

This perspective encourages designers to adopt a hands-on approach, analogous to how artisans experiment with new materials to discover unique properties and applications.

5. Overcoming Doubts: Starting from AI Capabilities

Addressing common hesitations, Kyle Turman challenges the notion that designing with AI is inherently flawed or “solutions in search of a problem.” He advocates for an exploratory mindset, where initial AI-driven prototypes can organically evolve to address real user needs.

“I’ve come to see solutions in search of a problem as like not a dirty word at all... there's the germ of something here and we're going to explore it.”
(04:34)

Maggie Appleton reinforces this approach by sharing her strategy to immerse herself in AI tools and continuously experiment, ensuring she remains at the forefront of design innovation.

“My plan right now is to just expose myself to AI as a material as much as I possibly can... because in order to be the best designer I can be, I need to be able to see what's possible.”
(05:00)

6. The Future of AI Product Design

As the episode draws to a close, the discussion turns to the inevitability of AI integration in product design. Kyle Turman envisions longevity in AI-driven design work, citing the complexity and depth of capabilities that AI models like Claude possess, which require continual exploration and understanding.

“There’s probably still like years of design work left because there's just all these things that the model can do that people don't know how to get... there are a lot of interesting design problems.”
(08:15)

Maggie Appleton concludes by affirming the transition towards AI-centric design roles, encouraging designers to embrace this shift and utilize resources like Dive Club to navigate the evolving landscape.

“We're entering a world where, whether you like it or not, you're probably going to be an AI product designer soon. And hopefully this show can be a resource to help us all figure out what that means.”
(08:41)

---

Key Takeaways

1. Understanding AI is Crucial: Designers must familiarize themselves with AI capabilities to fully leverage its potential in creating innovative products.

2. Adopt an Exploratory Mindset: Embracing AI as a new design material requires experimentation and a willingness to push technological boundaries.

3. Art of the Possible: Aim for the highest potential outcomes rather than settling for pragmatic solutions, fostering groundbreaking innovations.

4. Integration Over Isolation: AI should be seamlessly integrated into design processes, enhancing rather than overshadowing traditional user-centered approaches.

5. Continuous Learning: Staying updated with AI advancements and engaging with communities like Dive Club is essential for designers to remain competitive and effective.

---

Notable Quotes

• Maggie Appleton (00:00): “...the more that I can't help but notice all of the little ways that LLMs could be used.”

• Michael Wandemeyer (00:17): “There's a ton the web can do that we don't take advantage of because designers don't know what's possible.”

• George Kedenberg (01:27): “...aiming for the highest possible end outcome and are willing to fight tooth and nail for that rather than looking for the most pragmatic solution.”

• Kyle Turman (04:34): “...there's the germ of something here and we're going to explore it.”

• Joel Lewenstein (02:28): “...just trying stuff and just like continuing to push the envelope of what can this thing do.”

---

This episode of Dive Club serves as a clarion call for designers to integrate AI into their creative processes, not as mere tools, but as integral components that redefine the boundaries of what’s achievable. By fostering a deep understanding of AI and maintaining an experimental approach, designers can unlock unprecedented possibilities and drive the future of product design.

Transcript

[Maggie Appleton]

Over the last couple of months I've been designing a new product and I didn't think that it was an AI product, but the more that I work on it, the more that I can't help but notice all of the little ways that LLMs could be used. But these opportunities are only visible if you know what the materials are capable of.

[Michael Wandemeyer]

I need to understand the material I'm working with in the same way that like carpenters understand wood really well. Right. And like architects understand, if you're going to build a five story building, like you need to know what materials you're going to put in the support pipe so that it doesn't fall down. Even if the thing you are designing is like pixels and figma or seems to be to you, what you are actually designing is a live interactive system. There's a ton the web can do that we don't take advantage of because designers don't know what's possible.

[Maggie Appleton]

I think that's Maggie Appleton talking about the value of understanding how code works. And I think you can apply that same logic to AI as well. I mean, you don't have to be able to train your own model yourself in the same way that most designers don't have to write API calls. But having a baseline understanding of how things work allows you to see what's possible.

[Michael Wandemeyer]

See, I knew nothing about language models and AI. I was like a normal human, right. I started getting into it and that was really important for me to then be able to, once I joined a team, understand what was possible, like, what the limitations are.

[Maggie Appleton]

A big part of our role as designers is asking, what if we're the ones who are responsible for raising the ceiling of what something can be. It reminds me of how Michael Wandemeyer talked about the art of the possible.

[George Kedenberg]

Looking for the art of the possible. So when challenged with a very difficult task, not trying to block it and to say, like, what is it that we can do given these constraints, but really to ask the question, like, I wonder, like, what if we could do this? Is that possible? Like, let's try it. And I think that that's a really intangible thing, but it is born of a place that you really are aiming for the highest possible end outcome and are willing to fight tooth and nail for that rather than looking for the most pragmatic solution.

[Maggie Appleton]

And historically our starting point for figuring out what's possible has been working backward from user problems or maybe business objectives. And then, you know, we use different processes to help the team narrow in on a solution. But Times are changing and that's why I love this clip from George Kedenberg, who's a designer at Humane.

[Joel Lewenstein]

I kind of look at it as this like alien space metal that has crash landed on the planet. And it's a new material. It's like a new thing that as designers we get to work with.

[Maggie Appleton]

We can't ignore this space metal and it's here to stay. Which means designers aren't just working backward from user problems anymore, we're also working backward from what this new technology makes possible because we're entering a world where the products that ignore AI are the most likely to go extinct. Now, this might be a little bit of a red flag because, you know, it starts to feel like solutions in search of a problem. But that's why I want to highlight this clip from Joel Lewenstein, who's the head of product design at Anthropic, which is the company behind Claude.

[Kyle Turman]

I think solutions in search of a problem is such an interesting phrase. I think it's generally felt to be derogatory, pejorative. Like people say that as a sort of like you shouldn't do that. And certainly like the sort of capital D design school would say, understand user problems, start anchor there. Any good design crit starts with, here are the user problems. That's what endures, right? Like that is the technology changes, but people's problems stay the same. I've come to see solutions in search of a problem as like not a dirty word at all, I think as long as you just lean into it saying like, there's the germ of something here and we're going to explore it. I think the only thing that really, really matters is that eventually the problem and the solution link up together. So you're solving a real problem for a real person. But I've come to be pretty agnostic as to like, which end you start from. And this may be uncomfortable. When I started for sure, we're a very like prototype heavy culture. We're a very explore things out of our own passion and intuition culture. This comes from our researchers, from our engineers, from our designers. And my sort of like capital D design brain would see all these prototypes and I'm like, but what's the user problem? And give me a user journey. And I, I've had to sort of quiet that a little bit and just not to be too cheesy, but like it's the Justin Timberlake line from the Social network. It's like we don't know what it can be. We just know that it's cool. And like, not all of it is going to be useful, but I think there is something deeply valuable to just sitting with something that is cool and compelling and you can see the germ of something.

[Maggie Appleton]

Now, obviously Anthropic is at the bleeding edge of technology right now, but that's why I started this episode with my own example. Because like I said, I'm not working on an AI product, but I would be capping the ceiling of my product if I didn't experiment with perplexity or vision APIs. And like Joel says, the only thing that matters is at some point your designs have to solve user problems, but you don't necessarily have to start there.

[Kyle Turman]

I have a diagram in my head of like, you know, a double diamond design process and sort of like tendrils coming out from the solution end and eventually finding their way to the problem end. I think that's okay.

[Maggie Appleton]

And that's why my plan right now is to just expose myself to AI as a material as much as I possibly can. Tinker with new products, spend a Saturday morning making a random thing before my kid wakes up. Because in order to be the best designer I can be, I need to be able to see what's possible. And of course, talking to people like George helps too.

[Joel Lewenstein]

The only way you really understand a material super well is by just experimenting with it and like trying stuff and just like continuing to push the, the envelope of, well, what can this thing do? You know, like imagine if you had the first time you saw wood, you're like, what do I do with wood? You know, and you would, you would start trying things and you'd be like, oh, if I bend it this way, it breaks. But if I like heat it up with steam and bend it around this other thing, I can make these like really cool curved edges that you just have to go deep on these materials and just try a lot of stuff to see where they break and to see where they don't break.

[Maggie Appleton]

Real quick message and then we can jump back into it. So this new product called genway, has totally changed the way that I do research. It uses AI powered interviewers to help you gather rich qualitative data, direct basically an infinite scale. You can even interview people while they use your FIGMA prototypes. You just tell the AI what you're hoping to test and it will have a dynamic conversation with each person as they're going through your prototype. You should see the quality of the follow up questions that the AI asks. It is really something. And the best part is they just introduced A self serve onboarding so you can get started right away. And they're even offering two months free for Dive Club listeners. Just head to Dive Club Genway to get that special offer. That's G E N W a Y. If you've been listening to this show for a bit, then you've heard me profess my love for Raycast multiple times by now. So I want to highlight a couple people who started using Raycast after hearing about it on Dive Club. The first is Rex Harris. He says Raycast is the tool that most shapes how he uses his computer and keeps him in flow. The next is Greg Hunton. He called it a life changing product and says every time he pulls a thread on something in Raycast, it wildly deepens the power and experience of using his computer. I couldn't agree more and I can't recommend Raycast enough. It's totally free to start. Just head to Dive Club slash Raycast to check it out. That's R A Y C A S T. Okay, now onto the episode. Now I want to address two doubts. First, you might think this is beyond your capabilities and I promise it's not. I mean, before hitting record on this, I read a tweet from David Wong who says he builds an MVP for a personal CRM between Call of Duty respawns. It's really, really easy to make something, anything and once you get a little bit of momentum, then it becomes addicting. And the second thing you might be thinking is that you're already too far behind. You know, other people have already run ahead and figured things out. Which is why I want to end with this last clip from Joel.

[Kyle Turman]

Kyle Turman has this great phrase. They say even if the models never got better, even if Claude 3 was it Claude 3.5 was it for all time? There's probably still like years of design work left because there's just all these things that the model can do that people don't know how to get. It just is. It's opaque. It requires this like dark art of prompting. There's a lot of like interesting design problems.

[Maggie Appleton]

We're entering a world where, whether you like it or not, you're probably going to be an AI product designer soon. And hopefully this show can be a resource to help us all figure out what that means. That's all for now. I will see you next week.