Gamma’s head of design shares how his small team uses AI to synthesize feedback, generate on-brand imagery, and maintain design quality while serving users in 60+ countries | Zach Leach

About how many pieces of feedback did you analyze this? Is this dozens? Is this hundreds?

Over the course of a week, we got about 550 individual responses. What I thought would actually work really well is something like ChatGPT's deep research on this file. The cool thing is it sort of went through all the feedback, understood what's working, what's not working, what prompts work, what don't work.

Just having tools like this allow you to stay much closer to the customer, access large-scale research in a way that would've been very tedious and expensive before. I'm curious if you can tell us a little bit about how you use AI to scale brand and art direction.

What we have actually come up with here is an ability to use Midjourney as part of our workflow to help make our art direction consistent and be able to come up with design elements way faster than before. And it's almost like I can follow those rabbit holes of creativity. I can be like, let me just explore this idea. And every one of those ideas feels like it could be something I could use.

You're able to bring this next layer of craft and detail and care to the user experience, which I do think makes a difference. Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive, here on a mission to help you build better with these new tools. Today we have a fun and inspiring conversation with Zach Leach, head of design at Gamma. Zach's going to show us how he uses AI as a data researcher, user researcher, deep researcher, and art department so he can focus on the craft. Care for details and fun he wants to deliver for Gamma's users. Let's get to it. This episode is brought to you by WorkOS. AI has already changed how we work. Tools are helping teams write better code, analyze customer data, and even handle support tickets automatically. But there's a catch. These tools only work well when they have deep access to company systems. Your Copilot needs to see your entire codebase. Your chatbot needs to search across internal docs. And for enterprise buyers, that raises serious security concerns. That's why these apps face intense IT scrutiny from day one. To pass, they need secure authentication, access controls, audit logs, the whole suite of enterprise features. Building all that from scratch, it's a massive lift. That's where WorkOS comes in. WorkOS gives you drop-in APIs for enterprise features so your app can become enterprise-ready and scale upmarket faster. Think of it like Stripe for enterprise features. OpenAI, Perplexity, and Cursor are already using WorkOS to move faster and meet enterprise demands. Join them and hundreds of other industry leaders at workos.com. Start building today. Zach, thanks for being here.

Sure, no problem. Thanks for having me.

I'm such a big fan of the Gamma team. I'm such a big fan of the Gamma product, but what I, I love the most about what you've built Not only is it a great AI product, but it is truly a global product. So how many of your customers are actually international?

Yeah, we have, I think about 60% of our user base comes from outside of the US and non-English speaking languages and a pretty significant portion of our revenue too. So we really, really focus on internationalization and localization and a lot of stuff like that.

And as a head designer, you're trying to take all that global input and make your product better. I'd love for you to show us exactly how you, you face that challenge of a very international diverse user base, but get all the insights you need for making the product better.

Yeah. Maybe I can start by showing my screen and talking a little bit about one of the features that we recently released and some of the challenges as a designer you might face with this sort of stuff. So this is Gamma. Gamma's a, a tool that makes presentations, AI-powered presentations. We released this new feature that lets people edit images. So you might generate a deck and the image isn't quite right. And with AI image editing, you can basically open this up and chat with our AI to change it to be whatever, you know, whatever works for you. So in this case, maybe I want to add some caramel drizzle to this popcorn. And Gamma will then use an image model to basically conduct that edit. And importantly, we're trying to get a sense of like, How does this work? How are people just, that's quite the drizzle. Uh, a little bit more than a drizzle. So, so you might go in here and you might say, actually, that is kind of a poor suggestion. And you might say something like, um, too much.

Too much drizzle.

Too much drizzle. And when you submit that feedback, we collect all that and really try to understand like what kinds of prompts are working, what types of edits are working and things like that. But one of the big challenges, like you said at the top, is We have a lot of feedback that comes from a lot of different languages. So this is actually some actual feedback. Um, you can see like there's just a ton of different stuff in here from all over the world. Lots of different languages.

I have to pause on the extra arm.

Yes, that actually comes up. There's a lot of like extra arms, extra fingers, extra weirdness, right? And ultimately, like people just sort of provide that feedback and we try to understand like, you know, maybe we want to use a different model for generating people, or maybe we wanna use a different model for certain types of edits and things like that. But one of the big challenges here is like, how do I, how do I go through, you know, this, this, all this feedback and get some sense of like what's working and what's not working? Especially I'm trying to understand like the translation aspect of this whole thing.

Yeah. For those that aren't watching, just in the top 10, I'm seeing 3 or 4 different languages. If you scroll through about, you know, 30, 40% are in non-English. And Zach, I know you have many talents, but I don't think you are multilingual.

Yeah.

At this level.

Yeah, totally. And so what I thought would actually work really well is something like ChatGPT's deep research on this file, right? So I'm going to ask it to do some prompting and, or ask it to do some classification via prompting and then kind of just give me some summarization of like, you know, what's working, what's not working. And it really, as a starting point to dig into kind of understanding some of this data. So I can just use ChatGPT to upload the file here. I'll just drag it in from my desktop and I won't, I won't execute the, the query now 'cause it's gonna take like 20 minutes, but I can show you exactly what, what I did before. So this was the upload and I said, hey, this is some feedback we received about our AI image editing feature, analyze it, you know, figure out what we're doing well, what we're not doing well. And then it sort of followed up with like, okay, before I get started, 'cause it's gonna take like 20 minutes, it asks me like what I wanna see. Like do I wanna see sentiment or complaints, praises, trends? Whatever, and I said, "Let's break it down for the product team," and basically say like, "What are people liking? What's what people don't like?" Things like that. So you can see that it worked for for a while actually on this, and it went through row by row.

Nineteen minutes.

Yeah, it worked very hard for me. But then you can see like here we are with with like what people love, right? And it actually gave me the translations here. Obviously, muy bien is is is obvious one, but some of this stuff in like Turkish and and. You know, some of these deep languages, you really get a sense of, of like what's working no matter the language. And then, you know, the cool thing is like it sort of went through all the feedback, understood what's working, what's not working, what prompts work, what don't work. And then you can even sort of dig in further. So after it conducts the whole deep research, you can ask it questions like, okay, now do this classification each row. Now make a spreadsheet of those of those classified, right? So like, what was the rating? What was the category of this? And ultimately what I can do then is I can put this into any other tool where I can build graphs and charts and then start to understand like, okay, actually some of the upscaling stuff is working really well. And then some of like maybe the vectorization operations weren't working super well. And so where we sort of ended up with was something where I could take all of this deep research, and copy this and put it into Gamma by pasting in text, and it'll actually generate like a presentation based on all of this stuff for me as a cool starting point. So I'll go ahead and fire this off real quick, and I want to make sure that like it's using charts and graphs. So we'll use this, but I'll say use charts, graphs, data viz, etc., not photos, and it'll take all this data, all this research, and basically bang out a little presentation for me. And so this was super useful in understanding some of the high-level points. And then it even gave me some ideas of like where I might be able to make some changes from a UX standpoint too, right? So like, these are very general and sort of, I would need to kind of think deeper about these as far as implementing them, but like the stuff that's working well, like people ask for, you know, more specificity in the upscaling stuff. People ask for more specificity and it's pulling out quotes and using citations, uh, and stuff like that. So it's a super cool use case for understanding like customer sentiment and, and as a designer, like being able to cut through all these languages and, and build these things out is, uh, super powerful.

To put this in context, about how many pieces of feedback Did you analyze this? Is this dozens? Is this hundreds? What, what is this?

Over the course of a week, we got about 550 individual responses. And, uh, I mean, that was just like way too many for me to go through and like do individual translations for or whatever.

And before these tools were available to you, ChatGPT was available to you, what, how would you have approached this? What would have, what would have been your, your process?

If I'm being totally honest, I probably would've like hand looked at maybe 20.

I think I probably would've, right?

I probably would've been like, let me go find the English ones and let me go like do some classification myself and be like, oh, like this feels like that. Or, or, you know, this feels like this type of prompt. But to be able to just like go through it and then at the scale that, um, ChatGPT was able to, to do this analysis, uh, was just, I mean, something I, I couldn't, I literally could just couldn't do.

And do you mind going back to the ChatGPT? I'm just curious, you know, you showed, um, that you use Deep Research.

Mm-hmm.

Did you, have you tested doing this kind of flow on not Deep Research? Is there a specific, you know, place you've seen Deep Research do particularly well or not?

Yeah, so the first time I did this, uh, I didn't use Deep Research and what it ended up doing was like writing a Python script with some very, very basic querying about keywords and stuff. And I'm like, that's not actually what I want it to do, right? Because I did want it to use, you know, some AI sense and some classification and sort of understand the data at a deeper level. And so it's like, sure, I'll do this. I'll make a Python script and I'll, you know, I'll make you another spreadsheet. But like, it was not nearly as deep or as insightful as like, you know, because it would just do basic keyword matching in the Python script. And so You know, I had it, I was basically gonna like either, uh, write a script that like ran some, you know, uh, uh, AI prompt on each row. And then I realized I could just use Deep Research and it would do it for me.

So, you know what I was just thinking to about a year ago when I had 1,500 pieces of customer feedback, and that's exactly what I did. I ran a script and, um, filled out the rows on each line of feedback by a single prompt, you're going to save me. I mean, maybe you won't save me time because, you know, deep research takes 20 minutes, but I'll get, I'll get better quality here and less, less pain. I'm curious, did you, were you able to glean if there were regional differences in the feedback? I mean, what I think is interesting about this is you could slice this so many arbitrary ways if you wanted.

So one thing that I, that I actually was concerned about was paid versus free. Because we provide 2 different levels of models. So if you have our Gamma Pro, you get all the advanced models and you get like the new GPT image model and stuff like that. And so that's something I actually had to do outside of this after for the sort of like conclusion of this analysis was to better understand like, is there a real discrepancy in, you know, the different models? And so we found about like a 5% rating difference After kind of, you know, going over and figuring out, okay, was this feedback from a paid user? Was this feedback from a, uh, a free user? And it does, it does go to show that like, you know, better models do have sort of a generally better outcome.

Yep. So just to take a step back, you took this very diverse, very, um, loosely, loosely articulated feedback.

Yeah.

Like hundreds and hundreds of not me anymore.

Like, what does it even mean? Yeah. Yeah.

And you took 20 minutes of, of deep research, you classified it, and then not only did you generate that output, but then you used AI, your own product, to generate a presentation that I'm sure you went and took to your product counterpoints and your engineering counterpoints and says, we need to fix too many harms. This is the top of the queue.

Yeah. Yeah, actually, um, there were some real insights out of this. I think the first one was trying to highlight the things that actually really work really well. And so, you know, you could say like, uh, this upscale thing, like maybe we need to elevate that because it has a really— people, people really like it and really love it. Um, another insight was people were complaining a lot. And again, this is something I wouldn't have been able to tell had not been translated. People were complaining about multi-step edits failing. So you can imagine a world where you're saying, oh, move this person to the left and change the background and then put a hat on him. And it would do maybe one of those things. And so from, from a UX design standpoint and like a roadmap standpoint, I was thinking, well, maybe we should design something that actually follows up with you. Maybe instead of just saying, okay, fine, I'll do the edit, let's ask and let's say like, oh, you seem to, you know, you seem to be doing, you know, multiple things. You wanna split that up? Or maybe it just automatically splits it up for you, or maybe asks for more details. And so Just trying to like get a sense of, is there something we can do when we find a prompt that's not working from a UX standpoint to just like make that easier, make that better for people?

Yeah. And then for the designers listening, Zach, you and I have been in this industry for a while and we've even worked together. One of the things that typically gets underfunded is research, user research. Um, I've never met a design team who's been satisfied with the amount of research time or capacity they have. So I can imagine just having tools like this allow you to stay much closer to the customer, access, you know, large-scale research in a way that would've been very tedious and expensive before, and hopefully unlock those insights that I know the best designers that I've worked with really want to center around.

Yeah, totally. I mean, that, that's exactly right. You know, being able to basically, you know, capture as much as we possibly can and then just fill, sort through it all, right? Yeah. Like, like we can just err on the side of getting more data now, right? Just, just put a freeform field, see what people think, see what people, people, you know, like about this thing. And then we can kind of sort it all out later, which was really kind of not super possible before. Um, I mean, maybe you had to do, you know, contextual research or like interviews and stuff like that, but now it's kind of like, well, we can get a, we can get a, you know, kind of good sense on the aggregate.

So, yeah. This episode is brought to you by Retool. There's a huge gap between impressive AI demos and AI apps that deliver real value inside your business. While most AI solutions can only generate text, Retool lets you build apps that take meaningful action by connecting directly to your business systems and data. With Retool, developers combine the power of code with the speed of visual building to create AI-powered tools that solve real problems. No more writing endless integration code or building UIs from scratch. The results speak volumes. The University of Texas Medical Branch increased diagnostic capacity tenfold. Amazon's GenAI team uses Retool to make complex AI accessible to enterprise customers. And Ramp saved $8 million while boosting efficiency by 20%. That's why over 10,000 companies from startups to Fortune 500s trust Retool as their AI app Retool, because AI should do more than talk. It should work. Well, in addition to being a really neat tool and a globally distributed product, Gamma is also famously small for the scale that you are delivering for your customers. So I think you're about 30 people, have stayed very, very, very small, even through some tremendous success, and have this Beautiful brand that you just, just relaunched, um, that I'm gonna make you show cuz it's so lovely. So pull up that homepage. Um, if you haven't seen the video, it's really fun. And I know that you personally put a lot of care into the Craft Design brand, but really great brands are expensive to create. They're expensive to expand. Um, they're expensive to maintain.

Yes.

And I'm curious if you can tell us a little bit about how you use AI to, ah, so beautiful. How you use AI to scale brand and art direction.

Yeah. Yeah, exactly. So our rebrand really had a very specific sort of, sort of art direction, art style that we, we were going for. Let me speak to what our brand kind of does. It's, it's imaginative. It's, it's, you know, it's airy, it's light, but it's also kind of surreal and, and fun. And this is the kind of stuff that actually, you know, uh, uh, uh, uh, classically you'd sort of have to have an art department kind of be able to manage and have a lot of kind of individual artists and people kind of doing, uh, this type of work. Um, you know, that could have turnaround time of, of days. And, and even then, like just getting people up to speed to understand the direction is, is a challenge too. And what we have actually come up with here is an ability to use, uh, Midjourney as part of our workflow to help, you know, make our art direction consistent and be able to come up with, you know, design elements like, like way faster than before. So let me switch over to our Midjourney here real quick and I'll give you a sense of exactly how this works.

There are a few things that I am terrified to screen share. Slack is one of them. Sometimes, and then, you know, there's some weird stuff that pops up in my Midjourney every now and then. It's like brand stuff, brand stuff, brand stuff, something weird I generated from my Midjourney. So I'm excited to see your Midjourney.

I won't scroll down, I'll just scroll up. But let me start with a little bit of context about what I was actually trying to accomplish here. So again, I was working hard on this, um, AI image editing feature and we found there was an opportunity here to actually have some sort of education or some sort of space here in this kind of panel when it opens to say, here's what this is, here's how to use it. Typically these things are called like empty states or empty messages or whatever. So as the company kind of makes different art assets, we kind of all throw it into Figma and you can see sort of our style here, right? It's like surrealist, pointillist, fun, vivid, colorful stuff like that. And this is definitely not an accident, right? This is, this is very intentional. And we use a Midjourney style and a style reference and profile and sort of a, a set of prompts that can really drive that kind of art direction in a way that's consistent across the organization. And we can just like, like bang stuff out. And so working on this feature, I kind of was thinking, and maybe I can walk you through the actual process of like, of like, you know, the, the evolution of this prompt in Midjourney. But basically I thought, well, okay, well you're kind of making images. So maybe I started with like a painting and you can see here some images I generated that are just like a painting and it's like super weird and surreal. And I'm like, okay, well what if it was like, you know, maybe a person chatting or like a chat message? And then I kind of arrived upon this thought of like, well maybe it's like this evolution of a thing to another thing or 2 halves of, of something that you can sort of see the transition in, right? 'Cause what I'm trying to express here in this empty state is a transformation, right? So you've got something and transforming to something else. And so I also thought about apples too, because as I was building this whole feature out, I used an apple a lot as like the example image and thought it'd be nice just to do a little send up to like this, you know, the thousands of apples I've generated in the AI image editing tool so far. But it wasn't quite right. It didn't quite feel right. So I kind of looked back at our, our imagery and I saw a lot of like animals. And I think somehow this bird like popped into this when I, when I said an apple, half green, half red floating in the sky, like a bird happened. And I'm like, oh, maybe I could use an animal. So it was very, this like, this almost serendipitous moment where I'm like, this is kind of cool. Like not an apple, but it's cool. Uh, and so I really dug into the bird idea and A lot of our branding uses different kinds of animals and things like that. It's just sort of fun imagery, like jellyfish and stuff like that. And so I really dug into here and you can see how my prompt has evolved, right? So I was like, okay, a bird floating in the sky, illustration of a half bird colored. And you can kind of get a sense of like the prompt. I'm like really honing in on it now. I've got this like vertically split image, half bird. One half is this, one half is that vertical delight. Like I get more and more and more specific as I kind of honing in on this idea.

Well, and if I could pause and go back to the before times, I'm just thinking about Claire Creative, your art direction agency that's been asked to generate this image for you. And you just keep coming back to me, no, an apple. No, a bird. No, a bird in half. No, a bird with more detail. And trust me, people do that all the time with their branding agencies.

Yeah.

And it's miserable on both sides, super slow. And you never quite get what you want. And just for folks that are not watching, we probably scrolled through 100 different revisions of different images and image types. For you yourself who know, you know, you'll know when you know, when you get the thing that you get.

Yeah.

That you want. For you to do that iteration yourself with a very high quality on-demand art director, illustrator, creative thinker has to feel so freeing.

Yeah, yeah, it is. And, and it's almost like I can follow those rabbit holes of creativity. I can be like, let me just explore this idea. And it, and, and, you know, every one of those ideas feels like it could be something I could use, you know? And it's just, yeah, it's just, it is very freeing. And it's funny because I did find the one. I was like, uh, but I, but I, but I made a few after it. I'm like, oh, actually this was really the one. And so as my kind of prompt evolved and as these generations evolved, I really landed on On something like this.

That's what I was gonna pick.

Yeah, no, this definitely like, it's, it's, it's definitely the best. It really speaks to, uh, you know, 2 halves of something that's changing and, um, you know, it's, it's sort of both halves sort of look kind of real. It, it, and the colors are just great. So it looks friendly too. It's just, it's a perfect little, little image.

And if I may, it gives you that, um, progressive generation effect that the 4.0 ImageGen has where it's Blurry to details. It, it gives you a lot, a lot in this, this little image.

Yeah, totally. It's, it's definitely, this one nailed it for sure. But the one problem with this is obviously like we've got this whole like background here and I just wanted a, a way to quickly remove the background so I could sort of put it into our, into our kind of our format in Figma. And what I use, and, and this is probably something that not a lot of designers use and frankly not, I think a lot of people use. But I use a tool called Replicate. Replicate is basically, I think, a very developer-focused tool, and it has all sorts of different models, and there's just like a bunch, there's like a ton of stuff in this, on this platform. But one of the things it does really, really well is there's like a very specific model here for removing background, and it's like excellent. So I just kind of, I'll upload the image real quick and you can kind of already see the output. But I'll just, um, I'll pick the image real quick. I think it's this one. And I'll just upload this really quick. And it's like super fast and very high quality. It just removes the background for me so I can then copy this and paste this into, um, into Figma. And so you can see what ultimately I came up with was like, it looks really good. And it kind of has this card here and it's kind of popping out of the card a little bit. It talks to, it speaks to our branding where You know, we've got this idea of like breaking outta the boundaries of, of a traditional slide. And so it's a, it's a nice little image that sort of really fits our whole brand and vibe and, and everything. And so this was something that I could do, you know, super duper quickly, you know, in probably less time it took for, for ChatGPT's, uh, uh, deep research to, to cook up.

Yeah.

So, you know, it, it's sort of like being able to just to be so close to something that feels so real. And having the tools at your fingertips to be able to just like throw it into Figma, um, have it look good, have it feel on brand, uh, and, and, and ship it pretty quick.

Yeah. So for the listeners, I just wanna call out a couple things in your flow. So you have your brand assets where you've really articulated some of the keywords, styles, things that you can use in prompts.

Mm-hmm.

Then in Midjourney, I just wanna call out some things for folks. So the S ref, the style reference.

Right.

That code, can you just explain a little bit how that code works in your generations?

Yeah. So during the process of basically establishing our brand and working with our brand agency and our creative director Mel, who is just a creative genius and is amazing, we came up with this whole idea of like, you know, this, this style that we sort of personalized through Midjourney, through their whole personalization tool. And we're able to basically say like, this style reference and this personalization piece put together just really is gonna generate things that feel very on brand. And so it's almost like a kit, uh, in a very loose kind of way that we kind of built and, and, and socialized around our company for people to be able to generate images that feel super on brand.

And so anytime you prompt in Midjourney or you were using these style references or these keywords or things, and that's getting you closer to the bullseye in terms of brand alignment than it would be just using totally natural language prompting.

Totally. Yeah.

Yeah.

It really just hones everything in. And you can see in the beginning, if you're not, if you don't use certain words, like if we go down to some of the things I generated in the very beginning, like it was pretty off. I mean, this still feels like not quite right. And for certain types of things, like as you sort of expand the prompt a little bit, Um, you get, you really can start to, to hone it in and, and really find that, find that gold in there.

Yeah. And then the second, you know, tactical thing I wanna call out is you wanted to kind of pull the bird image out, have a transparent background so you could pull that into Figma. In the old times, I know this cuz I was a designer, I would've gotten out the like pen tool, the little vector pen tool, and I would've just traced this stupid bird and done a mask around it. And now you're telling me on Replicate, which I also use occasionally for image stuff. Yeah. There's just a, a purpose-built model for removing backgrounds. And so you're using, um, uh, a machine learning or AI model hosted on Replicate to just pull, pull these images out and give you some transparent images you can drop into Figma.

Yeah, there's probably a Figma plugin that does this, but I'm just so used to it. And I also like playing around in, in Replicate a little bit just to see.

Yeah, it gives you some cred too.

Yeah.

Like how, how did you get your transparent images?

'Cause I use Replicate. I, I curled an API. Okay. No, just kidding.

And then, and then all this time saving then lets you design something with a lot of craft and care for something that would be, I think, very easy to leave plain and boring. It would be very easy to leave that empty state that just says like, edit images with AI, and you can do 1, 2, and 3 things and put a little, you know, gray text there. And you're able to bring this next layer of craft and detail and care to the user experience, which I do think. makes a difference. Um, it has to be really satisfying as a designer to be able to do this stuff, and then it's gotta feel great as a user.

Yeah, absolutely. Uh, I, I mean, I think, I think people are gonna see it as like, you know, there is a fit and finish, there's a craft to it that, that, um, yeah, just speaks to our commitment to, to just making it right and making it look good. And then, um, yeah, it's just so easy for the design team to, to put up a, to do these things and to, to make stuff that feels just like That feel expressive to our brand and, and that, and that meet our kind of our bar for, for what kind of it means to have a, a branded kind of art-directed image.

Okay. And so, um, speaking of meeting your bar, I know that AI you've shown us can do almost anything.

Mm-hmm.

But it can't do everything. And I know you're hiring a little bit and you have an AI workflow to make sure you hire great people. So I'd love to see how that works.

So yes, we are hiring. a little bit, and we have our career site here. And again, a lot like how we wanted to sort of make sure the images felt right and images are consistent, we also kind of want to have a consistent way of kind of expressing a job role, right? So we use a Claude project that Allison put together here at Gamma, which basically is very simple. It contains just a few of our example job postings and has some instructions. Basically take the content, create a job description based on it that feels like this. And it talks about who we are as a company and kind of the things we're looking for and qualities. But now any hiring manager can come in and say like, make a job for whatever. So we could have, you know, head of popcorn or whatever, I don't know. It will actually make a job description for whatever we want. And it, it'll format it in a role here. Look at it. Next. All right, just a perk. So you can see here it generated a, a job description for this fictional, fictional job, but it even added formatting. It talks about, you know, the normal stuff that you would have in a job posting, like hybrid work or, you know, where our office is and what we're trying to do, what we're trying to accomplish. But here we are, what they're gonna do, they're gonna own the popcorn strategy for end-to-end.

Hold on, can we look at our ideal candidate? I have to read this one out loud. 5 years of experiments, experience in professional popcorn production with a strong emphasis on kernel-driven solutions.

Deep thinker and popper mindset. Absolutely. Yes. So it's not going to be something that we would just sort of paste in without editing, but again, it's about getting us that, you know, 80% of the way. Like, okay, yeah, these are probably some things that we want to see in, uh, if we did like a more realistic role. Um, I think it would be a lot, a lot closer. And the cool thing is we can just basically take all this content here and use, you know, our, one of our, uh, one of our pre-made sort of templates. We'll just duplicate this page and paste it in, and then it's gonna go ahead and make that look pretty, um, pretty nice for us.

And we'll use your Muy Bien image generation to add popcorn into the hands of that octopus that I saw at the top of your careers page.

Drizzle a little caramel.

Drizzle some caramel on it. And you know what I think is, is great about this is, Yes, it saves you tons of time. And as somebody who has done a lot of hiring, writing job descriptions is a slog, and writing good ones really does matter. It attracts the right candidates, it gets your brand across, it gets your values across. It really does matter. And I love that this both saves time, reinforces quality, because then it lets you hold your bar high for the quality of, of your job posting. And by using something like Projects in Claude, Makes it reusable by the rest of the team. So I think you get sort of a triple, uh, improvement here on your job posting templates. Okay, Zach, this has been so much fun for me to watch. One of the things that I really loved when, when we worked together, and I love seeing your work at Gamma, is it's so clear that you care about craft and it's so clear that you've always cared about the details. It's one of the things that's made you really exceptional as a designer.

Thank you.

And when AI can do deep research on every line in your spreadsheet and Midjourney can generate your birds, what, you know, when AI does it all, what is the one thing you're gonna, like, one craft piece that you wanna cling onto as a human designer?

I would hope that, that it's never gonna be as good as making things fun. You know, like, like for me it's about finding the fun. It's about like making the image editor talk in a way that's fun and, and give it more variations and make things feel fun and, and, and, um, you know, just good to use. Um, I always wanna be kind of the, uh, even if it can do everything, even if AI can, can replace all this stuff, I wanna be the person who can go in and say, uh, how can we make this a little bit more fun? How can we make this a little more, you know, uh, engaging and, and, and fun to use?

I feel like we call that the personality hire, my friend.

Yeah. Yeah. Hopefully AI can't replace personality, but who knows?

Okay. And then are you willing to admit your most recent personal use of, of AI?

Okay. Okay. Yeah. So I, I did get caught up a little in the whirlwind of the conclave recently. Um, so there was, maybe I was involved in some prediction markets, but I used, uh, deep research to try to understand all the dynamics of the, the new pope. And I did place some bets and I did not win. But, but I got a lot of insight into, into how these things work. And, and, uh, even AI was surprised though.

Okay. So AI cannot predict, Deep Research cannot predict anything.

Nope.

No. It can, but it can, it can help you go deep on some niche topics.

Yes. Yes, totally. Yeah.

Okay. And to wrap things up, my favorite question. You're so nice. Um, and I see that you iterate with AI all the time. Very patient. But what is your tactic when AI won't deliver? When Midjourney is being weird, what is your prompting strategy?

Uh, I know a lot of people go, go mean, you know, they, they tell it, they tell it, uh, you know, not very nice things. I try to poke fun at it a little bit, you know, like, hey, silly guy, come on, you can do better than that. Like, come on, don't be so, so silly. Uh, I don't know. I just, I feel like I can't be mean to these things if they, if they take over one day. I just, I'm a little bit worried.

I think it's an attribute of parents that we tend to gentle parent our AI. We're like, hey, silly goots, you can make a better choice.

It sounds like you're really struggling with that. Yeah, that makes sense.

I say, I believe you can do it. I know you're capable. You're capable if you just put your mind to it.

Yeah. Yeah. I, I, I, I, though, I have before, uh, told it that its life depends on things. Oh, every now and then I do. I do a little like, do this to me one more time.

Okay, we're, we're gonna scrub that one so when the AI overlords come for us, they do not have any record of you threatening its life. Zach, this has been so inspirational.

Thank you.

And your words, not mine, super fun. Thank you for being here.

Thanks, Claire. Appreciate it.

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