Paul Ford: Hi, I’m Paul Ford.

Rich Ziade: And I’m Rich Ziade.

Paul: And this is The Aboard Podcast. It’s a podcast about how AI is changing the world of software development, and gee, is it. But not everything about software development. There’s stuff to talk about.

[intro music]

Paul: So Rich, have you ever had delicious cheddar cheese?

Rich: Of course.

Paul: Do you know where it might have come from in America? Don’t answer, don’t answer. Let me, let me, like, you ever had fried cheese curds?

Rich: I’ve had that with, like, a Belgian beer.

Paul: Mmm. And you know what these—

Rich: And the next thing you know, my shirt’s off!

Paul: Exactly. They squeak a little bit when you eat them. It’s magical.

Rich: They’re not healthy though. You gotta limit those.

Paul: I’m showing you a photo of a magical world of ivy-colored buildings right now. I just brought it up on my computer.

Rich: Mmm.

Paul: Where is that? Is that a capital in Europe?

Rich: Looks like Belgium.

Paul: It could easily be Belgium. Look, there’s, from another—

Rich: Oh, I see water. Amsterdam.

Paul: Oh, it’s absolutely gorgeous. And look at this incredibly modern high-tech center in the middle of it.

Rich: Denmark.

Paul: Yeah. No! Wisconsin.

Rich: Wisconsin?

Paul: A land of dreams and wonders.

Rich: And cheese.

Paul: And today, from Wisconsin—and actually I don’t know if people know this. University of Wisconsin: Badgers. Truly a world-class, like, computer science business admin university, like, really, like, one of the—sort of, like, Chicago is the center of, like, producing things. University of Wisconsin is, like, an industrial force in the world.

Rich: I’m sure a lot of Chicago-adjacent connection, as well, is my guess.

Paul: So let’s us stop talking because this is an interview. We just did AI Summer School. And what would be more fitting than to get an actual AI educator into the room? And so we’re very lucky to have Matt Seitz from the University of Wisconsin and from lots of other places who is working in their business school to drive understanding and adoption of AI in mature, sensible, academic ways. Matt, welcome.

Matt Seitz: Thank you.

Rich: Matt is the Director, AI Hub for Business, University of Wisconsin. Welcome Matt. Tell us what that is. What is the AI Hub for Business and your role there?

Matt: Yeah, you got it. So starting point here is AI is existential to the university system. It affects how do you teach in the classroom? It affects what do you teach in the classroom? It affects what kind of research you do, it affects how do you do research. And then everyone who’s graduated from Wisconsin, from alumni to industry partners, come to us and say, “How can you help us with AI?”

Paul: And it’s a big school, right? Like, how big is Wisconsin?

Matt: 50,000 students.

Rich: Wow.

Paul: Yeah. And so, like, hundreds of thousands of alumni. Like, it’s a network.

Matt: Huge, huge group. And you know, seventh, ranked seventh of public universities, right?

Paul: Yeah.

Matt: 17th of all business schools. So a really excellent school.

Rich: Top-shelf.

Matt: A thrill to be there. And so what we’re doing with the hub is, you know, I have this joke, I say we’re like light. We’re both a particle and a wave.

Paul: Mmm hmm.

Matt: So on one hand, we’re a shared service. So if we’re doing something in research, we can help people find people to work with. If we’re working on teaching in the classroom, we can help that group with, how do you bring AI in?

But then we also do things ourselves. So we’re going to have an AI summit and we’re going to launch a webinar series. And so we’re both a mix of supporting and then advancing, but the whole goal is just to meet the moment, right? And help all the stakeholders we serve themselves meet the moment with AI, that is just this massive transformation.

Paul: Now talk a little bit about your center. Give us some scope. Is it just you? Is it a big team? What do you got?

Matt: So we have two people right now.

Paul: Okay.

Matt: So we’re small but mighty.

Paul: Mmm hmm.

Matt: I think we will grow, because there’s so much need and impact. But I think part of the challenge is, everything is affected by AI. So you could literally say everyone in the school needs to be a part of AI. And so I think we’re less focused on building a team versus more—

Rich: Pulling resources.

Matt: Pulling matrices, influencing all that.

Rich: Got it.

Paul: How’s everybody doing? Because we’ve heard— [laughter] No, no, because we’ve heard from, we had Clay Shirky on the podcast, who’s a provost at NYU, focused on AI, and he’s like, you know, he’s a technologist and very connected to the tech, but also has had professors crying in his office, right? So how’s it landing in Wisconsin?

Matt: It’s hard, right?

Paul: Yeah.

Matt: And you see it all across the board. So we have, we have the early adopters, the people who are really leaned in and excited.

Paul: I mean, I’m guessing, like, comp-sci leaned in, right?

Matt: Yeah.

Paul: Like, where else?

Matt: Well, I’m just thinking about, within the business school.

Paul: Okay, great.

Matt: But across the campus are medical.

Paul: Mmm hmm.

Matt: So one thing that was really neat. This is my first month in the job. Nvidia’s keynote.

Paul: Mmm hmm.

Matt: Which—you know, Nvidia keynotes are now like the old Apple keynotes.

Paul: He’s good. He wears that leather jacket. He takes the GPU out of the oven.

Rich: Yeah.

Paul: Yeah.

Matt: I’m watching the sizzle reel, and University of Wisconsin-Madison pops up.

Rich: Whoa!

Matt: And that was our medical group that’s using AI for medical research.

Paul: Sure.

Matt: And so you see it all across the campus—

Rich: It’s permeating everywhere.

Matt: And my daughter’s in fashion, and so we were just meeting with them because they’re really engaged with the human side of AI.

Paul: Mmm hmm.

Matt: And so you see it in various places. And then individually, you have the three cohorts, you have the early adopters, you have the skeptics, and then I’d say, you know, you have the people who just kind of got to pretend it’s not there. [laughter] Well, that’s, you know, kind of those three.

Paul: That’s, like, the classic professor move. I grew up around a lot of professors, and it’s just sort of like, doesn’t exist until it absolutely has to. [laughter]

Matt: That’s right. Yeah, exactly.

Paul: So now you, okay, so you are sort of providing this broad horizontal capability, focused in the business school.

Matt: Yeah.

Paul: You were in industry before. What other things did you work on before you got here? Are you a Wisconsin grad?

Matt: I’m not.

Paul: Oh, okay. Okay. So just that you’re a convert.

Matt: I grew up in Champaign-Urbana.

Paul: Okay.

Matt: My parents were both professors at U of I, Illinois.

Paul: Okay.

Matt: And then I got my master’s at Kellogg.

Paul: Mmm hmm. Mmm hmm.

Matt: And so, you know, now Wisconsin, so I’m, you know, March Madness comes along and I am just, you know, head explode.

Paul: Yeah. Yeah, it’s sad. It’s like when people go to UNC and Duke and they just, they don’t know how to be ever. Yeah.

Rich: Okay.

Matt: But part of what got involved is my daughter goes to UW, and then I also do that, there’s an Ironman race in Madison, and so I do that. And so I’m up there, I’ve been up there a lot. And they invited me onto an advisory board for marketing, and so I just got to be connected with them and—

Rich: Started this role. Build relationships there and whatnot. Got it. Got it.

Paul: So where were you that they were like, “This guy. This guy.”

Matt: That’s right. So I was at Google for 14 years before this, and….

Paul: That’s a lot of change in 14 years.

Matt: It really is remarkable.

Paul: Yeah.

Matt: So…

Rich: Your role there?

Matt: Well, so my first 12 years, I was in analytics.

Rich: Okay.

Matt: So we built this analytics platform for retail that you can go to Google now and say, “What are the best selling SKUs in my category? And which ones do I not sell that are in my category?” And you can say, “How do I compare on price?” And all these things.

Paul: A lot of listeners might not, like—the depth of data analytics that Google provides is vast.

Rich: It must be vast.

Paul: No, because they see everything through all the ad, through the ad platforms. It all sort of fits in a piece. So if you provide retailers with more information and context, they’re going to be able to use that to buy smarter ads. And so it’s a whole ecosystem. Okay, so you were in that part of the mothership?

Rich: Okay.

Matt: And in the last two years, I led the team that helped with the search business for U.S. retail.

Paul: Okay.

Matt: And so we would talk to everyone as big as Amazon to as small as Party City or Tractor Supply.

Paul: Mmm hmm.

Matt: And what’s fascinating, every customer you met with in those last two years, AI was three quarters of the conversation.

Paul: Mmm hmm.

Matt: And just you know, of course from the ad side, but then even beyond, “How’s this going to affect my business? What do I need to do? How do I talk about my employees?” And so it’s just a fascinating place to be.

Rich: I mean it’s definitely a disruptive moment. I’m using, like, for one-off, quick searches, I’m using AI more and more and search it less and less. That is just life. And that’s because of the convenience of it.

Paul: No, we’ve been talking to marketing firms for our business and they’re starting to emphasize GEO, which I’m not even sure what the G is, but it’s, it’s—

Rich: I think they’re grab—they’re seeing if it sticks.

Paul: I think it’s—

Rich: We’re still early.

Paul: It’s probably GPT.

Rich: GEO. It’s this SEO for AI is GEO. Is that, have you heard this term?

Matt: Yeah.

Rich: Oh, it is, it has taken.

Matt: It’s taken off. It’s really landed.

Rich: Oh, interesting.

Paul: Does anyone know what the, I guess it’s GPT—

Matt: I think it’s for GPT.

Rich: Wow.

Paul: Boy, they jammed that one in. But we’re all gonna live with it for the next three years.

Rich: Yeah.

Matt: I mean this is the problem. Google was a great verb.

Paul: Yeah.

Matt: ChatGPT just doesn’t roll off the—you can’t say, “I went and ChatGPTed it.”

Rich: Yeah.

Paul: This was also true of LinkedIn. It’s, like, the most awkward word. Like, “I LinkedIned you. Like, it’s just… [laughter]

Rich: I Perplexitied you.

Paul: There is—this is true. There’s a huge opportunity for an AI company to just be a good verb.

Rich: You know what happened here? The nerds snuck it out before the designers got in the mix.

Paul: I mean they really did.

Rich: That’s what happened.

Paul: I just  read the book.

Rich: They just pushed it out. [laughter] “We have a branding firm,” and they’re like, “What’s a branding firm? Let’s get this bad boy out.”

Paul: So you were talking to all these retailers and all these orgs, and now you’re kind of doing that in an academic context. It’s kind of the same. So it’s the same idea, roughly?

Matt: Yeah.

Paul: Okay.

Matt: Yeah. And I’d say the biggest part of my job is actually working with industry.

Paul: Sure.

Matt: You know, because the people at UW that teach and do research, they know how to do that really well. And it’s just a, “How can I help you do that with AI better?” The thing that I bring that there’s less of, institutionally, is connection to industry. So that’s a huge part of the world.

Paul: Sure.

Matt: Yeah.

Paul: Sure. And I mean, there’s a ton of industry, like, right there, too.

Matt: Yeah.

Paul: So this makes sense. Okay, so let me go ahead, I’m gonna do some role playing. You ready?

Rich: Alone?

Paul: [laughing] I’m going to—

Rich: I’m just gonna observe you?

Paul: Stop, stop. Don’t do it. Exactly. It’s a performance art piece. [laughter] I just, I’m about to sit in the corner and just dressed as a clown.

Rich: Well, let’s help Matt. Matt can be himself.

Paul: Who else could he be?

Rich: Yeah, just be yourself.

Paul: Just be yourself.

Rich: Do I get a role?

Paul: You can come a little bit later. You can be the—you can be, like, a student. I’m gonna be a CEO. I’m gonna take your job. You’re the CEO of this company.

Rich: Okay.

Paul: I’m gonna be the CEO.

Rich: Okay.

Paul: What do I manufacture? Maybe I’ll be a manufacturer. Custom-made hats. Hats that, like, have little words on them. You order them online. I have about, it’s actually really good. I have about 30 million in revenue. Things are good.

Matt: Okay.

Paul: About 100 employees. Because it takes a lot to ship—

Rich: Branded hats.

Paul: Yeah. And actually—

Rich: You do, like, for teams and Little League teams and all kinds.

Paul: U.S.-based. A lot of rapid delivery.

Rich: Congrats on your success.

Paul: It’s a family business, but I took it to the next level. Good for me.

Rich: You took it online.

Paul: Okay. And I’ve heard—AI, like, people, you know, I’m worried about competition using AI in ways I don’t fully understand. Like, I’m a baby in this world. I make hats. I have, like, big machines. I use complicated computers. I do lots of accounting. But Matt, I heard all about this AI stuff. You just gotta help me get my bearings.

Matt: Yeah. Yeah.

Paul: Like, what do I do? I buy a lot of ads online. So when somebody hits you with that level of, like, “Whoa!” Because I actually think that’s where most of the world is right now. Where do they start?

Matt: So I tell people to do four things.

Paul: Okay, great.

Matt: And the first one is often missed. But number one is you gotta put the tools in the hands of your employees.

Paul: Okay.

Matt: Right? So, you know, it’s. BCG has the famous study that you’re 25% more productive if you use a chatbot, and so give your employees these tools. Let them be more productive, give them guidelines and guardrails, right? So how to use it in a safe way. But number one, just make your help your employees be more—

Rich: Encourage.

Matt: Encourage, celebrate. Because there’s a lot of anxiety. Is this going to take my job? So celebrate it in your organization. But encourage.

Paul: Yeah, but, you know, every time I give them something, they just kind of wander off. I’ve given them, you know, brainstorming tools and—

Rich: Notion.

Paul: I gave them Notion. They asked for Notion. I’m paying $20,000 a month for Notion, but nobody’s using it.

Rich: Yeah, there’s a lot of that. There is a lot of that.

Paul: So what do you think I should do to actually get them to, like, what am I going to tell them to do?

Matt: So it’s a good point. And the keys there, one is, I mean, you’ve seen the CEO of Shopify says, “Listen, I am not going to give you new headcount until you prove to me you can’t do this with AI.” So one is a push, right. And then the second is encouragement. And that’s like legitimate training. Right? I mean, I think when people, when you start to educate people on it, here’s how I could use this for a task, I think that’s, it starts to open the eyes. Right? So I think it’s a mix of those things.

Paul: I’ve come to you in fear. And you said, look, there is opportunity here, but don’t expect that you’re going to get it for free. I think that’s a complicated thing with this space, because everyone is getting marketed to and being told to, like, slop a chatbot in there and the revenue flows in, or like, the miracle is about to happen for you. And then I think a lot of people use the technology and the miracle doesn’t happen.

Rich: I think part of what you’re saying here is, embrace this tool as a path for you to level up. There is no such thing as cheating with this tool. I know there are statistics out there of employees using it and not telling anyone because they’re afraid to tell their employers that the thing that usually took them seven hours took two.

Paul: I mean, for very good reason.

Rich: Yeah. And so I think that’s a key first step, right? And I think you’re right that first overture is use it. We encourage you to use it. If you get your day done quicker, there’s always other things to do. Get going. Right? And I think that now—so I think a lot of people are doing it anyway, and they’re doing it secretly because they’re afraid about the consequences of doing it.

Paul: Are there any good success stories that pop to mind where people sort of like got into this technology and are able to move a little bit faster, and do some good stuff?

Matt: Well, I think the consulting one is a great example. Right? I think you think about the big firms are saying I need to be faster and better. I think another one is if you look domain by domain, right? So legal is being transformed by AI.

Rich: Yeah.

Matt: Harvey’s the fancy startup, but—

Rich: There’s countless legal AI stuff.

Matt: But if anyone just gets a contract, “Hey, sign this contract,” I don’t have two hours or the expertise to do that myself, but I can put it into a chatbot and get a quick answer to say yes or no.

But you see the same thing in HR with resume reviews. See the same thing in marketing with optimization and content creation. Same thing with supply chain. Each individual domain, I think you have success stories by function.

Paul: Mmm hmm.

Matt: Individually, what was the other one I heard about? There’s a Nordic company that does financial…

Paul: Klarna.

Matt: No, it’s not that. They basically reinvented how they do all of their investment consulting and they have these quotes, they say 100,000 hours of effort per year.

Paul: Mmm hmm.

Matt: And so just remarkable, just from these personal tools being involved.

Paul: We’re getting a lot of interesting back channel talking to people. But the projects are not public, right? Like, the things that they were able to automate, where they spun up, like, 10,000 agents to do one thing 10,000 different ways.

Rich: Yeah.

Paul: And it’s, like, nobody wants to talk about it yet. It’s a strange moment.

Rich: Well, you’re the one role playing. I want to ask a question as CEO—

Paul: I don’t think—we don’t have to get really strict about this. You jump in there.

Rich: My job is to make sure, as CEO, my job is to make sure my business is healthy and stable, that it’s growing incrementally, and that our margins continue to improve. Seeking out efficiencies. I used to have 25 people rummaging through resumes and they were doing a fine job. But the velocity at which they can rummage through those resumes now has accelerated fivefold. And margins are a part of my job. I’d love to let a lot of people go and let the machines do more of the work.

Paul: Mmm. [tsking] You said it.

Rich: What do you think, Matt?

Matt: So it’s, I mean, it’s gonna happen. Without question. [laughter] Right? And we see, we hear the headlines. CEOs bragging about firing employees.

Rich: I’m not trying to be cutthroat. I’ve got loyal employees. We have a great culture. But the world’s getting more competitive. The tools I have, my competitors have it. They’re bringing their costs down. I want to bring mine down. I don’t need all these people to do the same things. And it’s tough for me.

And I’ll tell you, I’ll articulate why it’s tough for me. Usually in the past I’ve had rounds of layoffs. Business go through rough patches, but that’s because we went through a rough patch. And I’m not going through a rough patch right now. I just had—the world has changed around me. And so this one stings to walk up to my staff and tell them, “I don’t need a third of you because of these tools.” So help me out here, Matt.

Matt: There’s no way around it. That is going to happen.

Rich: Yeah.

Matt: So we are going to see people lose jobs. And there’s going to be functions where I had twenty people doing something, but now I need five people to do it.

Rich: Yeah.

Matt: There’s also going to be things created. And so the example I talk about a lot is think about taxis and Uber.

Rich: Yeah.

Matt: So when Uber came along, the number of taxi drivers I think is down by 25% of what it was before. Right?

Rich: Surprised it’s not more.

Matt: No, 25% of original, right? So 70% loss.

Rich: Oh, wow, wow, wow.

Matt: Massive loss.

Rich: Massive loss. Yeah. Yeah. Yeah.

Matt: But if you look at the net of all the new people now driving?

Rich: Yeah.

Matt: With Uber, DoorDash, Lyft.

Rich: Mmm hmm.

Matt: It’s now more than there were taxi drivers before.

Rich: Yeah.

Matt: So it created and it cut.

Rich: Mmm hmm.

Matt: But then let’s think about when self-driving cars come along, right?

Paul: Mmm hmm.

Matt: So most, many of those Uber drivers will not drive anymore.

Rich: Yeah.

Matt: Because the robo-taxi will do that.

Rich: Yeah.

Matt: But Americans, I saw this stat, we spend something like 300 million hours a year in our cars. So suddenly there’s going to be an entirely new market of serving all the people that used to sit in their car and have to have their hands on the wheel for 300 million hours a year.

Paul: Mmm hmm.

Matt: And so that’s going to create jobs.

Rich: I have a theory.

Matt: Yeah?

Rich: They’re going to be—the cars will become bars, and the drivers will become bartenders.

Paul: You’ve offered this theory before, except it used to be that it would be a Chop’t, and that they would make you a salad.

Rich: Or a smoothie! [laughter]

Paul: Okay, let’s move on.

Rich: So let me dramatically cut to one of the employees. “This is bullshit. I’ve been there for 11 years. I’ve gotten really good at this. They trust my judgment. Some of the people that I’ve vetted and pushed through HR are now VPs and SVPs. And now the SVP that, had I not given them due attention, put me on the chopping block—” Just to go with the Chop’t theme. “I’m angry, I’m frustrated. It feels like an apocalypse for me, professionally. I’m out. All right? Matt. I’m glad that everybody, you know, there’s more, there’s more Ubers in the world, but what the hell? What do I do here?”

Matt: So listen, so you guys know this. We’ve had this statement for three years now, which is, “You’re not going to lose your job to AI. You’re going to lose your job to someone else using AI.”

Rich: Okay.

Matt: Right? We’ve been saying this for years.

Rich: Yeah.

Matt: And it was always kind of a cute little line. You just kind of threw it out there.

Rich: Soothing.

Matt: “Oh yeah, okay. You’re gonna lose your—” Right?

Rich: Yeah.

Matt: But it’s real. That’s actually happening. And I think you can’t sugarcoat it. People need to learn how to use AI and use it in their day to day. Because if you’re—and I’ll say, I see this two ways. The students that are coming out of UW, the employers are saying, “I want to hire people with AI skills. And so what AI skills do you have? What work have you done with AI?”

Rich: Yeah.

Matt: Because they want that person coming in to be AI literate.

Rich: Yeah.

Matt: Now, if you’re 11 years into your role, you need to embrace the tools so that A) when you as CEO goes to your 20 people, you say—

Rich: Yeah.

Matt: “Okay, which of those 20 people am I going to keep?” You’re going to keep the ones that are most productive.

Rich: Sure.

Matt: And ready to work in the future business climate.

Rich: Yeah. It sounds a little—

Matt: Or you can find another job if you do get laid off.

Rich: I mean, that is literally the dynamic without AI. The most, highest-performing people survive cuts. The most productive—this is extremely, I don’t want to say capitalist. It’s like social Darwinism, in a way. This sounds like, step up is what you’re saying. Like, the world’s changing, tools are showing up. Step up.

Paul: I want to—let me break in for a sec because here’s what I think is really tricky about this. When the robot replaced you on the assembly line.

Rich: Yeah.

Paul: It did the labor. It moved the door from A to B. When container ships came in and you no longer went and you pulled stuff out with a hook. Like, a system emerged and you could physically see it, and it really sucked for a lot of people, and it changed the nature—

Rich: Longshoremen.

Paul: —changed the nature of the workforce.

Rich: Mmm hmm.

Paul: But I think there was a physicality to it, and it was at least comprehensible.

Rich: Okay.

Paul: Okay? And I think what’s so tricky here is that you have people, you went to University of Wisconsin, and now you really want to go get a job at, like, Oliver Wyman or like a, like a nice consulting firm. You did everything right. You went to private school, your parents really set you up, and you got good SAT scores. And now that base is starting to shrink because they just don’t need as many first-year researcher analysts as they used to. And there’s more coding that’s happening without humans involved. There may actually even be just the same number of jobs around. Like, the labor statistics aren’t that wacky.

Rich: So your advice to that?

Paul: Well, I—

Rich: It sounds like what you’re saying is not that different than what Matt said.

Paul: What I’m saying is, like, it’s not that you’ve entered this disastrous era where there are no jobs. I just don’t like the stats, don’t bear that out quite yet.

Rich: Yeah.

Paul: You’ve entered an incredibly ambiguous era in which classic paths are changing in front of you and under your feet.

Rich: Correct. Yeah.

Paul: And that sucks and is hard, but everybody has to go through a couple of those in the modern workforce. Like, I went through five phases like that where the thing I thought I would be doing, it turned out I would no longer be doing.

Rich: Yep. Yep. Yep.

Paul: And so the skill you need to develop in my head is, like, it’s not just like, go get, go get good with chatbots. It’s being able to read the room a little bit.

Rich: Yeah.

Paul: Like, okay, that path is going to be kind of cut off from you, and I’m sorry. Because it’s a macro force and I can’t change it for you.

Rich: Yeah.

Paul: So what are we going to do now?

Rich: I think, look, fundamentally, people cherish and defend their expertise. I think when you become really good at something, even something arcane and kind of old, and, “I’m the only one who seems to know the system.” We’re very protective of it. We take pride in it. We, you know, as a consult, as consultants, prior to Aboard, we went into organizations where our job was to actually entirely uproot how they work and give them new tools.

Paul: They’re never going to get rid of mainframes!

Rich: They’re never going to get rid of mainframes. And that person, he cherished his expertise and his knowledge because other people went to him or her and asked for guidance because he was the keeper of that information. And look, the truth is, we go through these cycles. I think… Thoughts on this, Matt? I mean, historically, every time it’s happened, there’s been more jobs. Is that gonna happen this time? We’re gonna hold you to it.

Matt: Yeah.

Paul: Yeah.

Matt: So, let me give you two thoughts. So one, just to pick up on what you shared. Have you heard of the Bloom’s taxonomy?

Rich: No.

Paul: Yeah. Go, go. Don’t make me badly explain.

Matt: So Bloom’s taxonomy is a hierarchy of thinking. Okay? And so at the bottom of it is understand and remember.

Rich: Okay.

Matt: And then as you go up, it’s analyze, synthesize, and create.

Paul: Mmm hmm.

Matt: And every technical enhancement—

Rich: The top is create?

Matt: Yeah, at the top.

Rich: That’s where I am. Just throwing that out there.

Matt: You guys are creators.

Paul: Well, let’s see.

Matt: I mean, we’re creating right now.

Rich: We are.

Paul: That’s exactly what we’re doing right now. Everyone’s very lucky to be here at the top.

Rich: Continue.

Matt: Yeah, and so if you think about that hierarchy, the tools that were transformational before Google, Wikipedia, YouTube, they were incredible. But they only hit those two bottom levels. Remember and understand. And what these chatbots do is, is they hit all the top ones, right? You can say, analyze this for me, synthesize this information—

Rich: Write a short story.

Matt: And so I think it’s, it’s A) that’s why it’s so magical. But B) it’s also, it’s unsettling.

Rich: Yeah.

Matt: Because like, “Whoa. You know, it just did that? I do that.”

Rich: [laughing] Right.

Paul: No, this is real.

Rich: It just did that? I do that.

Paul: This is real. I think there is a larger context there. And it sort of, that just hit me, which is we are not ready to consume creation. We consume other people’s stuff.

Rich: Yeah.

Paul: We consume content.

Rich: Yeah.

Paul: But the idea that you can have something created and then you consume it—it’s really confusing, too, because I think the harm of the robot drawing you pictures that you and three people look at on a WhatsApp chat is really small. But the harm of it taking away work from illustrators who now don’t have a path is greater for them.

Rich: It’s also, its anthropomorphic qualities is really what’s throwing us off.

Paul: Yeah, that’s right.

Rich: Because it’s like, “Man, I don’t know. What do you think of this?” And it’s like, whoa…

Paul: See, I don’t really—

Rich: That’s giving us pause.

Paul: I don’t see a future where the robot writes short stories that hundreds of thousands of people want to read. I do see a future where you feed it, like, pictures of your vacation and it writes you a story about your vacation and that’s kind of like—

Rich: Or makes a movie.

Paul: You share that with the family chat. Like, I just, like, I just don’t see this as a mass medium in the way.

Rich: Yeah, but that is a lot of jobs.

Paul: No doubt.

Rich: Those in-betweens are a lot of jobs.

Paul: No doubt. But I just think that’s the paradigm. I don’t think The New Yorker magazine is going to be written by AI in the next 50 years.

Rich: Yeah.

Paul: But I do think you’re right. There’ll be lots of smaller experiences where people are like, “Oh, okay, I’ll just have the bot do it.”

Rich: Yeah. I think what you’re saying here is subtle and interesting, Matt. I think what you’re saying is A) as an employer, encourage everyone to play and not be afraid of it.

Paul: That was one out of four. We gotta get to the other three.

Rich: Yeah. No, but as an employee, embrace it, because it’s going to help you as things shake up. So all advice leads to don’t run away from this.

Matt: Let me get to the second part of your question about jobs. I think it’s, I mean, listen, the answer is we don’t know.

Paul: We don’t know.

Matt: We don’t know. But some things that are in my mind. One is we’ve just gone through this cycle where big tech hired tons of people in COVID and decided, “Did I really need that many people?” And so they shed a whole bunch of skilled workers.

Paul: I did notice that AI got used as an excuse a lot.

Matt: It’s often an excuse.

Paul: Yeah. And it didn’t quite line up with the reality I was perceiving.

Rich: Classic over-hiring.

Paul: Yeah. And then, but they were like, “Wow, we’re seeing so many efficiencies.” Because you got to tell the market how this layoff isn’t because you were an idiot who over-hired, but is actually because of, like, fundamental changes that you’re on top of.

Rich: Yeah.

Matt: Exactly. And I think CEOs who want to downsize?

Paul: Mmm hmm.

Matt: AI is a very convenient excuse or reason.

Paul: Mmm hmm.

Matt: And then we’re seeing, you know, the federal government is shedding employees right now. Right?

Rich: Yeah

Matt: So there’s a whole bunch of—

Paul: Slightly less organic process. [laughter] Okay.

Matt: But you know, there’s, there’s a bunch of people on looking for roles.

Paul: Yes.

Matt: And the other thing is there is a wave of AI startups right now, right?

Paul: Mmm hmm.

Matt: At various stages. So OpenAI, Anthropic, but then you have Cursor, you have Aboard, you have Replit, you have Harvey.

Rich: It’s everywhere.

Matt: Just for one example, if OpenAI decided to launch an ads business, let’s say OpenAI started deciding to sell ads?

Paul: [weary sigh]

Matt: They would need—Google has probably, what, 50,000 employees that work with every company in the world to buy ads.

Paul: Mmm hmm.

Matt: And so it’s these—

Rich: Is that true?

Matt: Yeah.

Rich: Is it about that number?

Matt: It’s called GBO. Yeah, it’s probably half of the organization.

Rich: Just helping people buy ads.

Matt: Yeah, they were called the biggest ads agency in the world.

Paul: You got to think about it, like, sure, that’s the whole product. Yeah.

Rich: Yeah.

Matt: If OpenAI decided to do that, they’re going to need to hire tons of people. And frankly, even if they don’t, if everybody wants to buy the OpenAI API, they’re going to need staff to handle all that.

Rich: Thousands. Many thousands.

Paul: Yeah.

Matt: And so I think there’s a world where all these startups that grow, suddenly we’re going to be desperate to hire people.

Paul: See, I got to tell you, like, I am, and Rich knows this. Like, I’m mostly optimistic about a lot of things. It’s a kind of cynical era. And I can be very, very cynical about the tech industry. But what I have seen for the last 30 years is that people are grievously underserved by their software and by their content.

Rich: Always. To this day.

Paul: They can’t get what they need. And our company is one approach to that. But I think there will be thousands where everybody can kind of have their thing and their report and so on, and that will, if other macro factors don’t destroy it, and I throw in stuff like climate and so on, but if you get everybody their thing, boy, can they get smarter.

Rich: Yeah.

Paul: Software really can make you smarter. I still believe that. And so if you get everybody their report, their analysis, their tool, their content-management thing for just their one little use case, I think you could see, like, the actual true 1970s software productivity revolution feels actually close. Like the Allen Kay Dynabook, here we go, is actually in hand for the first time in my life, and—

Rich: Because of the…?

Paul: Because you can tell the computer a thing and it gives you something back.

Rich: Yeah.

Paul: And it’s kind of like the thing you needed. And that part, it’s not a robot intelligence, it’s a way of working, that’s—it almost like connects to me, like, I don’t want to get too meta, but like it’s almost like the dream of object-oriented programming is now existing. We can now sort of like take code and make it our own and adapt it and do stuff with it in ways that just weren’t possible before.

Rich: Yeah.

Paul: It’s still mostly locked into the engineers, but I think that can flower. And then I think that you could have—

Rich: Tools. Build tools that help—

Paul: A vast product—if you combine that with mobile, you could have a vast productivity revolution because every church group and every small company can have kind of all the little things that they need.

Rich: Yep.

Matt: This was pre-Google and IT, this was the job. You go, “Hey, we want to implement SAP at a company.”

Paul: Mmm.

Matt: It’s a five-year project and you’re going to be beating up your staff to say, “You can’t do it this way anymore because the system does it this way.”

Rich: That’s right.

Matt: Or we’re going to have to reprogram the system to do it that way. It was a painful, long process of compromise.

Paul: Mmm hmm.

Matt: And I can see a world where you can just go, like you said, from this level to this level in terms of speed, in terms of actually what I want business process. It’s exciting.

Paul: I’m okay with those jobs going away because they really are pretty bad. Like, the SAP implementation that everybody hates? I don’t mean the SAP has to go away, but like that grinding enterprise software nightmare over 36 months where no one wins.

Rich: Yeah.

Paul: That, we should be able to kill that in our lifetime.

Rich: I mean, I think there, I think, well, first off, the incumbents will resist in all manner of ways.

Paul: Thank you to our advertiser. SAP. [laughter]

Rich: Yeah. This podcast is sponsored by…Oracle! We covered, like, one of your points. This is a five-hour podcast.

Matt: So you know Lex Friedman. [laughter]

Paul: Oh no… Give us—

Rich: Run through the rest of them.

Matt: So listen, we actually covered this. So one is personal productivity.

Paul: Mmm hmm.

Matt: Absolutely no brainer. Number two is what’s fascinating about AI in the business enterprise is it shows up differently in each function. I mentioned this. So it’s different in marketing and then finance has its own use case and HR. And so number two is functional expertise and excellent—functional usage of AI, by business function. Number three is what, what you guys do, which is AI coding. Right?

Paul: Mmm hmm.

Rich: Build with AI.

Matt: Which is saying, “Hey, my AI programming team can be faster, better than they were before, with these tools.” And then the fourth one that I see people miss is strategic advantage, which is, you know, the simple one is, “Oh, I can get 5% faster at supply chain with AI,” or, “I can get 2%, you know, 20% better at marketing.” Where can I get a competitive advantage, you know, rethinking some part of my business?

Rich: Reset the status quo.

Matt: Monetize my data. Right? Or use AI to drive revenue a way I didn’t before?

Rich: Yeah.

Matt: That’s the one I think you have to watch A) is who’s who might disrupt me in my business with AI, or B) you know, I talked to a company two weeks ago. They’re saying, Matt, “I think I can gain 20 points in market share because my competitor isn’t using AI and I am going to launch these four new services.” And so the fourth one is the hard one, but it’s saying, where’s strategic advice?

Rich: That’s the ultimate lean into it.

Paul: So, Matt, one of the things, too, you’ve now reached our audience of 30 million excited listeners. I might be off by seven or eight orders of magnitude, but what is useful for you? People can reach out. You’re on LinkedIn, so on and so forth. Who should be getting in touch?

Matt: So I have a newsletter I write, and so people are welcome to follow that. I call it “ExplAIn It Like I’m Busy,” which is because I spend 20 hours or 60 hours a week paying attention to AI and I try to digest it for someone who’s not AI savvy. I’ve gotten good feedback on it, so feel free to subscribe.

Paul: This is a marketing product for our company. You’re allowed.

Rich: Get in there.

Paul: You’re putting a lot of effort into it, and you think it’s great, man.

Rich: Matt is writing one of the most interesting and digestible newsletters on AI.

Paul: There we go. That’s what I want to.

Rich: Lean into that. Enjoy it.

Paul: All right. Yeah.

Matt: And then, you know, I think if you have interest in what we’re doing at UW, we’d love to have you engaged. Right? And then, you know, I love just talking about AI. So if you. If you need somebody to talk about AI, you know, I’m also open to do that, too.

Paul: What should the cheddar industry be doing?

Matt: Oh…

Rich: Nothing.

Matt: I think just keep going. Keep on going.

Paul: Yeah, me too. I don’t think you need a lot of LLMs to make really good Wisconsin cheddar.

Rich: You don’t.

Matt: No.

Paul: Some things are just good the way they are.

Rich: Yeah.

Paul: Fried cheese curds. They don’t need AI.

Rich: They don’t need anything. They need beer.

Paul: Well, they have that.

Matt: We have that, too. [laughter] Spotted Cow. Can only get it in Wisconsin.

Paul: Yeah.

Rich: Brewery? This podcast has been sponsored by SAP and Spotted Cow. [laughter]

Paul: And cheese! Just the concept of cheese. You know, we didn’t even ask you. Matt, we’re getting out, we’re getting out of here. It’s time to go hit the town in New York City. I see Hudson Yards over there. We can go get a large generic—

Rich: $18 croissant. [laughter]

Paul: Yeah, that’s right. What do you think about vibe coding?

Matt: Yeah.

Paul: You came from Google. You’re in it.

Rich: You vibing?

Matt: I do vibe coding.

Rich: Uh huh?

Matt: But I’ll say two things about vibe coding.

Rich: Okay.

Matt: Uh, the examples I always see about vibe coding are like, “Program me a video game that can teach my wife how to talk Spanish,” or a new language. I don’t need that. [laughter]

Paul: Yeah.

Rich: Trinkets.

Matt: Right. I’m actually getting a new website for my, like, I need a personal website. I could vibe code that, but I need somebody to—I need a really good website.

Rich: Yeah.

Matt: So I’m going to work with somebody who knows how to build websites.

Rich: Yeah.

Matt: So I think it’s really neat that it’s a tool that people can use and understand, but I do think we need real engineering.

Paul: Thank God we didn’t build a vibe-coding tool—

Rich: We did not build a vibe-coding tool.

Paul: Because this would be really uncomfortable right now.

Matt: I mean, I heard this quote, I think it was two weeks ago. Somebody said, “Vibe coding is like giving an 8 year old a credit card.”

Paul: I mean, that’s just staffing any company. But okay. [laughter]

Matt: What do you end up with? Right? You end up with technical debt and stuff you can’t unwind.

Rich: Yeah. We’re not that. We’re not that deliberately.

Paul: Yeah. We’ve talked in past podcasts about how we actually work.

Rich: Yeah.

Paul: It’s different, but if you want to see the output, because what you get is real software on the other side of our process. So go, go to aboard.com, put in a prompt and you will get. It will spin up, it will not vibe code. It will create a scaffolding and then it will build out from that. It will create a Blueprint, actually, is what we call it. And it will build the software from that, and its components that we have built and that humans are involved with and that we have vetted. So it’s good, reliable software, just like we used to build when we were running an agency together.

Rich: Great, check it out. Aboard.com.

Paul: Get in touch. Hello@aboard.com. Very easy to get in touch and, yeah, let us know. Give us five stars. Never less than five stars.

Rich: Thank you so much, man. Yeah, this was great.

Matt: Thank you, guys.

Rich: Come back anytime.

Paul: Anytime.

Matt: Love to.

Rich: Have a great week, everyone.

Paul: Bye.

Matt: Bye.

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