Paul: Hi, I’m Paul Ford.

Rich: And I’m Rich Ziade.

Paul: And this is Reqless, the podcast about how AI is changing software.

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Rich: Paul.

Paul: Richard.

Rich: It’s not just about changing software. It’s changing careers. It’s changing economies. There’s all kinds of changes happening. This stuff is—I like, I’m trying to think about the biggest metaphor I can think of, and I keep saying meteor strike, but that’s not good because that killed everything, and then we waited another 5 million years until we showed back up. So maybe it’s not that.

Paul: It was good for mammals, bad for cold-blooded reptiles.

Rich: Right. But they still came back. They’re just, like, little lizards now.

Paul: Yeah.

Rich: Yeah.

Paul: Yeah.

Rich: You know what everybody tries to do? Everybody, when they see stuff that’s, like, this nutty, which, we’re lousy at predicting what tech is gonna do for us. We thought it was gonna make us share casseroles, and then it ended up with, like, badly conceived revolutions that didn’t go to the good place. [laughing] We’re really bad with predicting how to best position ourselves for the next technological wave.

Paul: I have a lot of thoughts about this. Let’s talk about predictions today. So first of all, I wrote in WIRED years ago, for my column, I found a book from the seventies. It was a list of predictions, and they’d gone out to thinkers and professional predictors.

Rich: Fun.

Paul: So I read the book and I wrote about sort of what had changed and what was wild, there are a few patterns that emerged. One was people really, really have trouble seeing beyond the current moment. They extrapolate. And I’ll give you an example. It’s like, birth control was a big issue. Overpopulation.

Rich: What year are we at this point?

Paul: It’s like, you know, think like ’74.

Rich: Okay.

Paul: You know, the environment is just becoming a subject at a kind of—

Rich: Yeah.

Paul: At a national level as opposed to, like, a hippie level. You can see how trapped people are and how much they assume that there will be an infinite trajectory along current lines. They assume that the space age is upon us and we will soon be on the moon.

Rich: Yeah. Yeah.

Paul: Because, five, six years before, you’d landed a guy on the moon. So obviously you’re not just going to do that once or twice.

Rich: Right, right. Yeah.

Paul: So you’re going to keep going. Let’s get to Mars, et cetera, et cetera.

Rich: Yeah.

Paul: Computers are in there, but they’re just kind of, like, every now and then somebody would get it.

Rich: Mostly wrong?

Paul: One novelist predicted, like, I don’t know what it’ll be, but there’ll be some kind of computer money—and it really sounded like bitcoin, I remember that. But in general, the mistakes are accidental.

Rich: Mmm.

Paul: The only thing you can bet on, and this will sound very reductive, the only—technology, you cannot predict it. You can bet on human nature. Human beings, I’m going to tell you, want to fast forward 10, 20 years, human beings will want to own media devices, eat a lot of food, have sex with other human beings. [laughter] They like clothes. Like, right?

Rich: Yeah.

Paul: We’re on year, like 50,000 of clothing now. [laughter] Okay, so, like, that’s gonna, that’s gonna keep going.

Rich: Yeah, yeah.

Paul: That’s, but the, so the basics, and I’m gonna, you know, I’ll call a negative one, which is like, we’re gonna have wars. We’re gonna have a war. Everyone’s like, no, no, everybody’s connected to the internet. Remember that? In the nineties, we’re gonna get everybody connected.

Rich: Global community.

Paul: No more wars. There’s, like, seven wars in the last hour.

Rich: There’s, like, extra wars.

Paul: We have a lot of wars.

Rich: Yeah.

Paul: And it sucks, right? So I think, like, the utopian fantasy, a radical disruption in human history does not occur.

Rich: Okay. With all that, that doesn’t help me here. Like, AI just landed. I’m gonna use the word “skimmed” the earth. The meteor skimmed the earth.

Paul: I think it does help, frankly. I wrote about this a little bit in the newsletter, which—

Rich: No, but I’m gonna play a role here for a second.

Paul: Okay. I love role play.

Rich: I’ve had the same job for ten years—

Paul: Yelling at me.

Rich: Steady as she goes. [laughing]

Paul: Yelling—okay.

Rich: And now this new thing showed up, and I want to be best positioned for it. Should I go get certification?

Paul: We talked about this. I think right now you just get in there and—

Rich: Play.

Paul: —whatever skills you have, you see what—you see what you see if you can teach it to do your job.

Rich: Okay.

Paul: Okay? So I can teach the new version of ChapGPT to create a rough outline—I’m not a bad software architect. Like, you know, meaning, like, you can define a platform and define the data structures and sort of what the components are. I would say it’s not as good as I am. It’s much faster.

Rich: It’ll give it a go.

Paul: So I do like, you can say to it something like, I want to write this kind of application. It’s going to be in C++. It should work on multiple platforms. List the open-source libraries you’d use and how you would build it.

Rich: Mmm hmm.

Paul: And it’s like, I don’t mind skipping that thinking because it’s table stakes kind of thinking.

Rich: Yeah. Sometimes the hardest thing is the outline.

Paul: That’s just—the page is no longer—

Rich: It’s, like, the bones of what you need to get done anyway.

Paul: I gotta tell you, I’ve been testing it for this, like, can I get it to do software architecture? I don’t know if it’s really going to save me time, but it will save me procrastination.

Rich: You could fix it.

Paul: I can fix it.

Rich: It’s much easier to fix a thing than to start stare at a blank page. Boy, it’s easier.

Paul: I’m going to make an extremely positive argument for that aspect. I have a theory of talent. Okay? People think talent’s really positive, but you ever actually spent time with really talented people?

Rich: Yeah.

Paul: How would you define them?

Rich: Insecure.

Paul: Anxious. Because they perceive how a thing should be, but then the one in front of them isn’t like it, and they freak out.

Rich: I have a wife.

Paul: Good. That’s, first of all, that’s amazing.

Rich: Yeah. That’s an achievement.

Paul: Good job.

Rich: Speaking to talent.

Paul: Yeah.

Rich: Who is in the food and beverage industry, in the restaurant industry.

Paul: Yes. [laughing] You made it sound like, it’s like, beer depot.

Rich: She is, I think, by any measure, doing extremely well.

Paul: She opened a restaurant and it is a hit.

Rich: It’s a hit. And she sees nothing but failure every day. She just can’t see—she can’t be—

Paul: Gee, I can’t imagine how you two got together.

Rich: [laughing] But you know what? It makes her press and thrive and continue to pursue, because talented people are always trying to sort of convince reality to line up with what they see as exactly what it should be. Right?

Paul: So there’s two aspects of talented people. One is they’re incredibly annoyed by, when the form isn’t quite lining up. And the second is it can often be really hard to get them started.

Rich: Yeah. Oh, that’s real.

Paul: Because it’s just, they know—

Rich: They procrastinate.

Paul: They know it’s only pain on the other side.

Rich: Yes.

Paul: Okay. So they don’t, they don’t want to do it because it’s gonna suck.

Rich: It’s hard. I’ve been there. I mean, not, not that I’m talented, I’ll let others decide that. But I have been there. I’ve been there avoiding the thing I have to go do.

Paul: Of course—

Rich: I know it’s gonna be ugly.

Paul: You stay home on keynote days, right, when you need to, like, get—

Rich: Yeah. It’s true.

Paul: Because it’s, if you lock yourself in the box and know you have to do it.

Rich: No escape.

Paul: Yeah.

Rich: Yeah.

Paul: So what I’m, what I’m getting to here is that I actually think there is a very, very positive case to be made for AI as a talent inducer, in that if you have a thing that you’re good at and it does it badly, you are motivated to do it right.

Rich: It’s almost kind of ignites the forward motion.

Paul: Yeah.

Rich: It sort of kicks things off.

Paul: I don’t argue that human beings want to see sloppy AI generated images of elves. I just don’t think we have that appetite at the degree that the technology justifies. I do think that if—

Rich: I always view that stuff as demo.

Paul: Yeah. If you’re an artist and you want it to draw you some pictures, it’s going to piss you off, and then you’re going to go, I can do better. That’s where I want us to be as a species.

Rich: Right.

Paul: So anyway, I don’t know if that’s where, so I took us on a tour of talent.

Rich: Okay.

Paul: But I think, so the talent is one force in the world. I think the other one, and this goes back to what I just wrote in our newsletter and so on. When you’re making predictions, one prediction is incredibly insufficient. You should kind of have a bell curve of predictions.

Rich: Mmm.

Paul: It’s literally what the science—

Rich: Portfolio.

Paul: Yeah, it’s what the science of probability is. Right?

Rich: Okay.

Paul: Like, let’s sort of figure out sort of what are the ends of this spectrum. So I think that one side of AI, and let’s just focus on engineering now, not art, not anything else.

Rich: Okay, okay.

Paul: But it writes code. It does software architecture. There’s one side where it’s just pure hot air and it doesn’t really matter and maybe people play with it for a little while, but it just like the balloon pops.

Rich: A toy. Yeah.

Paul: Then you go up one level and it’s useful, but it’s a feature in your development environment because you use it, you know, once a week, you really write that code, but it actually turns out the velocity doesn’t matter as much—

Rich: A tool that enhances one aspect of your work.

Paul: I’m going to skip the middle and go to the other side.

Rich: All right.

Paul: The other side is, boy, it’s really powerful. I am a ten-time better programmer. Then I think the final version is. We didn’t hire a team, we hired AI. We didn’t even bother with people. We describe the tool we want.

Rich: Yeah.

Paul: We describe it, it builds it, and it works just about as well. And we shipped it to the app store and everyone’s using it internally and we saved millions of dollars.

Rich: Yeah.

Paul: Okay. So I think all of these things are possible. The ones on the right feel a little more likely because there’s obviously something here because it writes code, which it didn’t do before.

Rich: Yeah.

Paul: But I think the one on the far right is the one they keep selling you. They’re like, “Oh, here we go.” VCs love the far right, because that’s where their hockey stick comes in.

Rich: Not only do they love the far right, they sort of, this thing, it just landed.

Paul: Yeah.

Rich: It just landed. And the VC’s like, “Wait till you see the sequel. It’s gonna be nuts.”

Paul: Yeah.

Rich: And it’s general intelligence. I hate that phrase, by the way.

Paul: Yeah.

Rich: General intelligence. Is that what they call it?

Paul: AGI. Artificial general intelligence.

Rich: Okay. GI would be, like, gastrointestinal issues.

Paul: That’s actually much harder.

Rich: [laughing] AGI. I’m not brushing aside AGI. There’s that. There is that. But, like, good God, we just got one of the most insane tools to ever land in our laps in the last, in my entire career, and I’ve been around a bit. We have not scratched the surface of what we can do with it yet, and we can’t—we have not had the conversation about how it can insinuate itself into how we work in useful, productive ways. Instead, we jump to the, like, here come the robot dogs.

Paul: Well, and, you know, one of the things I’m seeing is a Wall Street Journal article—so we talked in the last couple of podcasts about how to sort of organize your career a little bit and pay attention to this new thing.

Rich: Yeah, yeah, yeah.

Paul: Learn some of it. Figure out, like, what the future might look like. But if you look, there’s a Wall Street Journal article where they’re like, well, no jobs for programmers anymore. And of course, when you read the article, it’s programmers going like, “Yeah, I kind of had to take a salary reduction after I got laid off, and it was hard to get a job, and blah, blah, blah.” And it actually, just, as you’re reading it, you’re like, this is what it is to exist in a normal economy where you are not made of pure gold.

Rich: Yeah, yeah, yeah.

Paul: Right? There’s just, I think, a shock to the system going on where programmers are realizing, like, people in the digital arts space are realizing that they’re labor.

Rich: I mean, we should say it out loud. There was an irrational hiring spree spawned by the pandemic. There was cash that was poured into businesses through, like, all sorts of, you know, government infusions and all that. And then the economy cooled off in a pretty major way. Inflation kicked in. This is, I’m talking ’21, 2021-22.

Paul: The interest rates went interest went up—

Rich: Interest went up, and then you started to see layoffs in the tens of thousands.

Paul: Yeah.

Rich: Like, not a few hundred. It was tens of thousands were shed by Google and all the big players.

Paul: And you and I are middle-aged fellows. Like, that was just life up until that boom. Like, you, I remember—

Rich: Yeah.

Paul: I remember being 20 and there were like, I was like 21 and I wanted to go make web pages?

Rich: Yeah. Yeah.

Paul: And, you know, IBM had just laid off, like, 30,000 people. Like, just IBM.

Rich: Yeah. And so I think I, and this is, I’m, this is all predating, like, AI showing up as, like, a credible tool for augmenting engineering, though—

Paul: No, I think, I think those stories—

Rich: I think that’s a comp—that’s a, I think that’s in the mix.

Paul: I think those stories are going to get put together and if you’re not actually using these tools, you’re going to believe that all programmers are going to get replaced.

Rich: Yeah.

Paul: And I see that narrative getting more and more popular. It fits in—

Rich: It’s a popular article, isn’t it?

Paul: It fits in with a lot—it’s on Hacker News, you know, it’s just, it fits in with a lot of preconceived notions.

Rich: Sure, sure, sure.

Paul: I don’t think that it’s AI just yet.

Rich: Not yet.

Paul: I think we’re quite—

Rich: Not yet.

Paul: —and that’s actually kind of where I wanted to take us, and close it out, which is we don’t talk about this a lot. We make a lot—we make fun of ourselves often as being. like, enterprise software people, because enterprise and business is seen as kind of a little boring, not as cool as consumer, the big, that’s the big, if you’re not in this world, like, the word consumer means good, flashy, cool, nice. Anyone can get—

Rich: [laughing] Enjoyable, yeah.

Paul: Enterprise means I need to file my expense report.

Rich: Labor.

Paul: Yeah. It means like, really—accountants love enterprise.

Rich: Greys and blues. Yeah.

Paul: But what I believe pretty firmly is that, like, we’re in… The big middle is where everything happens, right? Like, maybe there’s a revolution coming and it’s going to be absolutely insane. But I actually think what’s going to happen, and you and I talk about this a lot, because I like to get excited, but what it comes back to is, like, organizations, which are not mostly software organizations that use software. They buy Salesforce and then they sell carpets. Right? Like, they’re not software people.

Rich: Yeah.

Paul: And they’re selling carpets profitably.

Rich: Mmm hmm.

Paul: And you’re gonna come to them and you’re gonna say, “I can bring a robot here and it’ll help you with your carpet sales.” And they’re gonna go, “I already have pretty good margins.”

Rich: Yeah.

Paul: “I can’t even get more carpet from my manufacturers right now, so I don’t know if I want to spend another $100,000 on you.”

Rich: Mmm hmm.

Paul: Right? And so, and that conversation is unimaginable to VC. Like, VC is like, we, they’re just going to want it.

Rich: Let me share another conversation, which is carpet store became a carpet franchise, and now they have a dozen stores. They started out running the business in spreadsheets, and now they’re having a hard time keep up. And their, like, inventory is all out of whack, because there’s really no one single picture of what’s in the warehouse and what stores need. And they’re like, well, we should get a tool. And they don’t know where to go.

Paul: No, they don’t have, like—

Rich: They could be, they could be $30, 50 million in revenue. They could be, they could be 200 stores.

Paul: They don’t have a CTO. They have either a guy named Carl or a woman named Juniper.

Rich: Just making sure the computers get updated, get the virus update.

Paul: Yeah.

Rich: And so that’s also a cohort that VCs don’t talk about.

Paul: And I think that’s—

Rich: I should correct myself. There is a strain of apps that aim for those kinds of businesses. They are the sort of productivity, turnkey productivity tools, like—

Paul: Monday.com.

Rich: Monday.com and whatnot. Those do exist. The challenge with those is a lot of those smaller companies often don’t have that, like, kind of quirky gearhead advocate who, like, wants to set it all up.

Paul: No. And the big ones are really understood as buyers. Like, they go, you know, big sellers—

Rich: Big RFPs.

Paul: Yeah. And it’s, you know, giant government orgs and consulting firms are all in there. So that chunk of the economy is taken care of. The small businesses get out their credit cards. And then in the middle is the boring middle market.

Rich: Yeah. And I think what you’re saying, Paul, is that, first off, AI does make these capabilities more available, more accessible, to midsize businesses, to smaller businesses that never thought they could have a custom tool in their hands. I think there is still a gap, though. And if you, you know, and one of the roles that I think is going to take hold is an AI product specialist or app specialist or whatever, who goes into these places, listens to them, and then turns it into software. Like, that’s, that’s, I guess, historically a product manager, but they, like, go into a chain of, like, car dealerships or, like, ask them what a product manager is.

Paul: Yeah.

Rich: They’ve never heard of it. They’ve never heard of what you just said.

Paul: No. They’ll just sell you a Toyota.

Rich: They’ll sell you a Toyota. They know what, they know what the IT manager is.

Paul: Yes.

Rich: Because they fix the wifi and they set up—

Paul: Well, if they can’t, if the computer enough, they can’t complete the transaction.

Rich: Exactly. But you say product manager, they’re like, well, that’s the person that bridges the gap between your business needs and the software that should be in your hands. [monster?? noises]

Paul: Look, this is kind of our thesis because of the world that we live in, the world we find interesting. But on the small business sort of individual freelancer side, I think you’re going to see AI baked into lots of tools. You’ll tell it you want it to do something, and it’ll do something for it, it’ll help you prepare documents and so on. And you’ll spend $60 a month. On the other side, on the giant business side, you’ll see all these like, custom language models and all their stuff will be searchable and they’ll spend millions and millions of dollars and they’ll, each AI tool will serve, you know, millions of people.

Rich: Yeah.

Paul: And it’ll be built into your search tools and your experiences that they share with their, you know, millions of users or billions of users or, you know, that’ll be like banks and places like that.

Rich: Right.

Paul: Then in the middle, they don’t really need it, but they can save a lot of money, or it can help them with their growth.

Rich: Yes.

Paul: And these are, you know, tend not to be like publicly traded companies, or they might be, but they’re just not on anybody’s radar.

Rich: The economy is very big and there are companies with hundreds of millions in revenue that grew too fast that don’t know what to do.

Paul: I actually think that’s where the most opportunity is for this kind of technology.

Rich: I think what we’re saying is that is AI coming for your job? I think it’s the wrong question. I think is AI now making software available where it otherwise seemed out of reach for like a giant multi-trillion dollar chunk of the economy? Yeah. It’s, I mean, commercial flight—I get, I love these old photos of like, no joke. Like, a giant ham getting sliced on a 747, on a cart.

Paul: Oh yeah.

Rich: [laughing] It’s the funniest thing.

Paul: It’s just Thanksgiving dinner rolling down the aisle.

Rich: There’s like ten chairs.

Paul: Oh yeah.

Rich: There’s like ten seats on this flight.

Paul: Yeah, you bring your dog.

Rich: Everybody’s smoking.

Paul: Yeah.

Rich: Honestly, frankly, felt, looked like a better time.

Paul: It was.

Rich: [laughing] Looked—

Paul: The planes crashed a lot more.

Rich: But here’s the thing. Flying casually and having a slice of cheese and a slice of ham on a plane was a very exclusive experience in the beginning, obviously.

Paul: Very, very expensive.

Rich: Very expensive. Very exclusive. Now it’s a bus from New York to Chicago.

Paul: It’s the angriest bus. Yeah.

Rich: It’s an angry bus. But what used to be a luxury became eventually a commodity. The truth is, custom software and tools in people’s hands that is really tailored to what they need has been out of reach for most businesses. And so they open Google Sheets. That’s what they do.

Paul: I think this is real. I think there is the ultimate case here is more of a growth case than a, we’re going to destroy the entire economy of technology case.

Rich: Exactly.

Paul: And what the real offering here is, it can make boring things faster. Everyone gets upset because it keeps making interesting things badly.

Rich: Yes.

Paul: But I think what it can really do is do boring things and tasks that never get completed. The documentation, the outlines, the footnotes.

Rich: Take comfort in that, professional person. Take comfort in the fact that it’s doing interesting things badly. That means we are going to be needed to get it across the line, A) and B), to talk to the people who need it, because they’re not going to bother.

Paul: So let’s make a prediction. The carpet company. Okay? They do spend, let’s say, and let’s say they’re worth a couple hundred million dollars as a company. They spend $1 or $2 million on their, you know, their technology infrastructure.

Rich: Yeah.

Paul: Every year. They do that today because Windows 365 and the website and all that—

Rich: They still need their infrastructure.

Paul: —call center. Carpets get stained. Now, how long before they go, “I’m going to buy one of those AI solutions to help me with my call center, to help me with my…”

Rich: It’s a great question.

Paul: How long do you think?

Rich: I think this is new terrain and I think that people have to see it as something that is accessible and available to them. That’s marketing, and that’s storytelling, and that’s like case studies. And because the thing is, they are often tasked, especially companies that grow quickly, they’re often told, solve this. Our accounts receivable is, like, $70 million.

Paul: Right.

Rich: We can’t keep up.

Paul: Right.

Rich: It’s not working. Solve it. And so oftentimes the non-technology people are tasked with, like, either going out to consultants or figuring out something to relieve the pain. So it’s not like they want to buy new things. They don’t. You ever talk to people who really care about carpets or about cars, used cars?

Paul: They want to sell carpet. That’s it. Yeah.

Rich: They don’t want to talk to you about your features. They don’t care about any of it. What they do care about is they’re doing a bad job following up on leads. Their money is being left on the table because they’re inefficient. And their backlog is leading to bad customer service. Like, things like that is what they care about.

Paul: And I think, actually, if you drop in and you’re like, ChatGPT can help you with all that, they’ll just blink at you.

Rich: That’s not going to work.

Paul: Yeah.

Rich: It’s not going to work. You have to come to them. The good news is it doesn’t require six months of, a six-month journey to come to them with these new tools. You can come to them in a few meetings, and that’s a big deal for them. Like that’s, they don’t have the time for you. They’re not interested in an expedition.

Paul: I’m going to say something that sounds dismissive, but because they are not technology people, they actually can’t follow a thread. Technology people, it’s like, all right, it takes three months to get this idea across the line. They don’t have that mental space because they have their own jobs.

Rich: They are suspicious of experts that show up. They don’t find it interesting.

Paul: Right.

Rich: They see all of that expertise and all the terminology thrown at them, and it makes them nervous and they don’t understand it. And they don’t want to understand it.

Paul: They’re expecting to get fleeced.

Rich: They’re expecting to get fleeced. And most run away.

Paul: Yeah.

Rich: Eventually, it’s too much pain. Let’s package this up on this podcast. I think what we’re saying is this is opening up tons of opportunity, tons of new paths for careers, if you’re willing to go down those paths. Tons of opportunity for new, new types of businesses. I am extremely optimistic about what this is going to create.

Paul: Well, I think what’s real, because of the way it’s going to work, you’re going to see a lot of narratives. And we started to lean into it a little bit, but I’ve been thinking about it. You’re going to see a lot of narratives like that one in the Wall Street Journal, where it is, here it comes, it’s over. It’s over for—those engineers and those programmers and those product people, they got too full of themselves, and now the invisible hand of the market is going to slap you across the face. And that is never the right position to take if you are building your own career. The right position to take is this thing can make boring things faster. If you align yourself as a person who can do boring things and get them done quickly, you will definitely have a good life.

Rich: Go to where there is daylight. You are a writer? Former journalist, slash writer. I was a former lawyer.

Paul: Mmm hmm.

Rich: And we went to this exciting place where we weren’t really clear if there was oil under that soil. We just didn’t know.

Paul: Actually, in the early days of the web, for many years, there was not. Things would fall apart and there’d be no economy.

Rich: But entire nations have been built in those gaps.

Paul: Yes.

Rich: Right? And I think this is presenting new opportunities for that. So I think go to where these new opportunities are. It’s still early days, but it’s exciting.

Paul: I think that’s right. Worry about, like, getting some stuff done and see what happens. All right, Richard. Well, people should get in touch. Hello@aboard.com.

Rich: Yes.

Paul: We’re about to have a nice event. Hopefully you’ve received the invite by now and, right after this podcast goes out. So we’ll give you an update on that next week.

Rich: We are the co founders of Aboard, a pretty amazing, AI-powered custom software platform that can deliver exactly what you need really quickly.

Paul: I mean, frankly, a lot of what we just talked about here is what we’re trying to embody in the product, which wouldn’t be a shock to anybody.

Rich: I’ll tell you what will be a shock. We will not be alone in telling this story. There’s going to be more than one company, and the big ones will start to tell it, too, I have no doubt.

Paul: I think that’s right.

Rich: Because, uh, they can reach more people and there’s more opportunity. So—there’s gold in them thar hills!

Paul: There you go.

Rich: And by gold, I mean really interesting problems to solve. [laughing]

Paul: And you know what? It’s better than crypto. That’s what I’m gonna say.

Rich: Oh, absolutely.

Paul: All right, friends, hello@aboard.com.

Rich: Have a lovely, wonderful week.

Paul: Bye.

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