The AI Skills Nobody is Teaching (And Everyone Needs) with AI Expert Ethan Mollick

So when you're interviewing for a job, and everybody's good because of AI, how do I stand out and get a job that they still need to hire for? I'm fascinated by that. Like, if Claude is really good at running your company, Claude's also good at running every other company, and there's no variation between them, and generically high quality with no variation means there's no votes or competitive edge, I think humans who bring competitive edge to this one way or another, just by providing variation if nothing else is a useful way to think about problems, right? You start to care a lot more about the taste of that person than you do about the entire organization built to deliver the product. We're all a little afraid of AI. Even the people who love it are a little bit afraid. Some of us are afraid it'll take our jobs or make us dumber or change everything so fast we'll never be able to catch up. It doesn't help the most AI experts fall into one of two camps. They're the dooms or they're the zealots. That's why I wanted to talk to Ethan Mollock. He's an AI expert who refreshingly is neither. Ethan's a Wharton professor studying how AI, entrepreneurship and innovation impact our work. He focuses on how employees actually use these tools rather than how they're theoretically supposed to improve our work. His New York Times best seller co-intelligence and his popular substack one useful thing have become the go-to resources for all those people trying to make sense of AI without losing their minds. Ethan believes we have more agency over AI than we think. It's our experience, our taste, and our genuine points of view that are things that AI can never replace. And that's important because the choices we make about how we integrate AI personally and at work as a society will shape what it becomes. If you like this episode, please remember to subscribe. This is a bit of optimism. You are very popular right now. What were you, I know you teach entrepreneurship and other things. Before AI, what was the, what were you teaching that was the hot thing? In addition to AI stuff, my other thing I really care about is games and education and education scale, two related things. I've done a lot of work on using video games for teaching. So I was, I was, as the brand says, not famous but known in that space of thinking about games and teaching at scale how do we teach transformationally. So that is what they have worked on for a long time and the AI work was sort of in parallel to that. And was it your own personal curiosity about AI that sucked you in or was it that you were forced to use AI in the work that you were doing because it had to because it made it better? Went to business school and my PhD program at MIT and I worked with the MIT Media Lab with their AI group. So Marvin Minsk used one of the fathers of the field and I was the non-technical guy in the group. So I was the person who explained to other people what AI was, how it works, when we go talk and have technical conversations, I'd come along. I've been AI adjacent or involved for 20 years but always in the sort of non-technical, like how do we use this, how do we explain it role? And everybody else was technical because it wasn't really working out. Like, AI had limited use cases. And so when GPT-3 came along and started to make a splash and then actually, after that, I was sort of well positioned in this world of someone who'd been thinking about explaining this for a while in a non-technical world. The reason I was really interested in talking to you, because to be honest with you, I try not to have AI guests on. And the reason is, is because they generally come in one of two flavors, right? It's the greatest thing that ever happened, and it's going to make the world a better place, or it's the worst thing that ever happened, we're all going to die. And the conversations are, for obvious reasons, a little upside and one-sided, and they usually have some vested interest in one opinion or the other. And the reason I wanted to talk to you, to be honest with you, is yours is just more practical. It's not, it's the savior, it's not, it's going to kill us all. But it's kind of like, well, it's here, you know, kind of like the internet showed up. What's the best way to use this thing? And it's a little more down the middle. Yes. It's nice to be in a place where being somewhat pragmatic makes you unusual. That's not usually the place where you get publicity for being the non-bombastic version. It's true. But also, the other one with those two opinions is they tend to eat the world, right? If you think that we're getting a machine god who's going to save us all, then, you know, all of it matters is discussing that, right? Just like any other sort of religious belief. And if you believe that we're all going to die, how can you have a conversation about anything other than, you know, this is going to do myself? And the fact is, this is general public technology. It's going to affect everything we do, one way or another. It's worth spending some time on that. And some of those will be good, some will be bad. I do remember the sort of the rise of the internet. I'm old enough to remember it. And the conversations were somewhat similar, maybe less, less dramatic on either side. There was a lot of positive energy at that time. Mostly positive. But there was lots of conversation like I remember people who, you know, there were the zealots who believed that the internet and everything online was going to replace everything. You know what it is? It's the difference between eating to live and living to eat. You know, and if you leave it to the technologist, they think all technology is living to eat. I mean, they literally made protein powder shakes. I don't remember a soy in to your suppose. I remember a soy. I remember people for people who thought eating was too annoying. Why are we spending all our time worrying about eating when we could just get it taken care of? Right? It's a different view of efficiency. But it's also a view that kind of blinds you to the fact that technology is the most human activity, right? We're making tools for ourselves. How we use them, how we adapt them, how we regulate them. Those are going to have big influences. You know, AI is more self-directed than most technologies, but we still have a lot of agency over what happens next. I mean, I know from my own experience, most people are misusing or underutilizing the technologies that are available to us. And I'm already getting to the point where I'm turning on, you know, social media or listening to friends or reading an article. And I'm already feeling overwhelmed by all of the advice of people telling me that I should be using it like this. And I be sitting up in the agent to run my life and sitting up in the agent to do my marketing and sit up in the agent to do my finances. I'm already overwhelmed by all the advice of how I should even be prompting the machine to the point where I'm almost backing off and shutting down because one minute, you've got to only use that one the next minute. You've got to only use Chachi BT then. You've got to only use Claude. It's all too much already. And for anybody who's not predisposed to like be all in, that reaction, I think, is pushing some people away, believe it or not. Well, I absolutely, I mean, look, I am a nerd of the old school. So I like getting into the details of stuff and partially like explaining them, which is I think part of why you have me here. But also it is overwhelming. I mean, part of what's actually interesting is AI has got any easier, right? Not to be too, you know, too evangelistic about it. But like it used to be the stuff mattered. Like you had like all those little details like prompt engineering mattered. So it mattered how I phrased things. It mattered if I said, you know, you are a physicist. It was better physics. If I said, think hard about this. That matter. If I offered bribes, that would matter. We've been testing all that. None of that matters anymore. The models have gotten good enough that if you're good at giving instructions, like a human to humans, you probably do okay with this. And suddenly all the models are getting good quite quickly. So whether you open AI or touch the beauty, they're like touch the beauty or Gemini or anthropic. They're all three of those are pretty solid. There's like one or two hints I'd give people. But otherwise it's really just use it for stuff and don't stress how you're using it because you'll figure it out. Also, when we talk about like AI is going to take away all of our jobs. And by the way, those are the technologists saying that. One of the things that I also love is the technologists are also very fond of saying, you know, things like 80% of the jobs today didn't exist 20 years ago. Which means it's fair to say that 80% of the jobs in 20 years we can't even imagine. And to your point about prompting, it wasn't that long ago where the technologists were telling us prompting is going to be the thing. And people are saying, I'm going to get a degree in prompting and the technology got good enough in just a few minutes that that literally went away. Yeah, and I think that that is part of what makes this kind of interesting right is we can't imagine the jobs we will keep trying. And also not imagine the jobs does get nerve racking when like, you know, AI is here. It's like, what is the job? Well, I'm not 100% sure. I mean, I think there's both legitimate reasons to worry about jobs. These systems are very capable and very confident. And they do change their impact real work. This is not electricity in the same way of like we need to figure out a way to harness or use this thing. There's a real impact. I've talked about this a little bit. I actually think that, you know, nature pours a vacuum, markets correct. When we have a bubble, the stock market will at some point not of our choosing correct itself. And it all systems seek equilibrium at some point. I'm fond of saying that in the 70s and 80s, robots started enter factories. And the blue collar world said, hey, we're going to lose our jobs. And the white collar world said, it's the future baby progress stops for no one. Reskill, you know? And, you know, the pendulum duff swing. And because your plumber doesn't care about AI, the carpenter doesn't care about AI. The mechanic doesn't care about AI. The people who care about AI are the knowledge workers. Yes. And, you know, it's the future baby progress stops for no one. Reskill, baby. Yeah, that's a really sad. I mean, there is a come up with, but there is another thing, right? Like, if you look at the last three industrial revolutions, there's either two or three. I mean, that's always got right. And the reason they worked out wasn't because the technology made everything great alone. It was because it was also labor fought against, you know, capital. And you had a whole bunch of fights happening. Unionization is how the benefits got spread around, right? The technology doesn't naturally do them. What's really interesting is we're going to have a similar fight here, right? Like, AI, we already have good data, right? AI is pretty good at being a doctor. It's getting better being a lawyer all the time. Like, most lawyers I talk to, see a trajectory where not too long from now, Now, you will be able to get as good advice for not the most complicated issues from the AI if you're not already, right? And there's ongoing debate about this. But the thing is lawyers are not going to be quiet about losing their jobs. And it turns out a lot of Congress is lawyers and a lot of people don't have money or lawyers. And I'm willing to bet that you're going to see laws passed in every state that you can give a lawyer officially a human sign off of it. So even if they're worse than AI, right? Yeah. So part of this, like, there is a little bit of, oh, it's your come-up and white color workers. But it's also like, no, no, they've got the, like, they're, they're, they're fields that are not going to go easily, right? And, you know, doctors, lawyers, it's going to be interesting. Coaters really do not have the protection that doctors or lawyers or actors or other kind of guilds or associations do. So we'll see a lot of conflict over these issues in the near future. Loving for our own interest is not a new thing. So for example, for years, there have been people who try to raise money for the government, you know, where we can get more income. The average lifespan of a dollar bill is about one year. The average lifespan of a coin is something like 30 years. And so the proposal to move dollar bills to dollar coins, because it would save the government, you know, untold billions per year in printing and all of the rest of it. And the reason we haven't done it is because of the income paper lobby, because they like those billions being spent on them to make new dollar bills every year. And so, you know, we're used to doing things that are not to our advantage because of lobbyists. And this is just another thing where those who have access to power and those who have influence will protect their interests, as you said. Not necessarily badly, right? Do we want all lawyers out of a job? It's an open question. A lot of people will be like, yes, yes, please. But like, you know, I mean, already, actually, there's some early evidence that the number of cases being submitted to judges is exploding exponentially, where people are pleading their own cases with AI law. I'm like, how do you deal with that? It used to be that we had a filter, right? So the secondary thing is you had to give it a lawyer to take your case. And if they did a bad job, they would be punished. And if you got a 100 page legal brief, a person wrote that. And that was an indicator of real efforts. But now it is it. We deal with that kind of system. So we're going to have all of these ripples in all kinds of areas that will require policy of changes, regulation changes, societal changes, even if we don't have sort of a apocalyptic AI event the way we were talking about earlier. So let's go from the theoretical to the practicals. And as we sort of said before, which is a lot of people who aren't technologists are underutilizing or misutilizing this remarkable technology. Some are still using it as a glorified Google. Google to search. It's more of an answer machine, but still I mean, we all do that because it is a very simple and fantastic use case. The more nuanced and complex prompts, I think I know I'm underutilizing. Like I ask for an answer, even if it's something that has some depth, but I don't ask it to write a report or make an interactive dashboard of the data that I'm not, I know that I'm not doing that. And I'm already ahead of some in terms of my utilization of the thing. I have two questions. One is you're teaching students, you're teaching a lot of grad students at business school. Is it a false belief that just because people are younger, they're all in on this technology or are they also sort of bumbling and fumbling their way as they learn about it? So we actually have a paper on this. So I think what people think, I hear this term in the internet, we're talking about digital native all the time. People talked about this, right? Like kids these days are good at using the internet. And indeed, like if you talk to somebody who grew up with TikTok, they will know all these intuitive ways that as an older person, you will not understand, like, no, that's cringe. There's a bunch of rules and slang and approaches that you want to take. And I think that that model kind of carries through the younger people get the technology. It does not hold for AI. Like I talked to like SCHR, I was like, oh, the kids these days, they're AI native. I mean, they're not AI native. You're just talking to Claude. They're conduits to Claude. Like, if you ask for a report, they'll give you a beautiful report. They have no idea what's in that report. How could they? They have no knowledge of this. They're just giving you what Claude says. And we actually found some evidence on this when we did a study at BCG at Boston Consulting Group. We found junior employees were often much worse at using AI. They seemed like they were using it while they were adopters. But how could they judge whether something was good or bad? I think this is a rare case where the more experienced you are, sometimes the older you are, the better you're going to be at using AI if you decide to use it. Because you can intuitively grasp how do I give instructions? AI works enough like people that if you give an instruction and you're good at a field, those who would be like, no, no, I understand what went wrong there. You're thinking about this. You should be thinking about that. Even though the AI is not a person, it doesn't think. You'll know what kind of information to expect to get good answers. So I think actually experience really does matter. If you think about how education is built, we're actually schools are in chaos. I mean, they're always in chaos. Universities have always been in chaos. This is not new. You know, people are cheap, which is actually we T. But we actually know the pathway forward. It's going to be a little bit messy. But we'll do more in class assignments. Outside of class, we'll use AI tutors which are going to be very effective at controlled experiments. We'll make them work better than we do now. In class, we act of learning. We'll figure it out. We can't figure it out. I am worried about the next stage. I teach people in general, I say, "Warton." They become specialists. They say, "We've taught specialists for 4,000 years," which is a apprenticeship. I send them off to work for whomever. They go work at Bank of America or whatever. They learn the job and everyone gets a good deal. They get a little bit of income, but not as much as they would probably deserve. They get a chance to prove themselves. They learn the ropes by doing run-work over and over again. The middle manager assigns them run-work that they don't want to do anymore. It gets to evaluate whether this person is any good or bad for moving up the ladder. It's been a great mechanism. That just broke. Every junior person knows less than ChatGPT. They would rather just use ChatGPT. They'd be dumb not to use ChatGPT or Claw to give you answers because it's better than what they could do. Every middle manager would rather delegate to the AI than a flawed human who takes forever to give them an answer. It is good. We're just doing AI work to each other. I think that's the kind of problem that you're talking about here, which is the danger is that we lose the talent pipeline. There are solutions to it, but they're going to require fairly radical change in how we think about talent pipelines. How much of this is kind of like art? Here's where my brain is going, right? Which is, I am an art fanatic. It's the thing that I love more than most things. I am totally fine with AI-making art. It doesn't bother me. I am totally fine with AI-making music. However, when I hang something on my wall, I like knowing that a person conceived of it. I like knowing that a person made it because when I buy a piece of art, I'm not just buying the visual thing on the wall. I'm buying the story that goes along with it. Or for example, I was listening to some music this weekend. I was listening to John Batista's Beethoven Blues album, which is, if you haven't heard it, spectacular. Now, could AI make a blues version of a Beethoven Sanada 100% it could? But the joy that I got from listening to that music was not just the music that I was listening to, but I was smiling that a person had the creativity to come up with this. And that was part of my joy. When we look at the work product, you know, there's two things we're neglecting, which is, I like thinking. I enjoy debate. I enjoy making my head hurt at difficult things. I enjoy learning. The same way a painter likes painting and a musician likes playing music and composing. Where is the human desire to want to learn and then will our schools, but especially our places of work allow for that to happen, where they all become so obsessed with efficiency that we actually, even if we want to learn, you see where I'm going with this. There's 10 million directions from here, right? So I want to put a pin on the art thing because it's actually really important and interesting, which is, you know, obviously the webby rise of our more artisanal human-made things. The most direct version of this by the way is when you have AI and poetry or long form fiction, there's often a lot of things wrong with it, but because we're used to, if we read something that reads beautifully and it's effortful to read, we assume that there's a purpose behind it. So we spend our own effort figuring out the whole. Like, for example, the eyes are very famous at weird analogies, right? So it might say this conversation is like a gap to smile. Now, that is not meaningful, but if you spend some time thinking about you're like, "Oh, how is it?" And you will reach a feeling of meaning, right? If that was, you know, Lazdo, Crosdekyre or someone else writing this set of stuff, and I was reading, I'd be like, "Oh, this person thought hard about that analogy and I just spend the work to do it." If it's the AI doing it, you know, in some ways it's beautiful, but the meaning comes from me and I'm being cheated because I have to create the meaning that has no intention. The intention belongs to the artist. The intention now is shifted to the list of art, right? Maybe it always has, definitely the novel stuff. But like, so that's one angle that's kind of interesting, right? And then I think the sort of second one is, you know, is on thinking about developing some of these kind of, you know, how do you develop intuition? And we actually have a way of doing that. We know how to train people. Like, we could teach people the experts, but the problem is it's effortful. And so, you know, like, there's always been this sort of view that I told you earlier on. I made games for education. And one of the most depressing things you learn is you can make something incredibly fun. But first of all, it's only 80% fun. It's not as fun as actually doing a thing for fun. And second of all, learning is effortful. And if you're not doing effortful work, then you're in trouble. And now for the few areas that we transically care about for you, you know, it might be art history or music or maybe for some people, it's math and science. Maybe for some people, it's, you know, it's a sport they care about. Whatever you, we are effortful about. And in transically motivated, you're like, why isn't all learning like this? And the problem is you don't care enough about it. Right. And so, but I still want you to learn math, even though you don't want to learn math. I still want you to learn American history. And if you shortcut that through AI, giving you an answer is you learn nothing. We've had enough experiments to show that. So making people essentially lift mental weights becomes the problem in a world where there are shortcuts. You know, I find there's a great irony in all of this, which is the problem actually doesn't lie with AI, which is we've been on the steady drum beat, this path to this point where we are, you know, discomfort avoidant. The concept of ghosting is the thing where you just avoid it. difficult conversation, or you see now a particularly among young people where they're more comfortable with quitting a job than having a difficult conversation or getting negative feedback. And then the idea that we've become so end result oriented, you know, as as capitalism has become short term focused and more focused on a shareholder supremacy, shareholder value over the quality of the product or customer satisfaction or employee satisfaction, you start to see we become more results oriented and we've left out the work product. This is not a new concept. AI is just the most exaggerated form of being results obsessed at the expense of the effort the work or the journey to get there. Well, and just to take another path from that, I mean, part of this is what makes AI work so challenging, right? Because if you want productivity gains, you just you'll get 100 times more power point, right? Right. So it requires you to rethink what the work is. And so what the work product is can't be the same thing. I mean, even the most basic way, coders can write 100 times more code than they could be for. If they are embedded in an organizational process where it takes two weeks to do a, you know, a product sprint as they often call them, right? So each of the stand-up meetings every day and the assumption is the code will write X them, or work the product manager will do this, the designer will do this, the marketing people will do this. What does that even mean for an organization becomes a problem? So part of this is our systems were coming back to that theme we've been developing throughout, which is human systems are not built for an AI world. We have, we're effort, you know, school wasn't built for a place where anyone could write your essays, right? Like, you know, and like work wasn't built for people to be able to produce power point on demand without thinking about it, right? Fiction wasn't built that I could write as many papers. The lock clerks and courts weren't built for anyone to be able to bring up our case. That's not a problem. That happens in every industrial revolution. It's just all happening once everywhere. And sometimes the AI wins, sometimes human systems win, sometimes we both lose, but that's where I watched the adjustment happen. I'm going to go backwards a little bit here. Let's go back to practical, which based on classroom and in the business world, because I know you study that as well. What are better simple ways that we could be using the technology available to us? Because most people are misor under utilizing the tool. And, you know, I'm overwhelmed by the people giving me advices of how I should be doing things and what I could be doing. But, you know, from a, from just a basic standpoint, how can somebody level up just one to 10 percent? You can get more than one to 10 percent. I take no money for AI labs, so you know, it's not like a, I don't like a, I don't like a shell, but you have to end up paying 20 bucks a month to one of the big three companies. This is what I'd recommend. Google's Gemini, open AI's ChatGPT or Anthropics Cloud, and you have to actively pick the best model available at that point, which is what you'll have access to what are called thinking models and those will change over time, but you have to actively select that. Default to a lower one. You will get huge impact improvements just from picking the most recent model and using it. The second thing I would say is AI has gotten quite good. So there's kind of three phases of AI. There's prior to ChatGPT where mostly we talk about AI, we'll be talking about how you use data analysis, basically. If there's all this, like algorithmic fairness and price mining and all the, like, you know, customized pricing, all of that came from prior to ChatGPT. Then ChatGP kickoff, Generative AI, and what I will, who are endosly call it because it's out of my book, my previous book, Cointelligence, where you'd work back and forth with a Chat bot to get an answer, right? I typed it with a Chat, it would give me an answer. Now we're in a new phase, which is called a GENTAG AI. And it's really just three or four months old practice. What does that mean? What does that mean? An agent is an AI system that can independently go do work if you ask it to. So a GENTAG is just the adjective of agent? Agent, right. So a GENTAG is an AI agent and there's marketing in terms of random, but it's an AI that can do work. The most important thing to realize is how good the work is and how long the worker it is. There's this paper and test by open AI. So you always take with the grain of salt, but there's been independent enough assessment. I feel good about it, called GDPVAL. And what they did was they took people representing 5% of the US economy. So journalists and product managers and lawyers and private investigators. And within average of 14 years of experience, they had them each create a really hard problem that they face in their field. They had another set of people with 14 years of experience to do it. It took them an average seven or eight hours to do the work. And then the AI did the same thing, took about 15 minutes for the AI. Then they had a third set of experts come in and spend an hour evaluating the outputs from each of these, not knowing who's who's who's and voting on which they liked better. And when this came out a year ago, the best AI in the world we're getting about 48% 48% of the time they were tying or beating humans. The latest models as of when we're recording this are about 84%. So 84% of the time, the work that they do seven hours of human work are equivalent to or better than a human. But that means going back to practical pieces, you would probably save three times effort and three times a cost. If every complex job you would give it to AI and even if it took you an hour to put it together in a value, even if you had to give up 30% of the time, you would still save the time and effort. So one of the things I think you're doing is not using AI and giving it hard enough task to do. Okay. And so that's the other thing, which is the value of the AI, where efficiency is not how quickly it can solve the problem, but how quickly you can evaluate whether it got the problem right. Which again brings back to expertise. An expert can look at this right away and be like, it not just as wrong, but like often it's wrong because of a specific problem that you should have either specified better or the AI is stupid about something. And sometimes you can instantly get, oh, it's never going to get this because it's too subtle and I can't communicate the point. I'm just going to do this myself. But sometimes you're like, oh, yeah, yeah, this is a rookie mistake. And I should remind it that when it writes articles, it not just factually explain everything but explain it with a story or whatever your thing is. And then it's better, right? So evaluation feedback, these are things experts are good at. And the AI responds really well to that. He was the other problem, which is, I remember when I wrote my first book, right? Everybody told me everybody in the publishing world said the most difficult thing for any author is, quote unquote, to find their voice, right? To have a voice. Now it's a very hard concept to understand, you know, what voice is. Essentially, it's when you read my words, they are of me. They might, they're my personality. They're, they're my point of view. It's not just nicely written, but it is, it is of me, right? And it's very hard to do for an author. And I have found that AI can write beautifully, but it has no voice. And if you ask it to have a voice, it's going to always have voices that are available to it in the world, in other words, published people, but not you. And so most writing will start to just sound the same. I mean, I'm already seeing it. I'm getting AI generated emails in my inbox and they're all basically the same email. It's not X, that's Y. It's doing the heavy lifting here. The thing that keeps me up at night. You see, this is a load bearing argument. It's the Cato 3 sentence, but word, word, word, word. And I'm starting to just delete them all because they're all familiar. Yes. And none of them stand out. Right. And I push back. I'd say it's not that it doesn't have a voice. It has a voice, right? A singular voice that is all voice or a tragedy between them. And it's actually not a bad voice. Like, if I always get, if I didn't see it for a billion times, it's a voice. But it's not your voice. Right. It's a perfectly good voice, right? It's a little dramatic. It's just sometimes it's like, it loves transitions too much. Obviously, it loves, you know, M dashes too much. And that is another thing that is like developing your voice. Now, a lot of people can't, right? Like, not everyone's a good writer. No matter how much we teach them writing, they don't get it. Ghost writers have been around forever, right? I'm glad, you know, that I'm writing is something I do and I have established voice. I know plenty of people who use ghost writers to do their kind of work. I agree on the AI voice. Now, I will say, you can get it significantly more like you. Not for the kind of long form work of a book. A tip here, if you want to do this, is give AI a large sample of your writing and then say, right, two pages summarizing the style of this and the instructions and how to write in the style. And then you paste that into your custom instruction and you say, right in the style, it will not, it will be slight parody of you, but it will be infinitely better than if you just say, you know, right like this famous person. Right. I mean, I did something recently as an experiment, which is I walked around the living room just talking into Claude and said, right and op ed in the style of Simon Sinek, here's the idea. And I just walked around the living room for about three or four minutes and then it gave me a pretty remarkably written article. Then I said, fact check it and it said, well, that's wrong, that's wrong, that's wrong. I said, okay, go offer me what I could say to make it factually correct. And the thing that I enjoyed about doing it, which is, you know, it takes 80% of my time to make a shitty first draft. And then editing is reasonably efficient and a lot more fun to really just clean something up. Most of the time is the first draft, right? And so here I got a shitty first draft in a few minutes and then I sat down and with it, you know, it fact corrects it, which is so efficient, I didn't have to go do all the research myself, although I did double check all the research just to be sure. As you point, the error rates of these things would drop. If you use a marker model, it's not making mistakes. It's not making mistakes the same way. I have to say it was actually kind of fun to edit it in my voice with my sense of humor. And the last finishing touches I realized I could put my voice. I was pretty impressed. Now I could cheat because I have written enough that it can know my style and I wouldn't say it was perfect, but it was, it was scary good. Yeah. I mean, there's a few things going on there. One of those is this idea of disruption to writing and I mean, there's cost to everything, right? So one option of writing the crappy first draft is it's your crappy first draft. So I always recommend some crappy first draft. because otherwise the AI's ideas will take over your ideas. It's very good ideas and you're like, you will find you can't brainstorm. But with that said, I find this kind of a similar loop of like editing is a weird way of approaching and it's not how we used to do it before, which is like I can get something written in my form and then I edit it. I'm sure some writers have worked that way for years, but that's a disruption to writing that might be better, it might be where it is hard to know. It's something you're a factory producing first drafts that you can pick up all the time. Or maybe some people are just really good at editing and they weren't good at draft writing and something they're more productive than they were before. - I think this is one of the future jobs that we underappreciate, which is not just that jobs are new, but that the weight of the job will shift. - Yes. - To your point, we've always celebrated the writer and editors have always been like, just there. If you work for public relations or you work in magazines, like the person who's the writer who wrote the press release, they're the person who went to school to write the press release and we just sort of like the editors are just the lower paid, you know, fail writers, you know, quote unquote. But now I think the writers, I think that the balance will shift. - I think we're gonna see the cross with lots of jobs, by the way, to come back to the job thing. So jobs are many tasks, right? A writer does, like as a writer, you're in charge of writing and editing and fact checking all of it. And the AI does some of that work. It shifts the burden of what you do, but it doesn't take away everything. And I think what we're gonna see in a lot of jobs is the idea of bottlenecks that the AI is good at some stuff but bad at other stuff. I would call the jagged frontier of AI in our early papers on this, which is it's good at some things bad, at some things you wouldn't expect. Where it's bad, right? Writing perfectly in your voice, getting a joke right. Like suddenly the demand for your labor is higher there, right? And your value is higher. It might have been that your jokes were not what was getting you, like that was not your main deciding factor. But if you're better at jokes now, something that there's value. Same things happening in coding, by the way. It used to be that writing really clean code was a really good skill. Now the AI is right most of the code, being an architect is good, being an engineer manager is good. The job's changed, what's important, what isn't important changes. And that changes who's good about it at two-precuring new opportunities and new risks. You may have instead of 100 coders, you might have 50 or 30 working on the team, but there's still human beings with egos and securities, lack of sleep, all of this stuff. And there's still somebody overseeing the project who has to manage all the messy human stuff regardless of how good the technology is. I for one believe that doubling down on human is gonna become even more important now because we still have to take care of the people who are working on the products with their AI agents. - Oh, absolutely. And also when I went to the code hit in the past, I had to hire a company to do it. Now there might be a code of working for every two person team and more software is being created than ever, right? So the jobs are unimaginable in the future, sort of an annoying thing to say. I think it is annoying because I think we actually have some idea of what this looks like, which is not that coders are replaced by, you know, prompt engineers, but that the job of coding changes, that the man for coding shifts from giant organizations for a thousand people worked together programming to now disperse to your card dealership, might have a coder building customized software for you around what the managers want to the team. You might have two developers working for you rather than outsourcing web development that are evolving things, the nature of software and the jobs change. And I think that that is a missing piece of this puzzle also. - And I think the other thing we aren't appreciating, which is the more things get good, right? 'Cause it used to be that quality would help you stand out. - Yep. - That if you were smarter, a better coder, a better writer, a better this, a better that, whatever it was being good at something made you stand out from the crowd, right? If the quality of, let's just say everything gets slightly higher or a lot higher, then it commoditizes so many products. And so what I'm curious about and cannot predict and don't even have a thought about what happens here, but if everything just becomes generically good, then how do you stand out at a market now? And we've kind of seen this with the rise of social media. We're in the last generation that has movie stars. I think it's the death of the movie star. Nobody's really buying a ticket to go see a movie because a particular actor is in it. Like one battle after another, lots of people went to see the movie, very few went to see it because Leonardo DiCaprio was in it. You know, that's what the movie stars used to do. They used to make people go see the movie. Now we'd rather see the franchise, when we're interested in Marvel than who's in it. And this is what I mean by commoditization. I'm so curious as everything becomes better and commoditized, TV channels, everything's commoditized. What's the thing that makes companies, products, and people stand out? So when you're interviewing for a job and everybody's good because of AI, how do I stand out and get a job that they still need to hire for? I think a few things are, there's a lot of things there again, right? Part of this, by the way, is writ large, right? Like if Claude is really good at running your company, Claude's also good at running every other company and there's no variation between them and generically high quality with no variation means there's no votes or competitive edge. I think humans who bring competitive edge to this one way or another, just by providing variation if nothing else. Yes. It's a useful way to think about problems, right? But your sense of taste matters, right? And presumably, you know, why people listen to you? It's like your sense of taste of who to talk to, the kinds of questions you have. You know, similar to the sense like, do you like Rothko or do you like Rembrandt? Like there's different tastes that have different kinds of outcomes. The second thing is developing taste, right? It's a bigger issue, which is how do we get people to develop taste? It's usually a casual, casual lifetime thing. That might be one of the new talents we teach people is developing a sense of taste, which requires experiencing broad things and making choices and having them look how do you describe your sense of taste and choices? I think that as people become bigger creators and they can do more, their taste matters more. Like directors may end up matter more than ever because I understand what I'm getting with a Wes Anderson experience, right? And if he can direct the whole thing the way you want to do, what would that look like? And we might find the same kind of thing with all kinds of other stuff. There's someone who has a particular taste in ice cream styles. Now you can make ice cream on demand because they will connect you through the APIs to a vendor that makes that product for you. So it kind of fits in of enabling one person to do much more, you start to care a lot more about the taste of that person than you do about the entire organization built to deliver the product. So good. I mean, I have my own biases and opinions, but I'm curious, is there actually a difference between Gem and I, chat, GPT and Claude? I know Claude has a much more B2B focus business model. That means security is more of a thing because business wouldn't stand for any lapses and security maybe customers might. Is there actually a difference? - So there are just a half step back on the boring educational side of this. When you think about AI now, you want to think about three things. The model, which is the brains of the bunch, right? At the time of recording this, that's Opus 47 from Anthropics. That's a Claude model, chat GPT 5.5 and Gem and I through it in one pro. By the time you hear this, they will be slightly higher numbers on all of those things based on how things are going, right? But those are the brains, right? The better your AI model is, the smarter it is at everything. It's better negotiations, better poetry. It's better math, it's better, like, but that's the brains. Then you want to consider apps. Apps are the tools you access these. For most people, when I say app, what they should be thinking of is chatgbt.com or claw.ai or geminite.google.com. That is an app. But the apps that people are creasedly talking about when they use AI are things like Claude, OpenAI's Codex notebook LM, which you haven't used for Gemini's free and very impressive for research and gathering data. And those are very specific tools built for the purposes. And then finally, there's what we call harnesses, which are how the AI can do things, right? So a harness lets the AI write code or do internet searches or make images for you. So right now, the three big companies all have roughly equally good. We'll probably, you know, jockey from position. But they're all making very good brains. The models are all very good. Right now, Google has the most diverse set of products of apps, but their main apps are probably weaker than Anthropic or OpenAI. And they have worse harnesses for the main apps. So if you want to use AI to do things, right now, the most powerful tools are Claude Codercod work on your machine if you're using Anthropic or OpenAI's Codex tool. And what makes those different is they use your computer. So like you can give it access to your files, to your email, it can, you know, it can do work for you using your machine, your web browser, whether you like this or not, right? And do work. So because of that, those two are kind of jockeying back and forth for the lead, but all three of them are quite good. The models are good across all of them. So now let's talk about security, right? So we're all tired of meta and all the other companies, you know, filling our computers with cookies, tracking our every movement on every website, even after we've left their website and their product. You know, we've all become very sensitive to turning off cookies and data privacy is now a thing, you know, do I want to give any of these AI models? Do I trust any of these companies to have access to all my computer, all my browse history, all my finances, et cetera, et cetera? So it's a hard question, right? I mean, there are more secure versions where you can even run your own version of these tools, but they will not be as good as open AI, anthropic, and Google's. There are a couple kinds of security conditions you might have. One of them is, are they taking your data and using it to train their next model? If you pay 20 bucks, all of them have an option to turn off that training feature. Is that enough privacy for you? It's hard to know, right? There's open questions about whether or not someone's AI history will be searchable. Is it, you know, is it something that lawyers can demand to look at it, right? Discoverable. There's open questions about, you know, what will companies do with this in the long term, even though they sign agreements with you. But in the other hand, Gmail probably has all your email in it, right? These look like enterprise software applications at this point, rather than sort of invasive individual tools. So do you try how much you trust, you know, Google with your information or instead, with your information, we're in that same kind of boat over again. The difference is, as much as I don't want Google to have access to my Google, my email, I know that it does, but I know that nobody can go out onto the web and ask a query in a Google search to read my email and tell me something. I think a lot of us are afraid that somebody could just go on to chat GPT or open one of the other. There's no, it's just like Gmail in that way, right? There's no bleed over where there's just one giant inbox and you're just barely holding it together, right? It works the same way. I mean, it looks like enterprise software. So that has its own risk, right? But the basic risk of like can someone just ask for something and get access to your chat GPT? No. If they log in with it, you know, you have to do all the same things you do instead of to factor authentication. Don't leave yourself logged on to a computer, but it works. The analogy I would have is Gmail, right? Like Google has all this information. They're obviously processing it and using it for their own purposes, but they're also not going to, you know, they've anonymized it in some way to try and create trusts. It takes effort to hack into someone's Gmail. It's the same kind of boat, right? Now whether or not we want you want a company to have even more power over it, those are choices you get to make. But I don't think we should put this in a separate privacy category. The actual risk is if I let it have access to my computer and it could use my web browser, you know, could someone convince my AI to send them all my money if it's, you know, if it's reading all my emails? And that is, you know, hasn't happened yet, but it's not impossible. Right. So obviously because you are, you know, you teach this, you embrace this, you allow your students to use it, I assume. I don't know how to ask this, which is how do you ensure that your students are learning if they are allowed to use these tools to learn? So I went viral first in education with my syllabus right after the chat, the first version, which is what we call GPD 3.5. And you know, that was around for a few months. GPD 3.5 was pretty flawed. Like you would make up arguments all the time, but obviously it was an aid. It felt like, you know, I like a smart, you know, ninth grader or something like that, right? And so I teach college courses I could tell. So my original policy was use AI for everything you want. You're accountable for the output. That was great for four months until GPD 4 came along, which is now obsolete, it wasn't good for a while. And it was as good as my students across something, not across all things, but enough that a low effort student was worse than GPD 4. And I can no longer tell people, just use AI I can tell because the AI was giving them the answers, not being the answers. And we've seen this over and over. There's a lot of studies that show if you just use chat GPD to get answers to questions, you think you're learning, even if you're not cheating, you think you're learning and you're not learning because the AI gives you the results. But it turns out we actually know pedagogically how to solve this problem. We did this with calculators, right? But in school, which is we could do in class testing, we can make you use the AI for some stuff and not for others. So for my class, I'm looking at T-Dontaprenorship. So output is in some cases, like I gave all my students, for example, what I called the bootcamp test, which is the name of the Blade Runner human test, but it made my own version of it. And they had to launch their startups using AI, but based around areas they were experts in, experiences they had had, knowledge of the world they had had, a viewpoint they had, which kept them in the picture. And then they also had to do a lot of in class stuff, right? We had to have a discussion about these things. I actually had them use AI tutors that asked them questions. They had to use an AI to build the case study with it. I set up the AI, so it won't give them all the answers. It would challenge them to come with a case study information. So there's things we can do, but it does require changing how we teach. But the reality is technology does affect our brains. Like, I mean, I'll give you a real life one-to-one example, right? In my mind, I used to have a steel trap for phone numbers. I knew everybody's phone number. You told me, "Give me a name. I'll tell you their phone." And I didn't have to memorize it. I just heard the phone number and I had a steel trap of phone numbers. It was just how my brain worked. And I, in the early days of, I bought a Casio digital diary. I got it from my birthday. I remember, you know, it had two K of memory. I think I upgraded to the 6K when it came out. It was like hardcore, right? And it was the most remarkable thing. And I programmed all the phone numbers from my memory into the device and then slowly added more and more phone numbers as I learned them. And my brain was like, "Okay, if that's what you want, fine. I can't remember a single phone number anymore." And if we have to remember that the Iliad and the Odyssey were oral traditions. You know, this book that we were forced to read in school that's like, you know, 800 pages, you know, go back a couple hundred years. And it was like, "Son, it's time I tell you the story of the Iliad." And you will tell your son the story of the Iliad. It was oral traditions that people remembered, but because the printing press, our brains just stopped remembering stuff. So this has to have an impact on our intelligence. There's no getting around it. I mean, absolutely. I mean, look, my grandfather was an engineer who built like the Fire's Appression Systems for Cape Canaveral. And his dissertation was writing, doing a single piece of Matrix multiplication. I have no idea how to do what he just did. And he did slides rules to do it. I've no idea he used a slide rule. My kids have not learned cursive, right? Like, we give up stuff all the time. The whole idea of technology is on purpose, we give up things that we used to be able to do, the machines. So we don't have to do them anymore. And every time we face the same choice about what's value and what's not. And when I worry about, like, the default version of that is bad, right? I mean, we've seen this happening with like, you know, you can argue short from video, it's killed reading because it's more entertaining to do that. I don't need to spend the effort reading the book to get there. Okay, that was a bad choice. We are going to have a ton of these choices, right, around AI. It doesn't hurt your brain, but it is a choice that you can hurt your brain with, right? As an educator, part of my job is to get around that problem anyway. People can survive a lot without reading very well. They can survive pretty well without doing math. They don't have to learn American history. Like, there's some degree of making this requirement. But this is a slippery slope, right? Because now we go down the path of, oh, you don't need university. And there's a whole movement that you don't need to go to college. And what we forget is you may not need the subjects that you learn at college, but going to higher ed teaches you to think critically. It teaches you to argue with people who have way more education than you and form strong arguments to take them on. It also teaches you, adulting. And so my problem isn't that technology replaces that there are sacrifices. Like, I accept that I don't have to have a memory for phone numbers because of technology anymore. That I accept that. My concern is that thinking, the ability to think, is the sacrifice here. And that's way more damaging than remembering phone numbers or remembering the Iliad. So I push back. I don't think it destroys your ability to think. I mean, I think for a lot of people, it gives them even more ability because they have a conversation partner at their level who's willing to discuss the topic. As long as people with any curiosity about the world, all of this is processes for the game. Books were posted. Someone else came up with an argument for me in an opinion that doesn't mean that there aren't negative effects on that. It doesn't mean we won't give up things we shouldn't give up. Part of what heartens me is like, we've got 12 to 16 years of schooling, you know, schooling to try and get some of this right. And if we do it right, AI accelerates some of that. And if we get to make choices as a society, now, will people make bad choices? Yes. And so I do worry about this, right? I'm thinking a lot about how we, what do we give up? How do we stay human? It's going to require effort, just like a lot of other things. And there is danger there. But I guess I feel like that feels like a big leap to, we're not going to think anymore. The AI will tell us what to do. We'll just obey its instructions. I don't think we'll stop thinking. I think it'll hurt thinking. Like the quality of thinking, critical thinking gets hurt. And I mean, look, you know this is as somebody who studies education. You talk to any college professor and they'll tell you, forget about AI. Forget the introduction and distractability of a phone, you know, that they'll say that, you know, the writing is abysmal these days. Every college professor is complaining about the writing being abysmal. So kids don't know how to write. And when I say write, I don't mean like, but I mean form an argument. And they'll say, like the first paragraph was fantastic. Second paragraph was fantastic. The third paragraph was fantastic. The problem is the paragraphs have nothing to do with each other because it's clear that they're like getting distracted in between paragraphs. I guess I would say, on one hand, you're right, but we've been very bad at education for a long time. The bad way to teach is stage on a stage where I go up and give a lecture, right? And a hundred people write things down. But we've done it for a couple thousand years because there's a lot of other constraints to make it the way we do work. There is a negative side, but like one of the things that really excites me is AI tutoring. We have some early evidence that it has big effects on learning, right? Like instead of me lecturing to a classroom and assuming the height of learning is, I lecture to what the upper part of the classroom, people who really knows if the middle, I, you know, I lecture to the person who doesn't know things as much. Personalized education is now an actual possibility. Like, yeah. It's a cure as well as a poison in this thing. And I think that it's worth paying attention to both. Like, if we don't change anything, the effects will be bad on education, right? But that implies that we're all going to sit down and just be like, I guess it's done. You know, like, yeah. And I don't, I think for the first time, I suppose a short form video where you had to do this very elaborate thing of like, we'll do TikToks for education and that never works. We actually have a tool that is a pretty good tutor that can talk to you at your level. They can make you get into an argument. That's part of why I do my classes. When we see schools adapting, right? First they put computers in all the schools and now they're still really taking them out. And it was partially because we just like come back to the human thing. It's completely like the thing that makes AI interesting is it understands, understands and quotes, right? For those who are just listening to this and making air quotes in my hands. It understands humans. It has theory of mind effectively. And that's what the other technology don't. Like, it can teach to your level. It can understand what you're confused by. It can help you make this interesting for you if your only interest is basketball or, you know, basket weaving. It can give you basketball and basket weaving analogies and problems. the Holy Grail of Education. And I think it's one thing to say, yeah, technologies have lit risk and everything else. I also think we undersell some of the positive impact that we can get from this. - The strong argument that you're making here is, and I don't know how many people have done this, which is where you use the talk function where you can actually have a conversation backwards and forwards with the AI as opposed to typing. And I think the case you're making is the idea and I, is that you can debate with someone at your level. So you're not explaining to somebody who's not at your level. You're not feeling dumb or trying to keep up with somebody who's more experienced or smarter than you, but rather that you can go backwards and forwards and learn the way you like to learn. And I've tried this where I'm having a debate or conversation, backwards and forwards, backwards and forwards, backwards and forwards, backwards and forwards. And I'll say things like, oh, wait, or is what you're telling me this? But I think this, that I think is really, really interesting to your point. - There's two other tricks there. One is the AI's sick of fandex. So if you're having a debate with it, it's going to agree with you. So you have to talk to act like a critic, right? Like you say, and then the second is, you want to take advantage of the meta piece also, the learning piece of saying, actually have a way to tell me what I'm doing wrong with my arguments. How can I be more persuasive? What patterns am I missing in discussion? Give me some examples of those patterns and how I could have used them. So again, pack the effort piece. If you're willing to do the lifting yourself of asking the questions, like everyone always says, they want to come to office hours and have this debate with professors. That's, most people don't come to office hours. You sit as a professor and you're waiting for somebody to come and debate to you in the great issues of the day and you sit alone in your office during the hour that people are allowed to come to you because they have other things to do. I think that we overestimate how this sort of shining city in a hill where it's sit down and debate and have these discussions. That's not how most things work. Now we have a tool that can do that. If you're interested, you can do that without having to come to my office hours. I want to double click on the two points you made because I think they're really valuable, which is remember that the AI is a sick event and you've got to tell it to criticize or critique and ask it to evaluate your thinking and help make your thinking stronger. Those are two brilliant, brilliant prompts that I think more of us should remember to improve the quality of our interaction with the technology. - We're talking early about AI and writing. A piece that was missing in your conversation, you're talking about user fact checking. It's very good at that. I would use it more for initial research. All of the AI models have a deep research mode that's quite good and will actually do research for you. But the thing you're also missing from that is, when I write something, I have the AI evaluate from different perspectives. So I will have the AI read it through as a reader who doesn't understand much about this topic and tell me what I need to change. Read this through as an expert who is out to get me on social media. Where would they nitpick my arguments? Am I being irresponsible anywhere? Did I hear my humor fall flat? So giving the AI, personas don't change the AI's ability. So you say your good at physics doesn't make a good at physics saying you're a physicist, but it doesn't make it talk like a physicist, right? Or parody of a physicist. Talk like a cynic, talk like a critic, talk like an naive person. You wouldn't get the answers you couldn't get without going to wide range of readers. Also true at entrepreneurship, by the way, get feedback from the AI and different personas about your idea. - This is very practical and very good. What are you actually afraid of? - I think we're in for a period of chaos, right? And let's say the Industrial Revolution works out like the last three did, like the AI revolution. - Yeah. - Living through it still sucks, right? Like Charles Dickens is basically just a story about how miserable the Industrial Revolution was, right? Like you have haves and have nots, you have social change. Even if everything works out fine, now we have better tools as a society, but I don't see a lot of action. You've led this conversation by saying that people either doom and gloom or everything is going to be great. I find policy making is in the same place right now. Either it's all going to work out great or we have to stop this whole thing. And neither of those are realistic outcomes. How do we help cushion people, if they're unsure? Turns out training programs for new jobs never really work. Is there something we could do better this time around to re-skill people? We're going to have negative effects on deep fakes are going to be everywhere. How do we deal with who we trust for information? There's a thousand little good and bad things that are going to be happening all at the same time. They're going to be very complicated. And they're going to get boiled down because of how social media and everything else works to either AI all bad, in which case you have a list of all these things that are a mix of real things and fake things about AI, water use or whatever it is. And it's going to be AI is bad or AI is great. And it is a thing. It's a technology and interacts with people. Technologies are neither good nor bad nor are they neutral. They have effects on our world. And I worry that we're not taking this seriously. The other thing I worry about is people don't know how good these systems are. They are better than you think. I have a doctorate. I'm a professor for a while. I publish journals like, the AI writes a pretty damn good academic paper now, not just a parody of an academic paper. If you give it a status set to work from. It is proving math at a level where you really need to be one of the best math professors in the world to know whether the system is right or wrong. It's often right at this point. It is doing really good images and marketing work that beats most marketers and studies that we have of this. It'd be like, these are really good systems. Their development is not slowing down. So we have to start thinking about what we want the world to look like rather than just assuming it's all either going to work out or not. And how much agency do we as the general population have or are we just the subjects? Are we just the pawns in this game between these three major companies, Microsoft, OpenAI and Anthropic? So I think that we have, there's two levels of agency we have. Level of agency number one is societal, right? Like there's a reason why people are floating in data center bands, right? Because they think that would be popular. The usual mechanism of policy making, of organizing, of writing letters to your congresspeople, those still work. The second is where I think there's even more agency. The ad labs are full of coders and they have found an unreasonably effective way of making a tool than mimics human thought. Like it's weird, the large language models work as well as they are. Like we know they work technically, but we don't know why this is so unreasonably good. Like how can it do poetry and offer, and interior decoration and write, and just kind of cash flow analysis and a pitch deck about the Gettysburg address. Like it shouldn't be able to do these things. It does all of this stuff. So we give them too much credit. They don't actually know much about how AI is useful in your field. Remember, there's a giant frontier. It's good at some stuff bad at some stuff. Your biggest source of agency is actually using it to positive use in your own job and work. Like a large part of what I post about is like, this is a way to help humans thrive with AI if we use it this way rather than just automating away human work. And I think our biggest sense of agency is, okay, you have access to these tools, Simon, how do you use that to expand your business to make sure that all the people who work for you have the focus of amazing folks that are overly smart. How do they do more than they did before? How do they do more satisfying jobs? There's a lot of agency there. And if you talk about it through your platforms, that changes things. And a lot of what I do is talk to executives and leaders of companies where I'm like, we have to show people how augmentation, how this can be used to make humans thrive, how can make your business thrive rather than the default plan of like, if I fire everyone in a place with AI, profits will be higher. Like that's the dangerous thing. So to me, the real agency right now is, let's find positive examples and there are tons of them out there, use them and build them to make AI make the world a better place and not worse. - I really appreciate this. Like you've given me, you've enriched how I can use this product. I'm gonna take you on. I'm gonna have the agency that you recommend. - I think this is a moment for transformation. - Yeah. - And I think people aren't being ambitious enough. Everyone's like, what if I record my, like it's not, how would you reach every one of your audience members separately if you could do that? And why didn't you just build it rather than waiting for it to happen? - Well, I'm not sure I'm gonna use it that way because I like the artist. I take pride in the fact that when somebody's talking to me that it is actually me, my opinions. - I don't think it's all about automating Simon, like creating a Simon clone. I never liked that. There's people who create Ethan bots. I don't think that's the way to do it. You're talking to a fake version of parody of yourself. I'm saying, what do I want people to accomplish in this world? Like how do I build a tool for everybody? - Yes, that I believe in. - That I believe in. - And like I said, I would do a Simon AI with a very specific application that lives alongside. But I like people knowing that when they see me and they think it's me, it really is me. And I agree. I mean, it's the same thing with my writing. I write all my own Twitter posts and everything else. And it's important to keep the muscles alive for nothing else. - Ethan, such a joy. Thank you so so much for taking the time. I really appreciate it. - Thank you. It's a pleasure. (dramatic music) As always, thanks for listening. And if you liked this episode, please do remember to subscribe to a bit of optimism wherever you enjoy listening to podcasts. And remember, new episodes drop every Tuesday. A bit of optimism is a production of the optimism company lovingly produced by our team, Lindsay Garbenius, Phoebe Bradford and Devon Johnson. And if you want more cool stuff or just to find out what I'm up to, visit SimonCinic.com. Until next time, take care of yourself. Take care of each other.