How to make AI worth your time with Max Mullen | from WorkLife with Molly Graham

[00:00:04] Hi everyone, Sherelle here. Today we're sharing an episode of a podcast we think you'll love. It's been handpicked by the TED staff, and we think as a TED Tech listener, you'll come away with a fresh idea and a totally new perspective. Enjoy, and head to the link in the description for more.

[00:00:25] If you're like me, moments like this can feel exhausting. Your bosses are telling you to play around with AI, and it makes you want to punch them in the face. Someone told you to spend your Saturday setting up a new AI tool, and it makes you want to throw your computer across the room. I get it.

[00:00:44] Despite working in the tech industry, I am actually a late adopter. I did not run out and buy the first iPhone. I don't pick up every piece of software that Twitter or the venture capital ecosystem is hyping. I have this strongly held belief that great technology should be easy to use. Great products don't need a user manual. I often say that great technology should come to you. You shouldn't have to go to it.

[00:01:10] And what I mean by that is simple. Great products make it really obvious why they're going to make your life better. I've been around long enough to see a few real revolutions in tech, things like the internet, the smartphone, social media. But I have also lived through plenty of hype cycles that turned out to mostly be noise.

[00:01:32] And to be honest, when ChatGPT launched and suddenly every conversation in Silicon Valley turned into an AI conversation, I was skeptical. When venture capital websites rebranded overnight and every startup pitch had AI in the title, I was honestly a little jaded. There were two reasons. The first is that AI and automation research have been around for decades.

[00:01:58] Chatbots. Chatbots have been hyped before. Responsive AI has been a thing since Siri came out in 2011. And big tech has been automating all sorts of things from resume screening to user support for what feels like forever. So I genuinely did not understand what made this moment different.

[00:02:16] The other thing is that we had just come off a very loud, very expensive hype cycle around Web3 and crypto that just did not live up to its promise for most people. But then something shifted for me. I kept playing around with like basic tools that anyone can access. ChatGPT, Gemini, Cloud. And at first it felt like fancy Google. It was helpful, it was interesting, but it did not feel revolutionary.

[00:02:45] And then one day I tried something different. I uploaded a bunch of documents that I'd written in the past. Blog posts and essays and notes and emails. And I asked it to help me organize an idea for a new piece of writing. And suddenly I had this robot collaborator. It produced a really solid first draft of a blog post. Something that might have taken me hours. It did in minutes.

[00:03:12] Something that I had previously experimented with paying ghost writers to do. This robot did for 20 bucks. In one moment, it had done three things. It made my life massively easier. It saved me a bunch of time. And it replaced someone's job. That was the moment that everything changed for me. I couldn't help but become a believer.

[00:03:40] Not because the writing was perfect. And not because I want AI to replace everyone's jobs. But because I could suddenly see the shape of what this technology might become. Slowly, over time, I've come to the conclusion that AI is going to be as big and disruptive as the introduction of the internet. But I also think that we are very, very, very, very early in this cycle.

[00:04:06] And I think most people that are talking about AI don't know what the fuck they're talking about. So now I am on a quest. I want to understand what's real and what's hype. I don't want the VC hype machine. I don't want the scare tactics that say everyone is ahead and you're behind. I actually want the use cases. I want the real tangible changes that make a difference in my life.

[00:04:32] The stuff that will help me understand what this technology is actually going to do to our work and our lives. So I'm going to do what I do when I want to learn something. Every now and then, I'm going to spend an episode asking some very smart people some very dumb questions. And I'm going to make them explain this technology to me. And either they're going to convince me that it is worth spending my Saturdays learning this stuff,

[00:04:59] or I'm going to tell you that maybe it's too early for the rest of us. My goal is simple. I want to understand what the average person, not the engineer, not the venture capitalist, not the hyper-technical early adopter, what you and me should actually be doing right now. What's real, what's useful, and what's actually worth our Saturdays.

[00:05:26] I'm Molly Graham, and this is Work Life, where we untangle the messy human side of work. Today, we're going to talk to Max Mullen. Max is the co-founder of Instacart. He led product in the early days, building software that coordinated millions of real-world actions. Groceries, shoppers, deliveries, all moving through one system. He's also someone I trust enough to ask all the dumb questions.

[00:05:53] These days, he invests in very early-stage companies, often just ideas. Which means he sees a lot of new technology before most of us do. And yes, technically that makes him a venture capitalist, which might sound like exactly the kind of AI hype machine I just told you I'm trying to avoid. But the reason I like talking to Max is that he is not breathless about technology. He's a builder. He's practical.

[00:06:20] He's spent most of his career turning messy, real-world problems into software that actually works. And he's been using AI tools inside his work and his life long before most of us started playing with ChatGPT. Max is firmly in the camp that AI is going to reshape almost everything about how we work. So today, I want to push him on it. What does he actually see happening? Max Mullen, welcome to WorkLife.

[00:06:49] Thank you for having me, Molly. I'm glad you're here. I've been looking forward to this conversation. Me too. So I am curious just to start with like, Max, do you consider yourself an early adopter? I think so, yes. I mean, I do love trying products early and often. I mean, I early adopted Facebook when it first came out on college campuses. And then I tried it over many years. And I think through looking at the way it evolved as a product,

[00:07:17] I think I understood something about that company and about how people use social media. So when something new comes out, you're like, let's try it out. Yeah, I'm excited to try it. And as an investor, I want to kind of know what's going on with people and what interesting things they're trying out there in the world. Like not just early adopting each thing once, but I try to early adopt whole categories of things at a time and sort of say, okay, here's how four or five different people are thinking about the same thing.

[00:07:46] What did it teach you to be so early on Facebook and then watch it evolve? There's just something different about playing with a product once and then playing with it again in six months and then again in six months and seeing how it evolves, right? And like great products evolve pretty rapidly. It almost sounds like you like being like part of the story, watching a product grow and change.

[00:08:08] I think if you want to know what the frontier of technology is going to do next, you kind of have to be in today's moment, trying the riskiest, most interesting, most fringe things that you can. And those things often look a little bit weird and contrarian today. Okay.

[00:08:30] So I have a question for you because obviously today I want to talk about AI and this moment that we're in that has, you know, a lot of hype and a lot of conversation around it. Part of what happened for me with AI was there was this just massive hype cycle around crypto and Web3. And I actually like, it was so loud that I like tried to buy in at some point. Like I really try.

[00:08:53] And then I feel like it, in my opinion, didn't really deliver on this sort of like hype, though I'd love to hear your opinion. But then like AI followed so quickly after that that it actually made me jaded. Will you just like tell me a little bit about like your experience of like those two hype cycles? Yeah. And what's really interesting is there's a bit of an overlap between some of the people that were involved in each of those cycles and sort of fool me at once.

[00:09:21] I also didn't get too involved in crypto and Web3. And I look at any technology or any company through this lens of like, well, what is the problem that it really solves in a consumer's life if it's a consumer technology? And I could never find the problem that Web3 or crypto was going to solve for me. I don't mind my bank. I didn't have a problem sending money and I don't send money internationally.

[00:09:46] So it wasn't really a big problem that, you know, that the crypto solved for me in terms of the money transfer. And I thought blockchain as a technology was very interesting, but it was also so early. And then I also just saw a lot of bad behavior. And I said, I don't really want to be involved with that. And I don't think I fully understand it. And there are a lot of people that specialize in crypto. And so that'll just be an area that I just don't invest in, was how I thought about it. Interesting.

[00:10:13] So you actually like tried it, played around with it and then like opted out? Yeah, I followed Bitcoin very closely and still do. And, you know, Coinbase was in the same Y Combinator class as Instacart. And I thought it was fascinating, but I just didn't. It never for me solved a real problem. And meanwhile, there were other more interesting technologies that I think were solving real problems. Well, talk a little bit about with AI.

[00:10:43] Was there a moment that made it real for you where you personally realized that it was different than crypto? And what was that moment? Yeah, I mean, the first use case for me was writing. I could ask it to draft the first version of a blog post or really anything written in email. And it would get 80% of the way there, right? Which really does save you quite a bunch of time. And then there was kind of, from there, there were little moments since then until now where it got a little bit more useful.

[00:11:12] So now we can do research on the web. You remember this thing called deep research came out. And you could now ask it to go off for five minutes and think and get a bunch of websites and summarize them all. And then come back with like a report on a topic for you. And now you're saving not 20 minutes writing the first draft of a blog post, but you're maybe saving two hours of work that you otherwise would have had to do manually. And another interesting thing that's changed is you used to have to be good at prompting the AI.

[00:11:41] And you used to have to know all these tips and tricks. And in the last six or eight months, that has all gone away. Now you can be very lazy, actually, and give it just what you want. Ask it for just what you want. And they'll give you almost exactly what you expect. You've obviously been part of a lot of different phases in computing and just technology. What was it that like natural language conversation with a computer sort of made you think was possible that hadn't been possible before?

[00:12:12] Well, you have to zoom out a little bit. We used to use computers exclusively by clicking and pointing our mouse at, you know, applications that were fairly structured and did one thing that somebody spent a lot of time building. Like Microsoft Word or something? Yeah, or Excel. Yeah. Yeah. And you're doing all this work on your computer to eventually get an answer, correct answer in the work context. And then you got mobile apps, right? Which really made things a lot easier.

[00:12:41] You could tap and drag and zoom and it was with you all the time. And it had GPS and a bunch of new things were capable then. And you got the beginnings of voice as an input, right? With Siri and, you know, and the Google Android equivalent of that. And AI to me represents like a new paradigm for user experiences that I think people don't yet fully appreciate. And that is just the one where you use the language you know how to program in very well, which is the language you speak doesn't even have to be English.

[00:13:10] And you just tell the computer exactly what you want. And then you get the answer that you're ultimately trying to get to very, very quickly. And very importantly, this new paradigm of back and forth, you know, this personal chat assistant paradigm can ask you questions. So if you are, if you have some information in your brain that the computer needs in order to make a good decision for you, it'll just ask you. And I think that's very different and that's very interesting. And that's full of potential too.

[00:13:40] Yeah. You know, basically any problem that you could solve by tasking another smart human in the real world to do for you, you could imagine tasking a computer to do for you now. Because you can talk to it like a human. Because you can just talk to it and you don't need to know any special programming language in order to do that. This used to be the domain only of people classically trained in engineering. And now we are all basically computer programmers. Yeah.

[00:14:07] So like one of the arguments behind that, which is really interesting, is that AI actually makes the power of computing more accessible. And I think that's like some of the products that have come out are sort of all about like, all of a sudden the average person can actually access something that was previously really only accessible to someone that could code. Does that sound right to you? Yeah.

[00:14:37] I mean, I think it's, even for me, still not clear exactly all the different ways that I'll be able to use AI in my own life. But one of the ways that I think about it is just if you have some problem that you think an AI application might be able to solve, you can now just ask it to solve that problem. And you can see very quickly if it will work or won't. This is where it starts to get interesting because this technology is moving very, very fast.

[00:15:03] And what that means is that by the time you launch this episode of this podcast, this answer will be out of date. But AI can do all kinds of wonderful things for you. You know, I'll give you an example of something that I did. I'm going to take my family to Japan soon. And I don't know the first thing about exactly where to go or what to do. And so I asked one of my AI assistant apps to plan a full itinerary for me and my family.

[00:15:30] And I gave it a bunch of information that in my mind, I would have had to give a travel agent. Gave it the ages of my kids. I gave it the sort of things we like to do. I told it, I don't like to be overscheduled. I don't want to do more than one or two big things in a day. Like try to cluster things around the hotel that you think we should stay at so that it's like less intercity travel. And I gave it the flights, which I had already booked, which were into one city and out of another city. And I said, let's see what this can do.

[00:15:57] And a couple minutes later, it came back with a very compelling, dense itinerary for this eight-day Tokyo, Japan trip. Is this just out of curiosity, because you said AI assistants, is this literally you doing this in ChatGPT? Yeah. Like, yes? Well, I'm a bit crazy. So I put this prompt into ChatGPT. I put it into Google's Gemini, and I put it into Anthropics Cloud. And I got back all three answers. And then I went with the one that I thought was the best.

[00:16:23] Did it actually give you like a good itinerary that you're going to use? So that was very interesting. I didn't know if it was a good itinerary. I didn't know if it was plausible or if the places that it recommended were the right places. And so I asked a couple friends who had recently taken their families to Japan, and they said it was an incredible itinerary. So it took a little bit of, you know, a little bit of elbow grease to validate that this AI had magically developed kind of what a travel agent might have spent a week doing.

[00:16:53] But it turns out that it was a very good itinerary. And it is now the itinerary that we will be traveling on. Interestingly, though, at that point, I said, well, now I need to make a bunch of hotel bookings. And I need to find out some things that are not available on the websites of the hotels. So I need to call Japan. And so I ended up actually hiring a travel agent to book the hotels for me. And so this is this line, right? What can you do with AI and where does it stop? And a human has to get involved.

[00:17:20] And I think a lot of people kind of assume that AI can either do nothing or everything. But the reality is it's somewhere in the 80 or 90 percentile range. And you eventually or someone eventually has to get involved and do the last mile, at least today.

[00:17:50] You're kind of talking about one of my challenges with it. And I think a lot of people where it's like you start to ask it to do something, but you don't entirely know whether to trust the information. You know, how do you handle this new relationship with a computer where you're like, I know you can do these things, but are you actually good at them? Well, AI used to hallucinate a lot a couple years ago. What does that mean? When people say hallucinate, what does that mean? It means it makes stuff up.

[00:18:20] It will confidently state facts that it has no idea if they're true or not. And this is obviously a bug and not a feature. And so the AI labs went about doing what they call reinforcement learning. They went and gave it a bunch of examples of it doing this, and it gave it a bunch of examples of better responses. And they sort of worked this problem out of the system. And so in most cases, for most of the normal things you'd ask an AI to do, it rarely hallucinates today. And I think this is an interesting point, Molly,

[00:18:49] because people may have tried AI some amount of time ago, and it didn't work for their use case. Or it did something like egregious, something that you'd fire an employee for if they did it and lied to you. But they haven't tried it for that same thing again recently. And I have this thing I call the six-week rule, which is that if you tried to do something with AI more than six weeks ago, and it didn't work, forget about that. You have to try it again. Because every day, every month, the models are getting better.

[00:19:18] And features and apps that you're using AI through are getting better. And the thing that you couldn't do six weeks ago, I'm pretty sure is probably possible today. And if it doesn't work today, you should try again in six weeks. And AI is moving so quickly, we might have to reduce this to like the six-day rule. Like, again, things are happening so rapidly. In a week or two, some of the things we'll say on this podcast will be wrong because the new features have come out and new things are possible. I love that rule, first of all.

[00:19:46] I think it's such a good, I guess like an indicator of how fast this technology is growing and changing and getting better. But it's also kind of exhausting, like as a normal person to be like, I have to keep trying. Do you know what I mean? Like it's, I feel like a lot of people try it, to your point, like a lot of people tried it a year ago and then like wrote it off because it couldn't do what they wanted it to do.

[00:20:15] Why should I keep trying? Well, I think there's a couple of reasons. I mean, it can be really useful and save you a bunch of time in your personal life or in your job. I mean, it can do all of the mundane things that you're doing that take up time. It can do them usually instantly. You could send it an email that you got from your school and say, you know, help me put these things on my calendar. You could have it write a performance review of somebody that's really thoughtful and kind

[00:20:44] from just a few bullet points. You can really save time by using AI. And so that's one reason to use it. And the other thing that I'd give you as a reason why I think the average person can really get up to speed quickly is that all of us are learning on the fly. You and I are maybe one or two days of playing with AI away from being experts. And the half-life of that expertise is very short because again, there'll be new paradigms and new models that are coming out every month.

[00:21:14] And so it is a little bit exhausting to keep up, but there's very little work that you have to do to become an expert. Like the best experts at using AI, they learned a month or two ago. So nobody's too far ahead of you. That is really interesting to me because I also think that, you know, you talked about sort of like the history of computing and like that obviously didn't used to be true, right? To become like, to get a computer to do something complicated, you used to have to study for four years

[00:21:44] and get a CS degree. I mean, part of what you're saying is that both the ability to talk to a computer is more accessible and to get it to do things you want, but also that the expertise is more accessible. Yeah. And one of the things that has changed in the last couple of years is that some people, people like me or even people who are less of an early adopter, have used ChatGPT or their preferred AI assistant enough times that it's collected this memory

[00:22:13] of what you need help with and who you are and what you do for a living. And now it has this context, right? And when you ask it a question, you no longer need to brief it on all the details. You just ask it a very simple question and it gives you a much better answer because it knows you. And so I would, you know, I would encourage most people to pick one of these platforms and just stick with it. And then it'll get to know you over time and that'll make, you know, the process of prompting it and getting a great answer much easier.

[00:22:43] It's interesting because like when you, I know that like, I'm thinking of my mom here. Hi, mom. Like you say, I give it my data and it remembers things about me and it gets to know me and she says, that sounds scary and I don't want it to know. I don't want a computer to have all this information about me. Like, I'm curious, like, do you have a reaction to that kind of hesitancy? I totally understand that. And I started off skeptical

[00:23:12] and hesitant as well, but I started to build a little bit of trust with, particularly with ChatGPT. And I'll give you, you know, a personal use case. I got a bunch of labs back from my doctor and there's, you know, lots of numbers and different ranges and different units that they measure things in and I wanted it interpreted. And so I uploaded it to ChatGPT. This was a moment of trust. I said, you know, well, here we go. You know, it's now going to know like my blood work. And I asked it

[00:23:41] to just give me advice as though it was a medical professional. And it was able to kind of clearly break things down and, you know, it didn't obviously prescribe me any medications or tell me I was healthy or not healthy, but it gave me the questions that I should ask my doctor. And so then it made the, you know, phone call I had with my doctor much more productive so that we were sort of both looking at the same, at the same sort of hypothesis of what was going on. You know what? Pause there for a second. Let's just list like, if you, if somebody was like hesitant or reluctant,

[00:24:10] what are like the three places you would be like, start by trying this? Like, like you said the six week rule. So it's like, you kind of have to pick one or two places to start. What are like a couple of the places that you like commonly recommend people starting? Probably not your health data. I think you could, I think you could start with something really simple. Like, here's an email that I wrote. How could I have stated this in a clearer way? Or, here's a performance review that I just got. What are three things

[00:24:39] I could do tomorrow to become a better employee and get a better performance rating next time? And then I would even throw in one more entertaining one, which is, it's really fun to use AI with your kids. So I would always start by saying, I'm with my eight-year-old son. He has a science question and then I'll let him ask the question. And then we're going to get an answer that's appropriate for an eight-year-old. And then if we turn around and say, okay, now I want you to give me the adult answer, we'll go ahead and do that. So it's very flexible,

[00:25:09] very personalized, and you just have to ask it for what you want and it'll generally be able to do it. So he talks to the robots? Sometimes, when we let them. You know, and we haven't even gotten into the idea of vibe coding, Molly, but this idea that you can talk to a computer and it can build you a whole app customized for you. And so my eight-year-old, who again, can't spell, but basically just has an iPad, he can, using the dictation feature on the iPad, he can dictate

[00:25:38] what he wants his website to look like. And then an AI tool built him an entire website. And I essentially just sat there and showed him how to push the publish button and now he has a website. He has a website. What's his website about? He's built a website where he has a couple of videos that he's made, which we put out there, and then he made a couple of different games. Like you can play tic-tac-toe against him and we realized the tic-tac-toe game was too easy. And so my son

[00:26:08] told the AI to change it to let you win the first game, but to beat you every game after that. You know what's so funny? My exam in college for my CS course that I did really bad at was to make a tic-tac-toe game. This is like possibly a great example because of your point about the accessibility of expertise, right? I had to take a whole CS course in college, six months or whatever, and I was still bad at making a tic-tac-toe game. But vibe coding, what the hell is vibe coding, Max? Well, vibe coding

[00:26:37] is this interesting concept that has really started to get a lot of attention in the last year or so. You know, when you're computer programming, you're writing code and you're running code and you're making sure that it works and you're pretty thoughtfully executing a plan. And vibe coding is sort of this idea that the computer is sort of coding and you're just approving things. You're just approving things that it's doing and then at a certain point you're pushing the code onto a server and running it and making sure it works and sort of like

[00:27:06] a little bit lazy. But the power of it is that somebody that isn't professionally trained in engineering can create an application very, very quickly and we're starting to get to the point where the models that do coding for you don't make a lot of mistakes and they also work very, very quickly. So in like five minutes, literally in five or ten minutes, you could make a website, you could make a game, you could make an application that you might use at work to solve some problem that your company

[00:27:35] doesn't have a tool for yet. Like you can make very powerful things and you really don't have to know how to code. Do you really not? Because like I feel like you just used a lot of words like push server and pushing code. Can I literally do this and make something good just using words? You really can. My kid doesn't know how to spell and has a really great website that has a very entertaining series of games on it including Tic Tac Toe

[00:28:05] and it took 20 minutes. There's sort of a feeling of all this hype around AI and all this and I think employers are really pushing people to like spend your Saturday learning cloud code or cloud co-work or whatever the newest you know

[00:28:34] model is that came out and that can feel just honestly exhausting but like part of what I hear you saying is that might be worth it. I think a great company should be having you do this on your Monday and training you and giving you the tools. That's certainly our position at Instacart. We want people to be AI native and really have a lot of leverage through giving them great access to tools and then also encouraging them to use those tools and giving them great training. But yeah,

[00:29:04] I mean if you really want to go deep and you want to spend personal time on it I think that's fine. But again, you don't need to spend that much time to become pretty much an expert user of these AI tools. You really have to only think of a problem you want solved and just really be able to articulate all the parameters of what a good solution would look like. I want you to book me a trip to Japan that's eight days long. I want to arrive in Tokyo and I want to leave through Osaka. I want to take the bullet train to get from here to there and every day I want you to plan

[00:29:34] one fun activity that an eight and a five-year-old would enjoy and then recommend me a bunch of restaurants. And that's a task that AI now can do 99% of. So I'm curious there's sort of this narrative out in the world like AI is going to change everything. Where is that statement overreacting and where is it underreacting? Like what do you think people are being overly dramatic about and what do you think they're being sort of like

[00:30:02] not dramatic enough about? I think it can simultaneously be true that the technology of AI is going to advance at a really rapid rate like maybe exponentially advance. We might look back at this conversation at the end of this year and say wow we had no idea that it could do these other hundred things and I think that may happen. And at the same time the rate at which people change their own behavior or companies change

[00:30:32] their processes or their org charts could be slow could be lagging. And I think there's a consensus view these days that like just the technology we already have from AI could permeate through companies and through people's workflows for like another couple years. Right? We have plenty of capabilities in front of us to use. We're just not using them we're not leveraging them fast enough because behavior change is hard. So I think the technology will continue to develop really rapidly

[00:31:01] but people may take a little bit of extra time to adapt. Yeah. I think there's reluctance I think there's also fear you know there's a lot of like people are like I hear robots are going to be able to do everything for me and I hear you replacing your travel agent with a robot. What would you say to people that just actually have a lot of fear about and like are trying to think about how do I add value in a world where like robots and automation seem to be

[00:31:30] the main thing that doesn't sound very human. What would you say to people? I think there will be a role for human taste in everything that we do with AI. I think it's not yet at the point where it can kind of put the final touch on a piece of writing where it can kind of generate an image and have that be perfect right? There's still this role for humans to curate to first of all think of ideas to build in the first place

[00:32:00] and then to curate the output of an AI assistant and then to kind of do that last 5% of work manually. I still have not gotten my AI tools to fully write something that I don't have to edit at all. I'm still sitting there and editing it for the last hour. Same. I totally agree with you on that last mile still being human. Is that what else I mean what else to you that someone that's I mean you built a company Instacart that created

[00:32:29] a lot of jobs. You created a whole you were part of creating a whole economy like now we're talking about a world where it feels I think a lot of people are afraid their jobs are going to go away. I think that the thing to do in that situation when a piece of technology is like difficult to understand and difficult to predict where it's going to go is to learn a lot about it right? I mean that's what I always advocate people to do is to spend time with it and try to understand it and I think a couple things happen then

[00:32:59] first of all you become more valuable in your job because you're the one that can help answer the questions of how are we going to wield this new technology and then secondly you start to get to know its flaws and you realize this isn't superhuman right? It makes mistakes it really requires human oversight and I think that's the way it's going to be for some time and you really have to think

[00:33:46] us lots of leverage and you could still imagine a company having tons and tons of productive employees that are now even more productive as a result of embracing this technology so I don't subscribe to this idea that AI is just going to ruin every job I don't think that's going to

[00:34:16] things we love to consume from other humans because they're human like I want to buy pottery that's handmade and I want to meet the person who made it I want to understand the story behind an artist and why they painted a painting these are just not things that even though robots can do them better or faster or cheaper they're just not things I want to be done by robots and so I think art and certain crafts carpentry these are things that

[00:34:46] are bespoke and human in their nature that's one category of things that I don't think will change very much and then I think there's other things where you that's able to look at my form and spot me on heavier weights and really understand me and meet me and hold me

[00:35:37] okay that was such a fun conversation with Max I'm glad you got to meet him and I thought there were a few really great takeaways from that and you know I do just want to say again like all this talk around AI can be tiring but I think you know part of what I heard Max say is number one this technology is getting better so fast it is important to keep giving it a try so his six week rule of just like

[00:36:06] every six weeks it's like you're playing with a different product like it's like almost like they launched a whole new thing to play with I think if you treat it as if it is changing that fast it means that if you tried it and it failed at that it's worth trying again and I mean the most powerful point that he made I think is that this expertise is just not that far off that the thing that differentiates the

[00:36:36] people that are experts at AI from the people that are new and beginners is actually just the playing around the people that are willing to give these tools multiple chances that are playing with it every six weeks that are treating it

[00:37:14] like I was such a skeptic for so long I think I was so burnt out from previous hype cycles but pretty quickly once I found a use case that just clicked for me then I found the next use case and the next use case so it became easier to

[00:37:44] I really loved that point that actually becoming an expert is a few hours away from you just playing around you know and the last thing I'll just say that I really took away from this conversation is you know I think a lot of folks friends of mine relatives of mine find this whole thing overwhelming and find it exhausting and are sort of like why and is that really worth my time and

[00:38:13] I heard Max say for sure it's worth your time like I also heard him say though I mean sure you can spend your Saturday on it but actually it's worth your Monday do you know what I mean like this is a critical part of our jobs whether weekend this isn't a hobby this is a part of like our lives and that it can be a really invaluable companion you know that it can unlock things for

[00:38:43] you that previously were inaccessible and that's that's really cool that's exciting to imagine that we can create things that we previously couldn't have done and to imagine all that creativity out in the world that maybe we'll get to see and experience that's exciting to me I know it's also scary and hard but there's exciting things everything has two sides right it has the scary and hard side but it

[00:39:31] special thanks to if you like the show and want more come join the discussion on my sub stack lessons I'm Molly Graham thanks for listening