The AI Playbook Every Leader Needs: A Chat With Adam Brotman & Andy Sack

29:50Yeah. How, how is it kind of like, just like an impossible challenge to say, we'd like to move as fast and try to get to AGI, but also on safety. Is that, is that doable? You know, I, um, I think early on a number of people recognized that this was not technology. This was alien intelligence and the capability set of the tool that is powered by technology, I guess, and that the power of the tool conceivably represents an existential threat to humanity. And so I don't know what you do with that. Humans aren't great. Like the capitalist system is doing what it does, which is a bunch of very smart, hungry business people at probably six or eight companies are attracting capital and deploying it and going as fast as they can.

30:44One thing that might stop it, I guess, I'll say it as a statement, but I mean, as a question. So I had an obit in Washington Post yesterday about what I thought was kind of like a positive use of AI, right? Like as we talked about in your podcast, like how do you do more precise access to entrepreneurship with AI? And the comments, there was like 600 comments. And most of them didn't seem to have like read the piece. But you could just feel like an immense anger and immense fear, right? It was all about, yes, but it's going to polarize all wealth. Yes, it's going to like, it's just very worried.

31:20And then I see like the Duolingo people put something on LinkedIn where they are excited about something done with AI. And the comment track is just like, I'm canceling. This is just because you want to make more money. You don't care about people. there's like a lot of like what i says is like anger and deep fear and then i think there are people like us that do these podcasts where we talk about all this stuff and we're like yeah but it's awesome um do you think that that kind of like what i would see as brewing resistance or brewing fear or brewing kind of like um attention to kind of things that go wrong might in some way kind of create that kind of like break effect to all this?

32:06Or will that just be kind of like pushed to the side and people go like, let's just go, go, go. I think it'll be pushed to the side. I mean, it'll drew up and be chaos. And it'll be like, you know, I'm sure you listened to the Diary of CEO, that recent part. I thought that was an excellent podcast in which he talked about the five to 15 years of chaos and then tried to make the case for utopian i'm so i'm sort of on that like you know like we're in it it's the bus is left the station if you're not engaging with ai your business you're behind if you're not having a code or having a holy shit moment you're not paying attention and i think there's gonna be massive of resistance and chaos.

32:53And meanwhile, the technology will advance. Did you guys see there was a Harvard report that just came out where they studied the human evaluation of work? And it was the same underlying work. And then the question was whether an evaluator thought that it was human-generated or human plus AI-generated. And the worst evaluations were given to human and AI generated work by the least likely to adopt the AI. So, which is to say, the less likely someone is to adopt AI, the more harsh they are to be towards AI adopters. And in many cases, these are the middle managers and they were harshest, by the way, towards women and minorities.

33:36When they perceived that a woman was using AI, they were much harsher. When they perceived that a minority was using AI, they were using it much harsher. or sorry, they evaluated the same underlying output much more harshly and questioned the competence. They knew who was making the output. That was the experimental condition, same output, but then they told the evaluator, this is human only output by a man. This is human only output by a woman. This is human and AI output by a man, human and AI by a woman. And consistently, the least experienced people were who often are in positions of giving promotions, of approving work, et cetera, were most harsh towards AI.

34:16They were testing for a bias in this AI context, AI helping context or AI assisted context. Yeah. And it doesn't surprise me in the sense of that's been going on before AI and now with AI, to your point. But getting back to, I agree with Andy that I do think we can draw comparisons to the internet in some way so like when the internet really i mean we're old enough to remember all this stuff at least i am and i'm not you know the internet caused a lot of problems causes a lot of problems like today like social media and fraud and scams and um so there's this weird there's this weird thing that we've experienced and it's gonna it just gets more powerful right computers to internet to cloud mobile to now ai where like it's the same mixture of like a you can't put the genie back in the bottle the it it causes it there's real concerns right andy's exactly right like the whole time we were talking to folks we'd get done with the discussion and we'd say yeah there was really not a discussion of like safety um or like why are they building these things that they don't know what's going to happen and there just needs to be i mean talking about society you're talking about even just like displacement and disruption and there's not a ton of so that so in other words this industry is happening and these tools are out there and i you know i do think it's similar to the internet in the sense of like yeah there's there's a dark side to this and there's a there's problems and we need to be doing more do you feel that we this says very many we talk about safety we often talk about the foundational models um and then i'll give you a little backstory i was part of like the early social web also right and so i remember being at social food camp you know like where everybody who was building social platforms were and all the founders of companies that now then became well known were kind of hanging out and there was not a lot of discussion about safety there because we're taking pictures of our lunch and putting them you know in a feed and we were like what's the worst that can happen then obviously you know a whole generation's mental health kind of got washed washed away in the process when we talk about safety and and you talk to all these ceos obviously they can't change the foundational models but i wonder if there's something they can do to address the element of safety just in the way that they are conducting themselves with the use every day in their organizations?

36:59CEOs of the labs or CEOs of everyday companies? No, I don't have an answer for it. So like, you know, I'm not sure that there is, but I just want to, we talk about safety and then we kind of like look at these eight companies and go like, you should fix it. And then like in Europe, we look at the government saying, well, you should fix it. You know, like I wonder like if there is the introspective. Is there safety on the edge as opposed to the center? Yeah. What would we do there? Right. You know, is it our responsibility? We early asked the question, like should we basically just kind of find new people that if the old ones don't want to be upgraded is part of the safety is to say, well, actually, no, it's your responsibility to kind of like make sure that people get along on the ride.

37:38You know, like those kinds of questions. I mean, I just, I don't hear them that often. So it's a good question. I haven't thought about it. My knee jerk reaction to it is that really it is about the large language models. It's not about the user at the end, the CEO and the policies, et cetera. It's about the capability set of the set of tools. And really the debate is about open source versus closed. And where does ethics and safety fall in the responsibility? And you just today, because AI is such a profound step forward in terms of its capability set to solve problems that humans can't for the good.

38:22We might actually solve cancer. We might solve Alzheimer's. We might solve fusion. It's being talked about as a potential breakthrough in all of those domains. The underbelly of all of that is that technology could be used for lots of not well-intentioned things. And when you have a debate geopolitical debate about what is intention. And just because the U.S. says one thing in Germany, which are two countries that are closely aligned, it gets really complicated really quickly in the world. Um, and so like open source or closed source is really a challenging question. Um, I think that's actually one that I don't hear a lot of the U.S.

39:10discussing about my co-founder at Autos and co-author of the book, Nicholas. He was in Bhutan last week. and one of the questions you get there like from a group of high schoolers is you know so what do you use oh may I have deep seek like that's like the first question right and then obviously you know he's like you know what do you mean like I use open my eye um I wonder how much of like a lot of like the the world politics also will kind of like then be influenced by the question that you're just posing open source versus close but also just where does the yeah safety is just being tossed. It's not, it's not top of mind.

39:47It's not given the, given what's at stake, the prize that is perceived at stake, um, geopolitically and capital wise, it's safe to be damned. One thing that I would love to revisit is this question about both leadership and organizational structure in regards to the playbook. Um, you mentioned Sam, um, Um, and one of the things that I've wondered about is to what extent is this about AI first versus call it agility for lack of a better word. And the reason I ask that is I think AI first has certain connotation, but when I talk to my friends at open AI, for example, the hallmarks of their culture aren't, they are using AI for everything.

40:30Everyone's using AI for everything. So that's a non-negotiable as Brad Anderson said on the podcast recently, every person in every function every day. Okay, granted. But when I look at the way they are making decisions at OpenAI, it's about being clear about one-way versus two-way doors. You know, it's classic Amazon kind of thought process, right? They're clear on meetings must be valuable. They're clear there's no email. They do everything via Slack. There's literally zero email in the company, except with outsiders, right? And so to me, those aren't necessarily AI solutions. They're organizational decisions around agility, velocity, pushing decision-making down, etc.

41:14How much of this is AI catalyzing the necessity of agility versus AI bringing in a new concern, consideration, etc.? I mean, I think I understand your question. I'll try for a second, and Andy jump in, we wrestled with the title AI first because we were purposely trying to make, we asked the question, like, what does AI first even mean before we knew the answer? And then we ended up with an answer that it's about human in the middle. Like we, it's, it's augment, it's 10Xing, it's the human, it's the Iron Man suit for the human. It's still Tony Stark in the Iron Man suit. And at the end of the day, that's how I think of it.

41:58I think Andy and I think of it is like it's still it is about like you're you're sort of going through your day and now you have this like always on augmentation tool that's at your disposal you know you're going to use it a lot and you're going to actually rewire the way that you make decisions um and it's going to get weird because we talk about this in the book like when agents truly we don't really have we have agentic things that we do with ai now like even thinking models are somewhat agentic just on their face. And then you've got these things called agents, but that's a really misused and overly used term.

42:34And, but at some point there's going to be agents that are like trusted, autonomous, capable, maybe even super intelligent agents. And I don't think that that's a world that's 20 years away. I think it's, it's much closer than that. And, and so that's a different consideration, but for now we don't really have that. This is an augmentation, like an incredible augmentation tool and you can automate workflows and you can do things, but it's humans that are being augmented. So, and you know, that's a, I don't know if that fully answers your question, but that's how we see things for the next couple of years.

43:09But people need to, we do think that, I would recommend that people in the workforce and leaders in particular, like realize that their people probably should be using it more, but it's to achieve what the people are trying to achieve, right? It's still human powered. And the question is like, how much augmentation, how much 10Xing happens, you know, for now? I mean, I do think that that spectrum, it's like science fiction, like that spectrum is going to, it is already starting to change. Whereas like, how much do you still let the AI do things? How much do you rely on the AI? And I think it's human powered still.

43:51Well, I think there's a lot there, Adam, just in terms of decision-making, if you think about turns in an organization, you're my boss, I propose something to you, you've got to review it, you come back. If we're both augmented and I say, hey, Chad GPT, you know everything about my boss, Adam, you know how he makes decisions. Will you recast this email in a way that's most likely to be persuasive to him, right? And you have an AI that's trained to evaluate Jeremy's proposals. You can imagine if, even if we just cut the turns in half, we doubled decision velocity, right and so there even in a world that's where it's only humans being augmented to interact with each other i agree you see the organization accelerate dramatically that's right yeah andy and i talk about it as like you ever see that movie limitless with bradley cooper like it's like i still think that analogy holds like is everybody just has like a limit of us like but of everybody not just one character in the movie but like what happens when you end up making better decisions faster.

44:54And they say, you think about it, like in most organizations, our jobs are like, we're just like decision-making agents to mix them, to mix the metaphor. I was slightly, I think it's related. I think it's, it addresses this question, but I was watching some YouTube clip. I, you know, I hear, if you've ever heard of YouTube, it's this great new platform. Amazing. What's the URL? Well, on YouTube, it was that Tom Brady was on and he was like talking to a soccer team and he was describing how every day in practice he would do the two minute drill and he would be like, I'm going to treat this practice like it's the Super Bowl.

45:37And he would do the two minute drill and he'd like, you know, they'd score and he'd be like, he'd jump up and down and he got his whole team to treat practice as if it was, you know, that Super Bowl moment. And I think that that's very relevant to this conversation. That's brilliant. I absolutely agree. Folks don't really see all of the opportunities there are for snaps, as you're saying. Yes. Every email exchange is a snap. Are you treating it like a Super Bowl moment or are you just casting it off? Yeah. It'd be interesting. I've always wondered, this is kind of a tangent, but I've always wondered, what if everything I did in a course of the week, I forced myself to use AI for every single thing I did, which would be really weird because I don't know how you do that.

46:29But like, but it'd be interesting because I almost want to try it as an experiment. I have a feeling I would find myself in a weird but better place at the end of the week, which is really weird to say. But it, but you'd have to force yourself. It's completely unnatural to do that. And, and yet it would be me prompting and me iterating. So it's still me. Like I, you know, we're not, again, until the agents become autonomous, truly autonomous, like it's still you prompting and still you interacting and you thinking about how you want to react and how you want to receive the information. So I, you know, anyways, I think that, that Tom Brady thing is a good example.

47:13I do think that that. And I think that's the, like, it's interesting. We've ended on this podcast on a point, which is like, I think in some ways, if that concept, which sounds so weird and almost overly like artificial and inhuman and all that kind of stuff is the point we want to get across in the book that is like, you can choose not to do that or it's okay, but just know that if you did choose to do that, you would probably make better decisions faster all week. And if your whole organization was doing that on a compounded basis every day, every month, like where is your company going to be?

47:49Right. If that was really, we actually know the answer. Like there's been studies done by Harvard and BCG and Wharton that say, you're going to be like 50 % faster and 50 % higher quality at today's models. And that's like, that's insane. If you could get 10%, Michael Dell was on a podcast that Andy sent me. BG Squared. Yeah, BG Squared. And he was saying the same thing. He's like, look, I'll take 10%. If I can get 10 % higher quality and faster decision-making. He probably read the book. He probably read the book. For sure. I have one last question, and then we'll let you go because we know we're running out of time.

48:32But I know, Adam, that you convinced Andy to write a new book. But really what I'm interested in is what is the kind of like the next thing you guys are pondering about? Like what's the thing that you might not have the answer for, but where you just have an insane amount of interestingness? I have two areas that I'll, one is the impact of this massive investment and hyperscaling to the overall economy globally and specifically in the U.S. And that means what does really happen to labor industry by industry, job title by job title, consumer respect, like the impact is there's like a massive gold rush that's being poured into the economy.

49:19So there's that. That's one topic. The second topic is the fundamental changing. I mean, in many ways, your question about organizational structure, really fascinating to me. But what actually happens to the fabric of competition? I compare a lot of what the competition in business in general, I compare a lot of what's happened with AI to suddenly, at least in the US, you know, there's 20 to 40 tools for every industry, every application. And it's like there's competition has been unleashed in massive ways, which hurts margins. And yet, like, what happens as a result of that? So I think business fundamentally changed, and I'm fascinated by that.

50:06That's fascinating. Yeah, the only thing I'd add is, and Andy and I have also, we've been talking about that. We've also been talking about vibe coding. And it's interesting. It's, you know, Andre Karpathy sort of coined that term. It's been around for six months or whatever now. but there's something about what's happening with the coding abilities for non-technical people in the last month between lovable and tpt5's release in the highlighted vibe coding andy and i as we started to try vibe coding some things it actually opened our mind that like it's vibe coding it takes that problem that ai problem solving we just said to like another dimension that uh that's another thing we're fascinated by like pulling the thread on that to be like i think these these sort of science fiction ideas of like organizations not just like rolling their own enterprise software but like i'm not a software engineer but like taking a software engineering approach to non-software problems and actually creating code to sort of help you with those problems.

51:17If you can combine a business leader's mind with functional expertise with software development capabilities, suddenly like that's a really weird and interesting combination for propelling an organization forward. And Andy and I are like, we're trying to get our heads around that, which is like a whole other, it's like in the series three body problem. I don't know if you've ever watched those books and that movie but like the first series is about aliens you know maybe coming to earth or whatever but then if you hear about the second third books are about you're like oh my god like it it went in a really weird place around things and i think that's where the sequel to ai first is going to be probably if it was ever literally or figuratively written we're going to be about how organizations they don't just like change their org design they don't have to say i first but like they're just completely different animals in a way because of the capabilities of ai yeah There's so much.

52:11It's impossible to overstate. I mean, talk about governance headache or safety, right? But I mean, I told Henrik this story the other day. I was working with a company in Latin America and they had like 10 ideas. We started with, you know, I'm the idea guy, right? So you start with a thousand ideas, you get down to 10. And before lunch, which is like 3 p.m. there, you know, of course, I said, hey, back in the envelope calculation, how much time and budget Do you need to pull these ideas? Not scale across thousands of locations, just like prototype. And the mode response, any guesses? It's like 50K, eight weeks.

52:49That's what everybody said. Roughly 50K in eight weeks. While they were at lunch, me and my partner built one of the ideas. And they come back from lunch. We're like, did you mean like this? And you just see, it's like, there's the real time blowing of minds. and then the CIO going, oh no, now you've really screwed me because now they're going to expect. And you think about every manager who hears a team say it's going to take 10 weeks and they go, great. You know, if a manager doesn't know, they should say absolutely unacceptable. I'll give you 10 hours. Right. Then they keep talking about velocity.

53:23Right. Then they keep saying, great, 10 weeks. Let me know when you got a prototype. Right. Yeah, that's right, Jeremy. I know we're That's a great story. Yeah. You just said it's interesting because we, Andy and I, in the book AI first, we're all about like, wow, like the Iron Man suit, the 10X thing that Reid Hoffman talks about. This is better decisions faster. But what happens when the execution of the better decision is also at that speed? Like that's the part, like you're saying, that's the part that we're trying to get our head around and is the next chapter. Yeah, that's awesome. I think that's a great place to stop the pot.

53:59Really, really appreciate having you on. Okay, Jeremy, interesting conversation, huh? I thought so. You know, I'm still, my head's kind of spinning there at the end. We were talking about everybody's got a limitless pill. Yeah. And I think for all of the hype around agents and for all the hype around, you know, scaling, you know, productivity, stuff like that, the kind of thought exercise we went through at the end, right? Adam's my boss. I'm working for Adam. if I just am able to communicate better with him and if he's just better able to manage me, understand or just thinking about the decision velocity in that kind of paired relationship, if you extrapolate it, it doesn't take very much extrapolation to imagine.

54:43It's not just like a 10 % better organization. It's a totally different organization. I want to listen to the BG2 podcast with Michael Delks, it sounds like he was saying something similar. But to me, it's really profound to think about truly being AI first, truly being augmented. And after we hit pause on the recording, we're talking about maybe we do an AI first challenge where we and our listeners say, hey, all week long, we're going to invite AI into every part of our week. We don't even know what that means, really. But even just to shift the frame from, you know, what is AI a fit for to starting point is we're working with AI for everything and finding ways to do it and then reflecting on that later.

55:27I think it's a really powerful reframe, actually. So, yeah, I think it's interesting when, you know, when you suddenly figure out it breaks, you know, like I was, I'm not sure we talked about it, but like I was wearing one of those little dongles, you know, that records everything. and uh you know i brought over around the family and my wife looked at it and go like what's that and i'm like you know it's an AI device i'm testing i'm recording everything she's like no you're not and it started like a really interesting kind of conversation about like in her view for example even though this is just for my own use she thought that was worse than taking a picture and putting it on social like that like the the boundary that was broken there and you know for me like since i was just using it for myself you know like i'm like you know it's just me and my ai friend right so uh right so i think it's interesting well the interesting with that experiments is not only obviously what's going to yield and kind of like it's active way what you can use it for but also like where you find out where you definitely shouldn't use it um the thing that i really kind of like crystallized for me was i saw a shopify kind of um head of design or something like that basically says something to extend like don't ever show me like figma files or anything i only want to see prototypes i only want to see basically you where you mucked up a solution for something that you're debating with me and many other points and as and that was kind of like i think the the output from my brain of this conversation of like are we asking our organization to implement ai because we're trying to implement new technology or are we trying to really create a new type of behavior a sense of resourcefulness or a sense of entrepreneurship amongst the people where organizations have more agency and they are more kind of like they you know they go further in the chain of thinking about something and then executing on it and I think what was interesting with this kind of example like I don't want to see and I don't want to see a text I want to see a picture I don't want to see a picture I want to see a presentation I want to see a presentation you don't want to see a prototype.

57:35Prototyping is kind of like now a kind of ability that anybody can actually do. And that was just not the case even like a year ago. You know, this, this is going to, I think that I'm predicting folks are going to enjoy this conversation a lot because you don't, you don't know this Henry, but we're going to riff here for another minute or two. Because one thing I've been thinking about is this idea of low-res prototyping. And now you can actually high-res prototype as quickly as you can low-res prototype, right? It's easy. In Replit, you can build a working app as quickly as you could build a crappy, you know, construction paper pipe in your version, right?

58:10And at Stanford for years, we've been teaching students the merits and values of low resolution prototyping. One reason is speed, okay? And now you can get high resolution at the same speed, maybe even greater. The other thing which I would be fascinated to dig into, which I don't think is addressed by, call it the replets of the world, is your own investment in your solution. When you are working with crappy materials like construction paper, your ego doesn't get attached. Whenever something looks nice, it also changes the customer's perception or the user's perception, right? If it looks nice, I'm talking about colors and button placement.

58:50Whereas if it looks crappy, of course, I'm talking about the concept because you couldn't possibly want to launch this, right? And so all of a sudden we're kind of anchoring differently in these rapid prototyping tools, I think will have a different impact on the user, which probably is good because the more realistic or believable the decision, the higher quality of the data point. So I like that. But from a user or from a designer perspective or an innovator perspective, I think part of the challenge is it's really hard to throw away because it looks nice. And I'll give you one simple example.

59:20One thing I know to be true teaching hundreds of professionals now how to use tools like Replit is that sometimes the best thing to do is open a new window and drop the PRDN and just start over. Because for whatever reason, Replit went down a weird rabbit hole. But what I've noticed is the cognitive load on a human when they see all the work. Yeah, granted, it only took Replit 10 minutes to do this, but it feels like four weeks worth of work. trying to scrap that window feels like throwing away four weeks worth of work not 10 minutes okay i have two things so there's like there's like a weird attachment there anyway i so i'm just i'm kind of riffing hit you know but come on there's two no i'm i'm hitting the riff because i'm into it there's two thoughts one is there is this kind of like um the promiscuousness of making which is if you talk to people who are great at um using people on upwork what they do is they hire six people to do the same work and then they just take the best part and they continue with that person they're kind of like disposable in the use which is kind of like weird for most people because they paid somebody to do some work i think what you're saying there for me is quite profound and has helped me as an entrepreneur a lot it's like i'm pretty promiscuous when it comes to kind of like concept i start two or three things at the same time and if it doesn't work i don't dig in harder i basically go oh it didn't work and then i kind of go to the next thing i'm very inspired by my wife she used this term she's a medical biologist she used this term like it was non-viable like it's not emotional it just didn't work next thing right um the other thing which i think is interesting that you mentioned was that this thing what happens when suddenly you can prototype in high fidelity and you're making the point that it used to be easy for people to basically do something that was kind of shitty looking because then people would focus on the concept i think the flip side of what you're saying though is that now that everything looks like the final product the idea suddenly actually matters right so people now has vo3 and you see these amazing produced videos and you go like yeah but it's not funny like it's not interesting it didn't make me feel anything.

1:01:34It basically was like you prompted something that was not a good concept. Didn't have an insight. The idea is more important than ever. The idea is more important than ever. That is so fascinating also, right? And the same thing, a lot of the work that I do now where I do product work is that I used to do the same thing. You know, I remember my first, in the start of my career, I would use like balsamic mock-up or like I would mock up stuff like in these kind of like wireframe-y kind of ways. Now, you know, I use, you know, whatever, GBT-5 or Replit. and I basically built whatever I want and then I give it to an engineer and saying, okay, I know this is like not safe or anything, but like this is roughly what I was looking to do.

1:02:09And then obviously the velocity of then taking that into the code base is much faster than having to kind of explain it to somebody that had to explain it to something that didn't have to code it. But if it's not working, then it's very clear immediately because it just doesn't pop right there when you try to use it. mm-hmm yeah it's it's really you know we talked about a future in this episode and how the future is going to look different how organizations are going to look different when it's technically possible to run that many experiments in parallel you're going to have all sorts of other call it coordination challenges which maybe will be solved by ai but i think folks will only earn the right to have that kind of elevated, abstracted conversation about innovation if they are at the edge of capabilities.

1:02:59Meaning if they're still writing, as we talked with John Waldman about a few weeks ago, right? If they're still writing 20 page PRD docs and reading 20 page PRD docs, they are going to be a hundred times slower. And if they're only building one thing with Replit, they're going to be a hundred times worse than if they're building a hundred and they're happy to scrap the 99 for the one thing that they wouldn't have discovered had they not done a hundred parallel versions, right? But this is that the extrapolating to the exponential in a sense is a wild way to think about product development, innovation management.

1:03:34And it's now more possible than ever because we're no longer constrained. Going back to the beginning of this conversation, actually, we're no longer constrained by our intelligence. The reason you could not make 10 versions of the landing page is because it takes 10 times as much time. Now, it literally takes the same amount of time. To make 10 is to make one. The only limitation is, do you as the innovator know you should make 10? That's the only difference. I'll stop now because we'll soon make the commentary on the podcast. No, no. I mean, folks, hey, how about this? How about the code word?

1:04:10The secret code word this week is Mas Henrik. That's M-A-S-H-E-N-R-I-K. or, uh, what's, what's less, less Henrik. I don't know. I want to know whether people like more of this kind of conversation or less. So whatever the code word you want to use, that tells us whether you want to hear us riffing more or just like get back to the, get back to the guest, you jokers, let us know. That's awesome. As always, as always, thanks for listening to this episode of Beyond the Prompt. I am your host, Jeremy Utley, alongside my co-host Henrik Werdelin, and we are delighted to learn alongside you. Until next time, signing off from Copenhagen in La Honda, California.

1:04:57Bye.