Title: Broke to the Frontier of AI
Source: https://youtu.be/gvufVSE6RE8
Generated: 2026-04-27T08:01:45.381Z
Note: Speaker labels are heuristic and may require edits.
[00:00:00] A: the beginning of social media all the all the companies had no idea what they're doing but then the kids did and the kids were just good at social media and then the company started hiring kids to like run social media it's kind of the same thing it's like this is a huge wave of new technology no one in the old world knows how to wield it uh the people that do are kind of like concentrated at the labs and then it's like if you pick it up and play with it you might become an expert at the next game we should have
[00:00:25] A: ideas and experiments at the ready for helping people ease the transition because it is likely that things move faster than people's ability to adapt and i'm talking to reed hoffman right co-founder of linkedin one of the earliest investors in open ai we talk for like five hours basically reed's just picking my brain about like this journey the same conversation we're having right now is like what have you learned in the last exploration of language models
[00:00:51] B: Being broke is bad,
[00:00:52] B: but being stupid is what's really bad.
[00:00:55] B: And what's really,
[00:00:55] B: really bad is being broke and stupid.
[00:01:00] C: Welcome to episode eight of Young, Smart, and Battling Broke. Today's guest is Parth Patel,
[00:01:06] C: a builder and thinker at the frontier of AI,
[00:01:09] C: repeatedly reinventing his career and perhaps the way we all work.
[00:01:14] C: He took an econ degree from UCLA and decided against the traditional path.
[00:01:18] C: He entered startup land and started stacking skill after skill.
[00:01:22] C: He joined Clubhouse in 2021 as a founding data scientist,
[00:01:26] C: contributing to its wild rise to a $4 billion valuation.
[00:01:30] D: Facebook has taken bold moves into two new product categories.
[00:01:33] D: It's taking on Clubhouse with Facebook live audio rooms.
[00:01:36] C: When Clubhouse faced post-pandemic headwinds and had mass layoffs,
[00:01:40] C: he saw it as an opportunity to go all in on his hobby projects.
[00:01:44] C: He spent every cent he had made,
[00:01:46] C: including his 401k.
[00:01:48] C: And every waking hour to better understand the power of LLMs.
[00:01:53] C: A year later, he was appointed by Reid Hoffman,
[00:01:55] C: LinkedIn's co-founder and early OpenAI investor,
[00:01:59] C: to lead frontier AI projects.
[00:02:01] E: This new world of AI avatars will certainly make a lot of people uncomfortable and by the way will certainly have some foot faults and errors but again what might we be able to make?
[00:02:10] C: And he's as knowledgeable about current model capabilities as anyone.
[00:02:14] C: you one.
[00:02:14] C: We get into his unbelievable bet on himself,
[00:02:16] C: the AI future he sees,
[00:02:18] C: and what this means for young people and careers.
[00:02:21] C: I hope you enjoy our conversation as much as I did.
[00:02:23] C: Thank you.
[00:02:25] C: Parth, I'm so excited to have you on, man. It's genuinely been...
[00:02:29] C: In the last two weeks occupying my brain,
[00:02:32] C: how many questions I could ask you to just like fully quench my AI curiosity thirst, man.
[00:02:38] C: Put very simply,
[00:02:40] C: you are one of the most experienced and esteemed vibe coders. But that's like the most simple, dumb explanation of what you do.
[00:02:48] C: So if you could just start with telling me what you're currently doing, Parth,
[00:02:50] A: Yeah
[00:02:50] C: that'd be wonderful.
[00:02:52] A: Yeah. Yeah. One of the first vibe coders vibe coding from before vibe coding was a thing.
[00:02:56] C: Mm-hmm.
[00:02:58] A: Yeah, that's definitely.
[00:02:59] A: A good amount of my day is generating code with language models.
[00:03:03] A: I don't say vibe coding anymore.
[00:03:06] A: I think because there's this like stigma around vibe coding
[00:03:08] B: Yeah.
[00:03:09] A: that it's not performant, that it's a little bit like it's more like.
[00:03:12] A: like it's a it's a more casual form of programming Mm um
[00:03:15] C: -hmm.
[00:03:15] A: and i'm and i have friends that like we were kind of like okay what other work like like it's like if vibe coding is talking to ai smoke and weed and like sitting back while it works then like what is the version of programming where you fire off seven or eight more of these agents on other problems other projects in parallel and like because that doesn't feel like vibe coding it's like if this thing is going to work for 45 minutes on my behalf
[00:03:39] A: I could either sit back, I could go to the beach,
[00:03:41] A: or I could fire off another one.
[00:03:43] A: And now it's like, why have one when you could have 20,
[00:03:45] A: 30, and then the bottlenecks, the bottlenecks are different.
[00:03:48] A: I think when you get good at one, when you get good at making one thing with AI,
[00:03:51] A: then it's like, it's a question of like,
[00:03:53] A: do you turn that into like your break time or you turn it into like,
[00:03:56] A: okay, well, let's hit the gas pedal and see how far this goes.
[00:03:59] A: I have a very obsessive personality and I'm a gamer. So I kind of see this as like.
[00:04:05] A: why talk to one ai when you could talk to like a fleet and
[00:04:07] D: Hmm.
[00:04:08] A: like have that kind of working um in the background on your behalf that's like my kind of like longer term kind of objective with working with ai and but it's been a it's been like a at this point now like four year journey for like i guess like since like three we're in 2025 so 2022 november so it's like three three year journey since like chat gpt and uh
[00:04:33] A: all as the scaling paradigm i mean that's where i'm gonna ramble a lot so you're gonna have to try to keep me I'm on excited
[00:04:38] E: on for it.
[00:04:38] A: yeah you're gonna have to bring me back to the points you want you hope that i make but basically like um when chat gpt came out i was working at a startup i was working on clubhouse and i could tell that like oh wow like this is like way better than c3po
[00:04:54] A: and c3po is like fairly advanced technology like you can talk to this thing it it can translate every language it can also like use a computer if you allow it to um at the time you had to copy paste what you were doing into chat gpt and then be like oh make this and then you write a program then you copy paste that back into your ide and i didn't even know how to set up my environment so i was like hey teach me how to run this program it's like okay here's how you run it i was like well i don't have python it's like here's how you install python so you can just self
[00:05:20] A: teach yourself every single step up until the process of vibe coding and then vibe coding was coined at the beginning of this year but a lot of us have been coding with llms since the beginning i think the first commercial application of llms was github copilot Hmm and that came out before chat gpt and for a lot of people at least engineers first they were like oh my god like this yes they can finish the next block of code
[00:05:43] A: But if you extrapolate that out,
[00:05:45] A: it's like, can it build the entire program?
[00:05:46] A: Can it write a multi file program?
[00:05:48] A: Can it build Facebook one day?
[00:05:50] A: Like those questions of like,
[00:05:52] A: if you keep scaling this,
[00:05:54] A: where does that stop?
[00:05:55] A: And then for me, it's like, it's like,
[00:05:57] A: okay,
[00:05:57] A: well,
[00:05:58] A: let's get good at it while it barely works.
[00:05:59] A: and then see what happens and then inevitably every eight months there's some like huge leap in the model capabilities and then everything that you were doing that barely worked then either comes online or is like massively amplified um
[00:06:11] B: Hmm.
[00:06:11] A: and so that and that pattern just keeps playing out playing out so like what you were doing in chat gpt is now baked into the coding environment what you're doing in the coding environment with models that had a context window of like 1.5 pages just three years ago now they have a context window of like
[00:06:27] A: like 450 page books so
[00:06:29] C: Mm-hmm.
[00:06:29] A: like they go from like intern to like competent co-worker
[00:06:33] C: To
[00:06:33] A: yeah
[00:06:34] C: a one prompt home run.
[00:06:35] A: to
[00:06:35] C: Yeah.
[00:06:36] A: zero shotting very complex problems that would have otherwise taken you three weeks and watching that like watching the model progression and working with it so it's like you could call it vibe coding but like getting to see front row like interacting with a model as it gets better more quickly than any person you've ever worked with
[00:06:55] A: has been just like a very trippy couple years also just asking it dumb questions and be like hey yo like strapping yourself to this exponential curve and seeing what you can learn um me being not a like a full not a software engineer three years ago and i don't say i'm a software engineer but other people call me a software engineer now and i do spend most of my day software engineering so it's like it's not like the title is i think i think of titles as like kind of bs but like
[00:07:22] A: when other people give you a title and then that kind of means something and then like you could because you've earned it through the way you act and things that you're able to make and i think there's like so people say vibe coder and i think that like i like that word i think a lot of people should be vibe coding i think everyone is going to be vibe coding in some capacity even if they don't know it but the like there's this other version of this which is like what might the top one percent vibe coder look like how might they interact with the computer
[00:07:50] D: Mm
[00:07:50] A: how
[00:07:50] D: hmm.
[00:07:50] A: because that's if it's anything like playing video games uh the top one percent like strategy gamer is never going to drop a game to someone that's in the 98th percentile because the gap between the top one percent like just the top 200 players in a particular video game the way they play the game the level of depth that they have in thinking about that game is so different from the guy that's at the 95th percentile
[00:08:11] A: or like you know near the top but not at the absolute top and the way they work the way they think about the game is different so i think about like yeah vibe coding might be like the everyday person's experience with coding agents and even now it's like we're still so early that most people are not interacting with coding agents or they don't realize they are and then i think about like some of my friends um adam silverman
[00:08:35] A: and like the agency ai team in sf they were like we should call it we should call it hyper engineering like this other version like what might that like power user version of programming with language models be called we haven't named it yet i mean hyper engineering is one name i like that name because like what's the version of this where you lean in and like you're like i need more um oh
[00:08:53] E: I really hope hyperengineering does not become a nice LinkedIn buzzword.
[00:08:56] E: That'd
[00:08:56] A: my god dude you
[00:08:57] E: be so gnarly.
[00:08:57] A: know the moment it goes a term
[00:08:59] A: both mainstream i'm just like okay well i can't use this anymore because there's no longer you know you say agents and that three years later everyone and their mom is talking about
[00:09:06] B: agents Yeah.
[00:09:07] A: so it's like okay why don't we just not say the word agent because that's the only way you can stand out right so like i'm like working with a startup and they're building an agent but one of the main things is like the founder and i were talking about it was like
[00:09:18] A: what if we just don't say the word agent
[00:09:19] C: Yeah
[00:09:19] A: and then like that ends up being part of the like way we stand out because everyone's going to hear agent and it's like sounds like the same the same thing and i think there's a lot of fatigue there like trying to not sound like i think that's another thing that's maybe one of my character traits is
[00:09:34] A: like i'm like anti-establishment or anti-mainstream to a fault like i like i'm an android user like if the moment everyone is doing something i'm like all right like time for me to head out like time for me to find the next interesting thing um so that that's that's definitely part of my personality and it shows up in like how i make decisions like every one of my friends was becoming a management consultant and i was like well you guys all want to do that because none of you know what you want to actually do
[00:09:59] A: I actually know what I want to do, which is I want to work at a startup and no one was like
[00:10:03] A: go become a management consultant then you can go into startup like that didn't but me coming from the bay area i i could see that that was clear to me also even in high school all my all my friends wanted to become engineers i was like well someone should do something other than engineering if we're all going to potentially work together um so then i was like oh i'll go become a business
[00:10:21] D: I'll
[00:10:21] A: guy yeah
[00:10:21] D: go learn how to talk to people.
[00:10:22] A: yeah i'll go like yeah exactly
[00:10:23] D: I'll
[00:10:23] A: yeah
[00:10:23] D: be that guy.
[00:10:24] A: i'll be the business guy i'll go figure out how finance works that was me in high school um and then i would bring that comp sci skill set to the finance
[00:10:32] A: finance space and
[00:10:32] E: Mm-hmm.
[00:10:33] A: so like i was the most automated of all the finance bros that you could ever imagine and so but then that lens of like of like like being good at a computer and applying that computer skill set to a problem space that doesn't have very many people that are good at computers ends up being how i stand out in that space um but
[00:10:52] A: Yeah, I mean, we're kind of rambling already.
[00:10:54] A: So let's,
[00:10:54] F: Yeah,
[00:10:55] A: yeah,
[00:10:55] F: I'll try. I'll try my best
[00:10:56] A: yeah,
[00:10:56] F: to reel us.
[00:10:56] A: yeah,
[00:10:56] F: So about three years ago,
[00:10:58] F: when you did start this kind of, yeah,
[00:11:01] F: it doesn't sound like vibe coding what you did start this journey as. It definitely sounds much more like hyper engineering in past stories. And when we've talked about it,
[00:11:08] F: you were pulling 14 hour days sprinting on trying to understand everything you could about this new technology.
[00:11:14] F: Could you walk me through those early days and what kind of sparked that journey?
[00:11:18] A: Yeah.
[00:11:19] A: So ChatGPT comes out in November of 2022.
[00:11:22] F: Mm-hmm.
[00:11:22] A: And I was working at Clubhouse and there were people in the app talking about this became instantly the most popular topic in the app and almost every single country in every single language in the app, like ChatGPT was in the title of the room.
[00:11:35] A: And you would just join the room and people would be talking about how they're using ChatGPT.
[00:11:39] A: and i talked to a lot of users that was like my thing on clubhouse was like i just i gotta make friends with people it's like you can talk to people all over the planet so you now you get to like meet people that you would never meet in the real world otherwise thanks to this app they like reduce the distance between any two people two people on the planet down to a conversation and anyone can discover that conversation and join that conversation
[00:11:59] A: that's magical it's a magic that will be rediscovered by another platform in the future but we had it and I was able to just go into rooms and ask people how they were using ChatGPT and there were so many moments everyone is using a different way like photographers artists etc like and then I had one moment where I entered a room with it was a it was a group of farmers from my home state of Maharashtra in India
[00:12:25] A: And they were talking about using ChatGPT to help plan their crop cycles.
[00:12:31] A: And I was just like, are you serious?
[00:12:34] A: Like, that means this is a computer.
[00:12:36] A: Like, for all intents and purposes,
[00:12:38] A: we finally have something that's like.
[00:12:41] A: Jarvis like but like anyone can have it's not just for the billionaire main guy and it's not just for Tony Stark yeah
[00:12:47] B: Protagonist, yeah.
[00:12:47] A: it's not just for like one guy using Jarvis and on the planet but like now we have this the beginning and it's like sure I was like oh man they're using it for that it's not very good yet
[00:12:55] A: but that means it must get really good we have to make it much better it's not it's general purpose technology which is why everyone can use it and then everyone's discovering the use cases right like they're using it in a way that i could never have imagined i'm like over here people are like oh it doesn't write my emails well i'm like this feels like a skill issue
[00:13:12] A: like you are applying this in a way that is like low leverage meanwhile other people may apply it in a way that like changes their entire like the way they the way they live and that's why it's important to talk to people because like you're like
[00:13:24] A: like you're like okay i'm not even seeing one percent like you tip of the iceberg on like possible use cases of the technology especially because the technology is a general technology it's not like this is for business this is for life this is for art only it's like actually the intersection of all it's it's it's like these models that have been trained on all of human knowledge are now a representation of the collective intelligence of the planet of like of all of humanity including people that died
[00:13:54] A: that's amazing now you can talk to these like ghosts you can you can construct these ghosts and talk to them and draw from the model insights that you would not be able to draw from the people that live near you and I think about that a lot right so like I go to clubhouse to answer questions about things that other industries and like other parts of the planet I try to understand like you meet people to understand something that you wouldn't otherwise have in your own neighborhood
[00:14:20] A: and now the model is a kind of like artifact that we can also call on to answer questions that it's like oh i don't have a tutor for this but now i don't need one like i'm not i'm not at zero for not having someone in my neighborhood that doesn't know this
[00:14:33] C: Yeah.
[00:14:33] A: i can at least start by talking to the model and that is a huge unlock so this is like a realization over november to march
[00:14:42] A: And I knew people were using it for programming and some of my teammates left Clubhouse to go to OpenAI in the months leading up to ChatGPT. So I was like, oh my God, when ChatGPT came out, I was like, that makes sense. Like Clubhouse is a natural language data set. It's like people meeting all over the internet and talking to each other.
[00:14:57] A: And now you have language models,
[00:14:58] A: which is.
[00:14:59] A: kind of like in the same space it's like the conversations we have language models it's a conversational experience it speaks every single language and um it just kind of brings us together in a different um way so it made sense that people who worked on social audio products ended up working in frontier labs and making these products like that makes sense in retrospect but
[00:15:19] B: Mm-hmm.
[00:15:20] A: also um the model just starts getting really good really quickly so march 14th of 2023
[00:15:28] A: they dropped GPT-4 and GPT-4 is like it's a multimodal model chat GPT had a context window of like 4,000 tokens at the time then there was a 3.5 turbo which had 16,000 context window and GPT-4 comes out and it's like 32,000 context window and I'm like well we are going very quickly like the the the if you think of the context window as like
[00:15:51] A: the conversational bandwidth of the model or like the the like the model's ram it's like how much can it work with in one prompt like that is quickly it's just doubling multiple times and i thought okay my dad worked on semiconductors his entire life and i was like yo this thing went from like barely holding together a page of information to like working with multiple pages at the same time plus getting vision plus getting like you
[00:16:16] A: really good at programming and in the span of months and my dad was like oh this reminds me of computers right like the
[00:16:22] C: The
[00:16:22] A: transistors yeah
[00:16:23] C: Moore's Law,
[00:16:23] A: 
[00:16:23] C: yeah.
[00:16:23] A: Moore's law exactly like this is gonna get better twice as good and you're not gonna think of how to use it every single time like you're not thinking about how to make use of all the increased capabilities as quickly as the capabilities come online and um so GPT-4 32k context and that was like a a version that wasn't even available I was like I was using the
[00:16:44] A: the smaller gpt4 and i was like man if they release 32k context in december i'll name my firstborn child gpt4 like now because i had i had co-pilot systems that i was building at this point i was building chatbots connecting them to tools and um they were it's like i could tell it to do one thing at a time and it would go do that thing like analyze this
[00:17:03] A: search the web write a file but it would be like one turn versus like one action of like competent work and then you're like okay well can you get it to work by itself if you tell it to write a plan and then to just keep iterating on that plan that was working and then it was like well actually like think step by step the all the prompting techniques were like oh you should also give these things to the co-pilots they get better at doing the job like think if you allow it to think about the problem and if you allow it to write code it gets way better at solving the problem and like okay you're you're
[00:17:32] A: these techniques are coming online but then the model's capability also just increases and then all those techniques start like flooding or like you realize you're like every day 14 hours a day you're working with this and you're still not discovering like the full range of its power and then um we had layoffs at clubhouse and i we had the nice thing was like we got to keep our laptop and we got four months of severance yeah
[00:17:57] D: Wonderful.
[00:17:57] A: so i'm sitting there and i'm like
[00:17:59] A: well this is like this is perfect now i'm not moonlighting this after work i can actually just spend all my time all my waking energy for the next 120 days i'm just gonna sit here and talk to this model and figure out what it can't do what what is it not useful for where does it fall short like i'm just gonna do that and then at the end of the 120 days then i can decide whether to go get a regular job again
[00:18:22] A: or um you know like yeah
[00:18:25] B: You want to marry the AI?
[00:18:26] A: it's like okay no it's like it's like either i figure out how to use this and it's like a useful skill or i go back to my old like job and try to get a regular job yeah and uh
[00:18:36] A: and and it was interesting because i met a guy on clubhouse and he was like he was the guy when gpt4 came out that was like you should be programming with this so then i was like okay no more excuses like i've been dodging programming my whole life and then i was like well now this thing is just going to write the code like all of a sudden everything became easier so then i just sit there i was like we're just going to code with this and of course i'm starting from zero like not completely zero i learned java in high school
[00:18:58] C: Mm
[00:18:58] A: but
[00:18:58] C: -hmm.
[00:18:59] A: it was so much it was so much easier than anything i'd ever done in programming like everything that used to take six months could be done in like three prompts and i was like okay that that's a crazy like you could tell it to you know teach me how to clone my voice it writes the program then you get the program running you're like two prompts and you did something that if you were to try to build that from scratch would have taken a team but because you're just leaning on the model to surface all the solved versions
[00:19:24] A: of the different parts of this problem you're like accelerated through a lot of everything that's been done you can like quickly go through because the model is really good at stuff that's already been done of course there's a frontier now of like how good is the model at things that no one's ever done
[00:19:37] D: Hmm.
[00:19:37] A: and that's a frontier but that doesn't mean that you can't just use it for everything we know that's like not an impossible problem that's like doesn't like how many people are working on problems that actually require novel physics versus like solving a problem that
[00:19:50] A: someone else has probably solved before the model being trained on everything that we've already done makes it so useful for just like copy pasting solutions from like existing other spaces so
[00:19:58] E: Mm-hmm.
[00:19:59] A: they're already useful and i was like you know you could if you froze improvement at 32k gp4 i could still use this to like explore mars like i could still use this and it still changes the world but then if you tell me you're gonna like 100x compute you're gonna 100x everything and i'm like okay well then
[00:20:18] A: a lot of these rough edges are just going to be like solved by scale and then a lot of other techniques are going to come online we're just going to bootstrap past a lot of these existing limitations and sure enough by december they released i was expecting 32k gpt4 in 2023
[00:20:34] A: uh november and they released 128k context gpd4 and i was like okay that's 50 so this is like so much bigger than i thought i was gonna get
[00:20:43] F: And where is this in terms of your severance?
[00:20:45] A: oh that was i am already burned
[00:20:47] F: through Okay,
[00:20:47] A: my severance
[00:20:48] F: so you hit your four months, you hit your almost 1,000 hours of AI coding,
[00:20:51] A: yeah yeah yeah
[00:20:52] F: and
[00:20:52] A: i because
[00:20:52] F: what was the mindset when you hit that four-month mark?
[00:20:55] A: okay so the good thing about like starting severance i was like i'm just gonna
[00:20:59] A: do this every day for 14 hours a day like sit here talk to the model figure out what like what this is for and then you know i'm gonna do that for 120 days the nice thing is then um and i'm just gonna do it on the weekends too because like when you are jobless like every day is the same right the weekend is only just a day that some other people are down to hang out and drink it's like it's like but like your social construct start falling apart
[00:21:25] A: especially when all you do is sit there and talk to AI yeah
[00:21:28] B: Yeah, there's a lot of way that those four months could have ended.
[00:21:31] A: it could be a lot
[00:21:32] B: I
[00:21:32] A: of you
[00:21:32] B: just imagine you hoodie in the basement just working
[00:21:34] A: that is true yeah literally true it's just like me sitting there
[00:21:37] B: EDM in the background.
[00:21:38] A: yeah blasting blasting music putting on mixes and then like the cats are just like what is he doing and then every once in a while just so then I run out of severance and I'm like
[00:21:50] A: I feel like I have more questions than answers.
[00:21:52] B: Mm-hmm.
[00:21:53] A: And I had friends that were seeing me because I just show my I had my friends from like previous jobs and I was like, guys,
[00:22:00] A: here's what I'm learning working with these models.
[00:22:03] A: This is how it changes definitely like data analytics,
[00:22:06] A: which is my bread and butter my like superpower I was like this thing totally changes data science and data analytics because instead of us writing SQL queries by hand building dashboards by hand you prompt the model to do both of those things and then that means that like I feel more like
[00:22:20] A: it it used to be the ceo asked me and then i go build the analysis but now i sit there and tell the agent to do the analysis so it's like i'm moving up an abstraction layer and then also it's like instead of relying on an engineered instrument the thing and like put the analytics into the code i could just be like add instrument this so that we can you know add logging instrument this
[00:22:40] A: so like i am both the engineer that implements the analytics code and the data engineer that structures the code that was previously other people in adjacent roles to me
[00:22:47] B: Mm
[00:22:47] A: but
[00:22:48] B: -hmm.
[00:22:48] A: now it's like i get to expand into all of them so i become the ceo and the data engineer and the data analyst and the the like engineer to some degree and so it's an expansion of the role i'm seeing so like even if i go back to data analytics this is how i'm going to do it but then you go back to like a bunch of companies like they used to work for and you're like
[00:23:07] A: you guys playing with language models they're like no we banned it it's like all right you guys are gonna get you guys are gonna get rolled then like like you you banned it and i'm over here seeing how like i can't imagine playing the game without this now without the in you play this game without these technologies and like you will be you will lose to someone that plays the game with these technologies um at least like just the old game is done
[00:23:32] A: but then a lot of people just weren't um they just weren't at that moment it made sense because they had the day job they had their obligations they hadn't you don't have three months to spend talking to ai being like oh shit this changes everything but then the people that were my friends were like yeah you have definitely discovered like the future of our roles um i feel like you should just keep doing this so then i was like hey this isn't insane like if the smartest people i know are just like you'll keep turning over these leaves turn over these cards like because they
[00:23:59] A: benefit from knowing how their own role changes then i was like okay cool like i think there's more to learn here um and also i thought like can't go to school they don't teach this to school like the students would find students from ucla would find me at a hackathon and they'd be like
[00:24:15] A: you want to just give like an underground lecture at UCLA we'll just take a room we'll give you you could plug in your laptop and just tell us what you think is going to happen and I was like absolutely dude like there's no one who's going to update the curriculum as quickly as now there are my friends are like working with UCLA to like use agents to update the curriculum but over then it's like I was like I'm just going to show up vibe code the deck in the ride over there and then like explain what we're doing with these technologies by using the technology
[00:24:42] A: and then it's like you know the kids are kind of like oh but is it cheating i was like cheating the real world is going to pay you half a million dollars to be good good at using the stack so
[00:24:50] B: Mm-hmm.
[00:24:50] A: like you're you're cheating in the context of the old
[00:24:53] B: The
[00:24:53] A: world
[00:24:53] B: old rules.
[00:24:54] A: yeah
[00:24:54] B: Yeah.
[00:24:54] A: the old rules the old game but that game is no longer even the game that's worth playing so it's like you if you were willing to reject that and like discover this new next game then like you could become good at the next thing and then
[00:25:08] A: yeah sure most people don't know how to put a price on it what it's what it is they don't know but like if it is the future then eventually they'll catch they'll come around and they'll realize like leverage this is leverage and then the rules will be defined and then you'll be able to be it's like you know in the beginning of social media all
[00:25:26] C: Mm-hmm.
[00:25:26] A: the all the companies had no idea what they're doing
[00:25:29] A: But then the kids did and the kids were just good at social media and then the company started hiring kids to
[00:25:33] D: Mm
[00:25:33] A: -hmm. like run social media.
[00:25:35] A: It's kind of the same thing. It's like this is a huge wave of new technology.
[00:25:40] A: No one in the old world knows how to wield it.
[00:25:43] A: uh the people that do are kind of like concentrated at the labs and then it's like if you pick it up and play with it you might become an expert at the next game
[00:25:50] E: What an interesting analog.
[00:25:52] E: That's super fascinating for youngins entering these funky labor markets.
[00:25:56] A: yeah oh that's the way you have to you cannot go for yesterday's game
[00:26:02] A: it's not even clear to me that yesterday's game is worth playing
[00:26:04] E: Mm hmm.
[00:26:06] A: and it's like or even more valuable than the next game but
[00:26:10] E: it's it's a funny one because I don't think the establishment or the traditional companies have these like new defined roles of the hyper engineering or something of the sort.
[00:26:18] A: no
[00:26:19] E: So.
[00:26:19] A: I think every single company is going to should be hiring vibe coders and the number one request I get when I'm talking to people is how do I hire it's like one they try to hire me
[00:26:28] A: and I have a job but then then they'll be like okay how do I hire people like you and that's it's a very and then I was like oh shit like how would I find someone who's kind of in this mindset where is that person and it's hard I mean it's it's it's like then they try to hire my friends which is that's a cool thing is like I have friends that I've been bringing along on this journey people that I was bouncing these ideas off of a lot of them eventually like they might have experienced layoffs or they were like well I think I should just take time off
[00:26:54] A: To kind of go deep,
[00:26:55] A: figure out the next thing and then come back into the job market with this.
[00:26:59] A: new new skill set and and because parth kind of took that risk and mapped it out like i can like because i did that i can just give you the like i can get you to level two level three faster because like you don't need to you still need to put a lot of hours in to become good at anything but you wouldn't be guessing as much because you have a peer group that's like also exploring
[00:27:19] A: So I knew I would I was like in the best case scenario,
[00:27:21] A: I do this work so that most of my network doesn't have to start from scratch and then I can kind of see the technology within the network and then the whole network becomes more resilient and then the longer term value is that if we're still right and that it is like an upgrade to the way we work and think,
[00:27:37] A: then six months from now you would be teaching me something that I didn't know about how to use the tech to create these feedback loops of community.
[00:27:44] B: So fascinating.
[00:27:46] C: Okay, but you still haven't hit on how you started generating revenue because business-brained Parth
[00:27:50] A: yeah
[00:27:51] C: couldn't
[00:27:51] A: oh
[00:27:51] C: have been in this post-severance period like
[00:27:54] A: man
[00:27:54] C: I can just have fun with my AI in the basement for the next year and just keep on vibing. You were probably starting to get a little stir-crazy.
[00:28:03] A: yeah three months three months into not uh like after severance and three months into just burning my money and i mean burning my money like the more interesting and creative my ideas were the more compute i would burn
[00:28:14] A: burn trying to achieve that or like you create a chat bot you put it put it in a group chat and you leave it on all night and then you realize you wasted like two thousand dollars on generating the word it's just saying thank you to each other it's like oh shit like what did we learn here it's like okay maybe you need a manager in the room to like end the conversation so we don't spend all this money and i was like did i just spend rent money like oh man like so then they look the lessons became expensive and then my friends one of my friends like part just like pick up coins along the way
[00:28:42] A: like turn this into money my mom was saying the same thing she's like everyone's gonna catch up to you and then a couple months later i was like no one's gonna catch up to you because you don't have a life you don't have a wife you don't have kids like as long as you don't have a life when you gas pedal like it's gonna be you're gonna have this lead which you can't do forever it's not sustainable and for me it was like i started then i sold all my crypto i
[00:29:04] A: And I don't recommend this to literally anyone.
[00:29:07] A: And in retrospect,
[00:29:08] A: even if I asked AI,
[00:29:10] A: it probably would have told me to like do something other than.
[00:29:13] A: early withdraw my 401k yeah
[00:29:14] C: Yeah,
[00:29:15] A: 
[00:29:15] C: that's a little bit crazier than selling all your crypto when you just
[00:29:17] A: with
[00:29:17] C: say out loud.
[00:29:17] A: how many finance people we know uh like this is the problem like when i say like i'm anti-establishment slash mainstream to a fault like asking anyone in finance what the right thing to do in this scenario they wouldn't have recommended this and they might have suggested a lower risk kind of way to like just buy more time and i guess i was in a state of like isolation of like
[00:29:41] A: I just need to move to the next like the next day I'm going to learn the next thing the next day I'm going to learn the next thing
[00:29:45] C: Yeah.
[00:29:45] A: and I wasn't thinking rationally about like uh I was like okay if I just sell all that I still have x number more months of like play time and and I was also like you know you go to the
[00:29:59] A: and you're like okay well are you insane it's like yeah probably but also like you have figured something out and you can't go to the regular the real world is just not even paying attention really outside of san francisco to what this means and uh you can just get better at this tech like then i was like okay would i rather a year from now have no money to my name like literal net worth zero and be good at using this
[00:30:24] A: or would I rather have like a regular job and not know any of this stuff and I was like I would much rather have no money but be good at using this because then someone's going to probably pay for me to think like this and that was like
[00:30:40] A: like once you say that and once you believe it and then it's like okay cool like we're gonna go until we run out
[00:30:45] B: your one decision to make a thousand basically like that had decided what the next 100 days would look like make doing that
[00:30:52] A: yeah
[00:30:52] B: calculus that's
[00:30:52] A: yeah yeah
[00:30:53] B: so interesting
[00:30:53] A: and then there are other mantras like you know you're talking to the cats and you're just like don't worry guys like the boys ain't gonna starve the boys will have wet food once again and it's like with that mindset is more like look we're not gonna start like okay let's say even if i run out of all my money
[00:31:09] A: Okay,
[00:31:09] A: worst case scenario,
[00:31:10] A: I could go ask my friends, you know, if they need an analyst,
[00:31:14] A: like what I was good at before AI,
[00:31:17] A: I would be 10 times better at now.
[00:31:20] A: So like, I feel confident in at least getting an amplified version of my old role.
[00:31:25] B: Yeah.
[00:31:25] A: Right?
[00:31:26] A: So like, we will make money if we need to make money,
[00:31:28] A: we will make money.
[00:31:29] A: It's just that I would rather
[00:31:32] A: be in a headspace every single day of using the new capability than playing yesterday's game not not everyone can do that like and not everyone has enough time or learns quickly enough to skip to the next game even through experimentation um and i noticed this a lot because like um like especially if you have like a wife and kids like you don't have nearly as much time to learn and explore and i thought of it as like and i was like
[00:31:59] A: had another thing you tell yourself to justify lighting all this on fire is like oh they don't teach this like my mom was like maybe you should just get an mba i was like then i definitely don't learn this like what like get an mba that's down to lose money
[00:32:12] B: Learn to
[00:32:12] A: yeah
[00:32:12] B: smile more.
[00:32:13] A: yeah it was like then i lose money and it's like i have not i definitely they don't teach this in mba and i would lose lose my money and and uh i say lose my money it's not that i don't value an mba it's just i've never in my life been in a room looking around like gosh
[00:32:26] A: oh shit if only we had someone with an mba like that's never happened um but then i was like like okay they're not teaching this in school so then i was like okay another way to think about this is like i'm investing in my own education yeah
[00:32:43] B: And when did we start seeing the ROI on that investment?
[00:32:47] A: yeah pretty much i was like down to like two months of
[00:32:49] B: runway Okay.
[00:32:49] A: and uh my mom my parents i visited my parents and they could tell because i was like very honest because like they were like oh why don't we let's we want to travel here uh in three months and i'm kind of like
[00:33:00] A: yeah i can't really think about three months out because i need to think about how to make money three months from now and like i know you want to plan that trip but i'm not going to be able to come because i need to like figure out my life right and then they were just like oh shit they were like what like do you need help like honestly like i know that my parents would have allowed me to move back home and just live in the garage if that's what i needed to like find my place and maybe part of it is like my own uh just i was like you know i will figure this out
[00:33:26] B: Mm And-hmm.
[00:33:26] A: also I was optimistic because I had just gotten like the first like contracting gig started coming online where I was working I was basically like I wasn't completely alone I mean I was alone in my work but being in LA I would I would go to events all the time like every week I would go to like community events AILA largest community around AI in the city.
[00:33:50] A: And I made friends,
[00:33:52] A: I was introduced to the founder of AILA, Todd Tarazas, and he's amazing.
[00:33:55] A: He's a great connector.
[00:33:56] A: He calls himself the nerd herder because
[00:33:58] C: Hmm.
[00:33:58] A: he gets nerds together and we, and he's focused a lot on like the evolution of Hollywood.
[00:34:03] A: But at the same time, I'm focused on the like the automation and the coding agents and the like automation of cognition.
[00:34:09] A: And so we're, we're like hanging out.
[00:34:12] A: And like we're throwing events,
[00:34:14] A: we're trying to get people together to like learn what is the builder community,
[00:34:17] A: the creator community doing with this because we're not the only ones seeing this like.
[00:34:23] A: transformative movement it's like it's not in isolation you get a bunch of people together you realize you're not crazy you're not the only crazy person there's a couple other crazy people it's a subculture it's not mainstream yet but at least we can create our corner of the city where we're experimenting we have hackathons where people are using image and video models to tell short stories and make music videos and uh so in la the hackathons are like creative hackathons then you also have technical people here and so um in working on the community meant that people would see what my
[00:34:52] A: my abilities were so you go to a hackathon you get to know people and they're like oh this guy has a skill set which isn't traditionally really defined yet and then people would be like oh we'd love to learn how to implement this in-house so like i knew that language models are useful and there's like a there's like a progression curve of an organization adopting language models
[00:35:11] A: and i think like there's the level zero stuff of like let's just make sense of the information we have create structure from all the unstructured data then you know level four or five is agents but everything up until that point is like on the path towards becoming a more efficient company so like the skill set is useful can you implement it and so i was taking contracting gigs and i was like okay great like
[00:35:31] A: my buddy john milinovich i worked with him at clubhouse and he was like he gave me he was like parts you have finally he's like good like you have found a market for this new skill i was like great he's like now you just need to figure out what the price to charge is i was like how do i do that so just raise your rate with every new person you work with and then when they say no you may have discovered the neighborhood of the price and so as i would get these contracting projects i would just charge a slightly little higher amount and then no one would ever say no i was like
[00:35:59] A: oh shit like this is actually like potentially like even today it's like
[00:36:04] A: oh dude i could be charging like a stupid amount for this but then i for my friends i just like let's just get you alpha right
[00:36:10] B: Yeah.
[00:36:10] A: like i would rather invest in you and then see the the the the like like the payoff for me is like where you are two years from now having now knowing this new game
[00:36:19] B: Mm
[00:36:20] A: exists
[00:36:20] B: -hmm.
[00:36:20] A: instead of me trying to like um extract value from every single interaction that i have
[00:36:25] B: I love that.
[00:36:26] A: um at least for my friends right like randos maybe i'm down to charge people yeah no to two maybe 20 maybe that's
[00:36:32] A: maybe that's that's the question
[00:36:32] C: mm
[00:36:33] A: is like maybe we should be like at bc when i we used to work i used to work at bc one of the first things i did was like we should just slap an extra zero on what we're charging clients
[00:36:44] A: -hmm and it turns out they wouldn't say no this is the whole
[00:36:46] C: it actually adds
[00:36:47] A: yes
[00:36:47] C: to your ethos the price yeah
[00:36:49] A: yeah they're like oh we got to take them seriously because like they're actually charging us real money right but it's not like a donation to a bunch of students it's like if you think that's what you're worth and you charge that and then people actually pay it and you deliver the value
[00:37:00] A: you like it's win-win actually but so that was like an exploration in pricing and also i got a job um creating courses for coursera and they were like we wanted you to teach they basically brought me on to to create a bunch of courses related to language models for data analysis that's my core skill set but then also language models for software engineering which was like whoa
[00:37:22] A: I'm like not a software engineer but I'm teaching a course on language models for code generation and software engineering my buddy was like part one of the highest leveraged things you could do is be someone that teaches software engineers
[00:37:31] A: like that's
[00:37:32] C: Hmm.
[00:37:32] A: a valuable that's a very high leverage thing and i was kind of just like imposter syndrome but then it's like i have a course on llms for software and at the time it was like i was using coding copilots but like the course was like let's just do chat gpt or like let's just you how do we use an api and i was like so very intro level stuff like chat gpt for code gen and then like
[00:37:54] A: embedding models and retrieval systems which is like very easy for me at this point because i've been playing with it for like so long but i was also like oh this shows like the the like we need to i need to come back to people's like level and give them the like first thing the first piece of leverage what's the most important first thing you learn such that you might discover for yourself all of these other things because i can't tell you what the most important thing is but like if i give you the first couple wins
[00:38:20] A: the model will reveal to you a lot of these other things that even I haven't seen and so but the doing the Coursera was like when I say it's like is it better than the influencer course selling thing
[00:38:31] A: I didn't own those courses.
[00:38:33] A: Coursera owned them.
[00:38:34] C: Basically, it's just less profitable.
[00:38:37] A: Yeah. So I get the stamp of Coursera on my bio. And actually, like, I didn't put it in my bio because I was kind of like I was kind of just jaded by I was like, man,
[00:38:44] A: I did something very useful, but I don't own a stick.
[00:38:47] A: So it's like I don't even promote the course because I don't get paid more for more people taking the course.
[00:38:51] A: So like I didn't even put it in my bio because I was kind of just like jaded by this.
[00:38:57] A: Coursera, if you're listening,
[00:38:58] A: you might want to change that.
[00:38:59] A: creator revenue model um course creator revenue model i mean honestly like if you want to get a good teacher and you want them to stick around and really contribute you got to give them some kind of vested interest in contributing to the course but then uh then you go to a language model and you ask it okay who is parts patel two years ago it would just be like there's like nine parts patels out there and it would just blend them all into one guy then it was like there is one parts patel
[00:39:25] A: notable for working with language models and he has a Coursera course I was like damn I didn't put that in my bio like the language model could go find those details and then I was like okay I'll put in my bio so that the language models know because the language like because then when you have a conversation with language models like who is Parth and then it's like it's nice that the models know that I have Coursera courses even if I am not personally promoting them it's just like
[00:39:48] A: it does lend credibility to work with a notable brand um i do think that if i did the same course as an actual create if i build a creator brand and build my own personal brand and i sold those courses i would make way more money yeah um that was the lesson there the lesson there was like okay like
[00:40:06] A: you built a course and it's on someone else's platform and you don't even own a percentage stake now your motivation isn't there you're kind of jaded but actually like it's like okay then i was like okay i gotta build my own brand actually like it's more important to build so that's actually why i came to work here with a bunch of creative people is like creators in la is like they are like their business is the brand the their business is the creator journey and i am at the very beginning of that of like realizing that like okay
[00:40:32] A: okay you don't have to build everything on other people's platforms and actually you should have a corner of the internet that's your own especially because the language models will be surfacing you in conversation and it's like how do you become the answer to the question of who someone is looking for and so that that has been an interesting thing of like
[00:40:49] A: unless you own your own presence on the internet you let it be defined by other people and then the nice thing is that language models make it easier to find some of that stuff so that you end up you end up showing up in conversations as the answer
[00:41:01] B: to You surpass your name twins.
[00:41:05] A: yeah yeah now now if you go to a language model and you say like who's parth patel like it will actually be able to delineate between the different parts patels and there's like nine of us at least on the planet nine of us that at least work in tech
[00:41:17] A: heck there's probably like a hundred thousand of us but like most of them aren't on the internet and it's like okay so then i was like started taking speaking gigs because i was like oh turns out that also helps right like coalescing who you are and then i went back into corsair i logged in and i updated my bio so it's more consistent with my presence on the rest of the internet so that the language model seeing
[00:41:37] A: 500 links would be like okay this is Parth and this is a bunch of other people also named Parth Mm but
[00:41:42] B: hmm.
[00:41:42] A: that this is the Parth that's known for working with language models at the bleeding edge of coding agents that like I want to be known for that so then I put that on the internet internet is like evidence of how that how I should be known for that yeah
[00:41:55] B: Yeah.
[00:41:55] A: 
[00:41:55] B: Yeah.
[00:41:56] B: So you do the course,
[00:41:58] B: you're starting to get consulting gigs.
[00:41:59] A: Yeah.
[00:42:00] B: And at this point, you're probably feeling a little less imposter syndrome surrounding this skill set.
[00:42:05] A: Yeah.
[00:42:06] A: It was cool because that was two months after my parents were really concerned about me.
[00:42:09] A: And I was like, I think I can, I think I'm on the verge of this.
[00:42:12] A: And then, then my fate kind of, well, basically I went cashflow positive and the cashflow
[00:42:19] B: That's
[00:42:20] A: started
[00:42:20] B: big,
[00:42:20] A: to increase.
[00:42:20] B: baby.
[00:42:20] A: Yeah.
[00:42:21] A: Yeah. Wet food.
[00:42:21] A: Wet food.
[00:42:22] A: You know, the boys ain't going to starve.
[00:42:26] A: and then um a mutual friend out of the i was working at this i was just co-working at a hacker house with a bunch of ai la people and one of the guys at the hacker house ben relis um he he he was like oh like do you know how to build these these i was really good at building chat bots and he was like you think you could build a chat bot on top of like a corpus of an established creator and i was like yeah so i built the first version of that that afternoon for uh reed hoffman
[00:42:53] A: and then they were playing with it and then they were like oh this is really like good and then he was like you should a couple weeks later he was like you should come to the bay area and then I come to the bay area he introduced me to Reid Hoffman
[00:43:03] B: Hmm.
[00:43:03] A: and we we talked for like five hours basically Reid's just picking my brain about like this journey the same conversation we're having right now I was like I was like what did you like what have you learned in the last like exploration of language models and it's like well here's how it applies to every domain I've ever worked in I spent one month talking to language models about music
[00:43:22] A: it turns out they're really good at operating a digital audio workstation but then if you combine that with the fact that you know they're good at code then you start wondering well then they're going to be really good at using the computer then actually i should be able to talk to my software like then it's like what is the role of voice like all of these these like trend lines that i've observed in exploring the models and i'm talking to reed hoffman right co-founder of linkedin one of the earliest investors in open ai
[00:43:47] A: and he's probably the first person i talked to that's like like we can have a real conversation about the second third order effects and
[00:43:55] B: Wow
[00:43:56] A: that like i am not insane but that this is actually like the game has changed and um that ends up being a four and a half hour conversation and um next day um he reached out and he's like you should you know like would you be down to work for me
[00:44:13] A: and uh i said yes and so i've been working with him for almost two years now uh kind of doing the same stuff but now i have a team of people and we like people that i build tools for so i get more feedback uh than just working in isolation and also like uh reed is one of the most creative people i've ever worked with and so he's just got like a thousand ideas and
[00:44:34] B: Mm
[00:44:34] A: that's
[00:44:34] B: -hmm.
[00:44:34] A: perfect when you have hundreds of agents that are coming online and you're like hey like we should attempt and start figuring out all these things we're no longer bottlenecked
[00:44:42] A: on dev productivity if we can like delegate a lot to this to these models that are coming online and like uh so like the projects are ranging i think read ai has now become its own um more sophisticated thing like it's gone on speaking tours it's probably going to be on more podcasts
[00:44:57] B: Read AI is the
[00:44:58] A: yeah
[00:44:58] B: avatar.
[00:44:59] A: It started off as a chatbot, but now we have a visual avatar.
[00:45:03] A: We have like an interactive avatar you can talk to. It's not widely available yet,
[00:45:06] A: but it has been on like Colin and Samir's podcast.
[00:45:08] A: And I could totally imagine this thing being on, it's been on the news in different forms.
[00:45:13] A: And it's been an interesting project because it blends language models and video models and avatar technology,
[00:45:22] A: retrieval systems into this like avatar experience. So I'm known now.
[00:45:26] A: Now for digital twin projects and like AI clones.
[00:45:31] A: as a side effect of being good at working with language models is
[00:45:33] B: Mm
[00:45:34] A: that
[00:45:34] B: -hmm.
[00:45:34] A: this problem space became like and it was just because like we're like oh what if we did this like and i was talking to readers like what if we connect this to like an avatar we could create that scene from tron where clue like where jeff bridges talks to himself and i was like that would be amazing and then we like get access to hologram technology and and van nuys and then they're like oh we can put this avatar in a life-size box and you can show up and talk to it and so they it just keeps
[00:45:58] A: getting that project has been a magical surprise because it's just like
[00:46:02] A: it's like oh we would love for read ai to keynote speak at the computer history museum i'm like are you kidding me like that i went there as a kid it's one of my favorite field trips and then i get to come back and like a thing that i made is now giving a keynote presentation and so it's you could never it's that's one of those weird things where like you don't know where it's going to go but like you're rewarded for playing with technology and also because what i learned from read was like i was because i was mind blown at how like
[00:46:29] A: like it opens doors but it's what i learned from it was like well if you're early to something and you experiment publicly with the technology then what happens is like everyone else knows you as that guy and then eventually it'll go mainstream and it'll be they'll take it for granted one day but they will remember you as the person that introduced it to them and so we did that with avatar technology but it also was like i did that with gpt for my network i was the guy i was like and i used to one of the mantras when i was unemployed was like
[00:46:56] A: i could be like the johnny apple seed of gpt4 i just go around to just like sprinkle gpt4 across everyone i meet it's like you know you you know you meet the cashier it's like you should download chat gpt and he's just like what trust but it's like you know you never know it's like you get your uber driver it's like have you have you heard of the lord and savior chat gpt and then next thing you know they're like oh my god like this changes so when you actually so then but then like my my friend's like oh you should be using cursor
[00:47:23] A: before anyone else i'm using cursor now everyone's using cursor right so before anyone else like i recognize the technology is really good then i planted across my network partly because i'm like it starts off small it's like okay
[00:47:35] A: did everyone hate that or did it change the way they work every day because if it if if they hated it then i'm like okay why do they hate about it and then like move on to the next thing but then it's like you some things you show people and everyone agrees this is a game changer and they're using it in a different way like voice transcription technology same thing coding agent same thing cloud code same thing it's like this technology sells itself and so i'm like the johnny
[00:47:59] A: apple seed of that i was like i'm just going to go and plant orchards by dropping apples all over the country and then a couple years later it's just like ah yeah now everyone's on it thanks to like a couple people just like being out there and creating content and then just like putting it out there yeah
[00:48:13] B: how was at the end of that four and a half hour conversation your brain what were like the chemicals swirling in your brain like after doing so many months of
[00:48:25] B: sprinting on this problem space probably
[00:48:29] B: You had to live by these mantras to get you through a
[00:48:32] A: yeah yeah
[00:48:33] B: lot of this period and doubt started to creep in.
[00:48:36] B: And then there's this extreme moment seemingly of validation and maybe there was several moments of payoff in the months leading up to this. But this really does feel like a pretty damn cool moment that just kind of validated all the months before. I'm curious.
[00:48:50] A: yeah it was definitely the final like like it was like okay cool
[00:48:55] B: Yeah, it's
[00:48:56] A: maybe there aren't that the many
[00:48:57] B: final scene of Pursuit of Happiness.
[00:48:58] A: yeah it's like yeah yeah yeah well it's like i mean look all my smart friends understood they're like he's not insane he's just like early and then i and then you meet reed it's like okay no this this is like actually like most people have not even recognized that the game has changed
[00:49:15] A: and they're still playing yesterday's game
[00:49:17] B: Hmm
[00:49:17] A: and um but hearing that from him and um getting to bounce these ideas off of him for over four hours i was like we all have now more questions than answers and that like uh like we need to find more people that are also just like
[00:49:35] A: um in this wild west right
[00:49:37] B: Yeah.
[00:49:37] A: there aren't many of us it's a subculture and there will be it will eventually go mainstream but like right now we kind of need to just assemble like assemble the the avengers and just kind of like bounce the ideas off of the people that are like really pushing on them and then learn from each other and have these conversations that otherwise you just i mean for me now i've created enough of a network that i can
[00:50:02] A: i can like call on my friends even in la and have a conversation about this tech but back then it was like isolating right you're the only person that knows or wants to talk about it or you go to sf and every coffee shop's talking about it but
[00:50:14] B: Mm-hmm.
[00:50:14] A: if you're not going to be in sf then you better have like the internet you better have communities that you create where you can explore it otherwise it's going to be very isolating but meeting reed and the end of that was like cool like
[00:50:27] A: if i could go more all in i would like you know i mean of course now i still need to figure out money but then the next day he offered me a job and i was okay and then when when we first had our first meeting it was very much like you can do the same thing except now it's like not it's
[00:50:41] B: not Have
[00:50:41] A: yeah
[00:50:41] B: you on the payroll.
[00:50:42] A: we'll pay you yeah you got health insurance um but like we're gonna do it even bigger right like uh we're gonna go further we're gonna learn more it's no longer limit it's not like it's not the experiments that i i and also he started introducing me to people
[00:50:56] A: like within Microsoft that we're also thinking about because I was like okay who's working
[00:50:59] A: on this that's not constrained some people at microsoft you
[00:51:03] B: Yeah.
[00:51:03] A: know you meet you meet the guy who builds google docs um sam scolace we have a conversation he's like yeah i got i got a couple dnd agents talking to each other and it's and he's like that's like a failure because like um last i checked it's just playing chess with some npc i'm like isn't that victory a lot of times you're playing dnd and like people go on this side quest that you didn't expect and then that is actually the magical thing is that's the unscripted like side quest
[00:51:28] A: that they spend up they're like oh we're just going to go to the tavern and buy drinks for everyone that's going to be what we do today and then like you may have planned something but it's the thing that you didn't expect that ends up being the thing that everyone loves yeah so i i think of that a lot i was like okay finally started meeting people that because i was doing dnd bots i was like
[00:51:47] A: can you just have a dm and can you have players and then can you have can you create an adventure in this like improv manner when you create a couple different chatbots and you tell them to play dnd with each other and group chats and stuff like this is the beginning of multi-agent stuff and then um it's all relevant because now that all of the models are better they can use tools so i'm reassessing those same ideas but now giving them it's like what happens you do a group chat of coding agents
[00:52:11] A: okay well now how do you make it so that when they work together today it's like it's not solved but like because i've been working with these things even when they were imperfect it's just like
[00:52:22] A: cool one day it'll work it gets better and also like maybe this is the wrong way anyways but it's a lot of fun and it's not useless it's
[00:52:29] C: Mm-hmm.
[00:52:30] A: like it just reveals something about what's possible new form factors and um i don't think it's i don't think you're really wasting time i think you're just like banking experience of like what worked what didn't work what might work and maybe it ends up all being a waste of time when gpt7 comes out
[00:52:48] A: I doubt it, though.
[00:52:49] A: And also until GPT-7 comes out, like these things are inklings of like useful paradigms to lean into.
[00:52:57] D: When we parse what knowledge means in this space,
[00:53:00] D: I think that that is actually like exactly what you're talking about right
[00:53:02] E: Yeah.
[00:53:02] D: now with like once GPT-7 comes out,
[00:53:04] E: Yeah.
[00:53:05] D: are the skills that I've built useful?
[00:53:07] D: And I think that that is for me a real curiosity surrounding hyper engineering or vibe coding or whatever the future of software engineering is, is is it like something that the intelligence threshold and knowledge threshold and skill threshold continues to basically?
[00:53:23] D: diminish and me who has not been playing in the same playground as you and just tried to basically vibe code with GPT-7 can start building similar applications and similar cool things to very skilled parth. I'm curious what your perspective on that is.
[00:53:39] A: Yeah, I have suspicion.
[00:53:43] A: Okay,
[00:53:44] A: so when I think about like, okay, a lot of times people say prompt engineering.
[00:53:49] A: doesn't matter or like the models will just prompt themselves which is true the models will prompt themselves but i don't think that prompt engineering doesn't matter i think that like people have not really
[00:53:59] A: find prompt engineering as a um what i did a little over a year and a half ago was i read there was a paper that tried to create use llms to figure out all the different techniques of prompt engineering just have them read a bunch of papers on prompting and then it's like do a taxonomy analysis like how many techniques are there and at the time there were like at least i think there were like 80 something techniques back then
[00:54:20] A: and i was like wow if there are 80 like some of them are like few shot prompting provide examples of how to solve the problem or like allow it to use tools or like image prompting these are all different approaches to prompt engineering so then i was like okay there's at least 80 you can also mix and match them which means that like prompt engineering is a very uh multifaceted uh space of like bringing context into the model so that it has a better chance of like zero shotting your problem
[00:54:48] B: Hmm.
[00:54:50] A: or like even just helping you with your problem
[00:54:51] C: not And
[00:54:51] A: even i
[00:54:52] C: zero shotting is so important because of the cost in both time and dollars,
[00:54:56] A: right? don't think it's that it's more like if i can get this thing to solve the problem in one word prompt and it takes you like five turns of conversation then maybe i'm maybe i'm just better at this than you and it's like uh i think that's this is more like okay prompt engineering i think is sort of like the 10 000 hours
[00:55:16] A: you gotta you gotta run 10 000 prompts before you like judge a model and i'm not saying that like like you could like you get better by looking at other people's prompts you can get better at using you have to use the model to get better at using the model knowing what you can ask for but then there's this whole other vector which i've been thinking about which is like expertise the role of expertise and what levers that gives you so if you're really good at something
[00:55:39] A: You have a very rich vocabulary that comes from being good at that thing. If you're really good at photography,
[00:55:44] A: you know how to use your camera,
[00:55:46] A: you know all these levers of the different settings on your camera,
[00:55:49] A: or you know cinematography or you know direction,
[00:55:52] A: you know like anything.
[00:55:54] A: The better you get at it, usually there's an associated vocabulary that comes with that expertise. Like if you're a five-year-old working on...
[00:56:04] A: playing an instrument it's different from like Hans Zimmer working on like a movie soundtrack movie score and his exposure to so many like his experience his exposure to so many experts allows him to articulate his vision to these other experts which work on his behalf to create a more comprehensive ambitious thing than a five-year-old could ask for five-year-old can ask for something and I'm sure it will probably sound like a masterpiece but they're less in control because they don't have the control over the language
[00:56:31] C: Yep.
[00:56:31] A: and i think about the language is like your um i'm gonna get his name wrong fitkinstein i'm
[00:56:39] C: Mm-hmm.
[00:56:39] A: gonna name drop did
[00:56:40] C: You nailed it.
[00:56:41] A: i okay so what did what did fitkinstein say reed's always name dropping him and i'm always like but then it
[00:56:48] C: You
[00:56:48] A: i
[00:56:48] C: do something regarding like the game.
[00:56:50] A: think he says okay he says like uh yeah look it up look it up pull that shit up pull that shit up pull that shit up um i think he says like language is the limit of my uh cognition or
[00:56:59] A: language is the limit of my ability to think pull it up find the actual quote though because i don't want to forget this or butcher it but i feel like i discovered that and then i read Wittgenstein because my buddy was a huge philosopher and mentioned it and then i was like oh this makes sense like i'm just there's nothing original it's just what's the quote what's the
[00:57:16] B: The
[00:57:16] A: quote yeah
[00:57:17] B: limits of my language mean the limits of my world.
[00:57:19] A: yeah
[00:57:19] B: That's gorgeous.
[00:57:20] A: the limits of my language mean and that's even better than what i was suggesting because
[00:57:27] A: it applies to all ai not just chatbots but like every image model and video model and game model of the future the limit of your ability to wield the technology the limit and their world engines things that can literally generate worlds so the limits of your world and what you can create are it's it's the language it's
[00:57:44] B: Mm-hmm.
[00:57:44] A: like your ability to articulate that and you could give that to a language model but otherwise in that scenario you you are still less like you have
[00:57:51] A: You are telling the language model to do some of the decisions that you wish you had more control over,
[00:57:56] A: but that would only come with experience and or expertise.
[00:57:59] B: Yeah, that makes so much sense. And I think once you have that output from the model.
[00:58:06] B: The expert will be able to have the taste to
[00:58:08] A: yeah yeah
[00:58:09] B: say,
[00:58:09] A: 
[00:58:09] B: okay,
[00:58:10] B: where did it fuck up?
[00:58:11] A: or like pull some more levers and get better iterations the people are so obsessed with the zero shot but i actually think that like the sixth or seventh version of something is if it could do this if it could go so far in one
[00:58:23] A: then you see it and you play with it and you're like well actually what we need is slightly different Mm what we
[00:58:26] B: -hmm.
[00:58:26] A: want is different like my vision is a little more ambitious or different then the second and third rounds of iteration are also very powerful of
[00:58:33] B: Mm-hmm.
[00:58:33] A: course you go to Replit it will Replit's like vibe coding app the first version will be impressive
[00:58:39] A: but it's like the eighth or ninth version once it's like deployed with a couple people that you actually are like this is like the well-oiled machine so
[00:58:45] B: Hmm.
[00:58:46] A: iteration is key expertise is key even if the old job is gone you having experience it's a good like it's a good like bridge for you into the next game is leaning on your domains of expertise the other issue is that not everyone's an expert in anything like many people are not an expert in anything
[00:59:06] A: there's a positive there which is through like dumb luck and just like being a noob you might discover something that experts would otherwise be too proud to discover like i believe i'm one of those people where i'm like i just asked the model hey is this possible and it's like yeah it is okay good thing i didn't good thing i didn't think that this was my unique like like that like i had to do this myself that i might be
[00:59:30] A: uh too proud to like ask for a possible answer from a thing that is trained on everything um
[00:59:36] B: Mm-hmm.
[00:59:37] A: and i find that like that's been huge for me like humbling it's just like dude you're not gonna learn everything you're gonna get good at a couple things in life but as also like you can just not be judged for asking dumb questions now and then you might just stumble into like interesting solutions like now when i do presentation i used to hate doing presentations because
[00:59:57] A: It's not that they're active,
[00:59:58] A: like doing.
[00:59:59] A: making a presentation is like annoying but but like that my mind would see a deck and i'd be like this is off by a pixel i'm like why does it matter why do i care that it's off by a pixel like like isn't it the subject of the deck like now i'm distracted i'm like why three of the bullet points have a period the fourth one doesn't and i'm like am i missing the whole point here right like by paying attention to the detail and a lot of that being hand manually done it's like man we're spending so much time in the the thing other than the idea
[01:00:26] A: idea yeah but then i went to a language model i was like you know build a deck and then it builds a presentation and i'm looking at it was like wait this is a web app that looks like a presentation and it's like yeah what do you need and i was like give me a pdf it just converts that into a pdf i'm like we're using web development to build presentations and i was like um it's like oh it's let's create a fake data set here's a fake data set for an ice cream company you build a deck it builds the deck
[01:00:52] A: the deck is like pink and it has like ice cream and stuff i'm like make it mckenzie though and then just rebuilds the deck in the style of mckenzie and for all intents and purposes it's a presentation but it's not built in powerpoint and it's not it's built in html css and javascript and it's got like sleek animations and everything but now i'm
[01:01:12] A: creating the entire thing by just prompting it i can be giving the deck as a i can be presenting the deck and then someone asks a question then i can switch over to the coding agent and be like add a slide about x by the time i get there that slide is ready and so now i'm like well i've discovered that you can vibe code decks why would i do why would i make a deck manually ever again if i could just talk to the model and it could generate the deck and it would look professional
[01:01:39] A: as i need it and it's uniquely and i can be like oh it's too verbose oh yeah it'll just rewrite every single slide make it less verbose and it's like oh vary the slide layouts a little bit make it more like you know you can't just have three bullet points on every slide it adds more variation so i'm like wow like i feel like i'm the partner delegating
[01:01:56] B: Mhm.
[01:01:57] A: to the analyst right
[01:01:58] B: Yeah.
[01:01:58] A: except
[01:01:59] B: Yep.
[01:01:59] A: now the analyst is this bot that doesn't sleep right and the ramp time for that bot to understand the problem is like zero
[01:02:08] A: which is interesting but again it's like i've seen and gotten good at the old way that was that is now inefficient and now i can ask for a higher quality output in like three prompts so again leaning on the expertise to get to a higher quality in your in the thing that you know how to judge quality on
[01:02:27] C: Yeah,
[01:02:28] C: it makes a ton of sense.
[01:02:30] C: Are you down to play a little game of
[01:02:33] C: But we'll call future headlines and we're going to try to we're going to try to test your predictive abilities for
[01:02:39] A: Sure.
[01:02:40] C: two to five and ten years out surrounding
[01:02:42] A: Okay.
[01:02:42] C: AI.
[01:02:43] C: Okay.
[01:02:43] A: I don't think anyone can see more than three years out, but let's play.
[01:02:46] C: You can though,
[01:02:47] C: you can.
[01:02:48] A: Maybe.
[01:02:48] C: Maybe. Okay.
[01:02:49] C: But I'm going to read you some headlines for possible things that we could be seeing in the AI world.
[01:02:53] C: Some are much more positive,
[01:02:55] C: some are a bit more negative.
[01:02:56] C: But yeah,
[01:02:57] C: yeah, of course you need those.
[01:02:59] A: And I just want to get your reactions. And if you have headlines that you think are much more likely than any of these,
[01:03:05] B: Mm-hmm.
[01:03:05] A: please tell me.
[01:03:06] B: Sure.
[01:03:06] A: But for two years out,
[01:03:08] A: A,
[01:03:10] A: a former CTO licenses his AI clone to his former company,
[01:03:14] A: trained on years of notes and meetings to advise company executives and engineers for royalties.
[01:03:22] A: B.
[01:03:22] A: AI agents are seen as being overhyped and continue to require a human in the loop for even many low-level tasks.
[01:03:30] A: C.
[01:03:31] A: Goldman,
[01:03:32] A: McKenzie,
[01:03:33] A: and Meta cut 25% of their analysts in research teams after internal AI agents significantly outperform those hires.
[01:03:40] A: Middle managers are next.
[01:03:42] C: Yeah.
[01:03:43] D: Okay,
[01:03:44] D: let's start with the CTO cloning himself.
[01:03:45] A: Let's do it.
[01:03:46] D: I think that digital twins that people I think because right now a lot of the digital twins are being attempted to being deployed within companies,
[01:03:53] D: that seems like what the headline might be. But I think even if you did that, that would be more of a stunt than a practical thing.
[01:04:01] D: I think that, yes,
[01:04:02] D: like digital twins of us working with each other while we sleep makes sense.
[01:04:06] D: I think a lot of context that we have like doesn't enter the company in a way that other people can use it. Like it would be nice if I could loan my expertise.
[01:04:15] D: while i'm asleep to people that i want using my a version of me and i'm working on digital twin of myself like can you talk to this thing and use and reach into some of my experience through this thing and um so i think there is a practical version of this i just think that like the more interesting thing that i think is like you've seen mulan oh
[01:04:35] A: I've not actually so
[01:04:36] D: my god too many people okay
[01:04:38] A: uncultured
[01:04:39] D: dude okay gotta watch mulan but
[01:04:41] A: For let's assume that the audience hasn't watched Mulan either.
[01:04:44] A: Give us give
[01:04:44] D: Are
[01:04:44] A: us a little
[01:04:44] D: you serious? Okay, okay, okay.
[01:04:46] D: Assume that the audience has not seen Mulan.
[01:04:49] D: Okay,
[01:04:49] D: in Mulan, Mulan is a story of a girl in China and then they're being invaded.
[01:04:56] D: and her dad gets drafted and so this is very beginning i'm not going to spoil anything her dad gets drafted but in her in his place she takes her dad's place in the army and then disguises herself as a man in order to enlist so that her dad doesn't have to go to war because she doesn't want him to die in battle and so she goes but then what happens is her they have like a shrine of her ancestors and the ancestor spirits come out of the shrine and then they meet and they're like oh my god
[01:05:24] D: we need to send someone to protect mulan so they send a spirit down in uh and he takes his name is mushu he takes the form of a tiny dragon and then it's like
[01:05:34] D: mushu isn't even like the spirit they wanted to send they're like you need to go wake up the spirit to save mulan but then he kind of messes up and then he just he's like oh i gotta go solve this problem myself so then he goes himself to accompany mulan on her journey and protects her i think the more practical beautiful version of
[01:05:50] D: Digital Twins is like, I would like to be able to lend my perspective on life to my great,
[01:05:58] D: great, great grandkids.
[01:05:59] A: Hmm.
[01:05:59] A: right like what if you could draw from the wisdom of your ancestors so i think that the ancestor version of we're going to get every version of this good and bad digital twins will be every version of this i think in many of these cases like what you're talking about that there you're going to get every version of this good and bad i think one of the more interesting positive versions of this is like i wish i could talk to my ancestors or a version of them or an agent that like embodies that like their
[01:06:26] A: publish body of work that i can lean on and it's not them it's like more like a painting in harry potter that's like animated that you can talk to and we're going to get that i think that we're also going to get these corporate like digital twins i just think that the cto one is like whatever although the like if that person is someone that like really the like like the steve jobs like you're going to want to be able to talk to the clone of steve jobs such that apple like i think there's some people will want
[01:06:56] A: Apple to be able to draw on Steve Jobs'
[01:06:58] A: unique perspective or some version of that to keep the ethos maybe somewhat in that world.
[01:07:05] A: But the corporate version is kind of boring.
[01:07:08] A: The ancestor version is more interesting.
[01:07:10] B: It's much more beautiful corporate version though.
[01:07:12] B: I mean, I think
[01:07:13] B: I hear in some of my work about companies where somebody is going to retire and
[01:07:20] A: Yeah.
[01:07:20] B: they're like, we'll pay you, we'll keep you on the payroll.
[01:07:23] B: You don't have to work close to the hours that you used to do,
[01:07:27] B: just you have to be ready to hop on a phone call when we need you.
[01:07:29] A: Yeah.
[01:07:30] B: And
[01:07:30] A: Yeah.
[01:07:30] B: that seems like a really weird
[01:07:32] A: So
[01:07:32] B: real application.
[01:07:32] A: that's definitely expert networks and stuff like that is a good application of digital twins.
[01:07:37] A: I do think that this is very likely that
[01:07:40] A: because people keep trying to hire me but i don't have a job so i'm like i say no and then people like well you cloned reed can you clone yourself because i would pay to talk to it i'm like that immediately it's like the question of like is this a new market what's the size of this market expert networks me loaning my unique perspective on life to people and then charging for it can this clone pay the rent i have not figured the answer out yet but i think it's yes like and you can scale your expertise through this kind of like experience so
[01:08:09] A: Yes, I think it'll happen.
[01:08:10] B: Fascinating.
[01:08:11] A: Yeah.
[01:08:12] B: And let's double click on the leading companies across tech and finance.
[01:08:19] B: What do you feel like we're going to see in the labor force two years from now?
[01:08:22] B: Do you feel like there are going to be a lot of lower level analyst type roles that are being removed or are they just going to be higher agency roles because of the little management that they get to do of the AIs below them?
[01:08:34] B: How do you see this impacting those big ass companies?
[01:08:39] A: This is my opinion,
[01:08:40] A: right?
[01:08:42] A: So I think that we're in the short run,
[01:08:46] A: a lot of companies will opt to lay people off instead of retraining them.
[01:08:53] B: Yeah
[01:08:53] A: I have not yet seen any major company outside of like a Frontier Lab type company.
[01:08:59] A: actually embrace ai in a way that is like ai transformation projects like i haven't seen any large corporation make that they say it they're not doing it i mean like they're trying but they're not trying hard enough in my opinion mostly because like you just can't moonlight like the amount of time and energy i put into just changing my own perspective is not something you can expect of everyone and uh you
[01:09:26] A: it's easy to expect it out of all the frontier labs because they for them it's like religion it's like oh we're going to do this we're going to build all our software using our coding agent we're going to build we're going to have gemini go and scan and like make everything more efficient like that makes sense because they're native they're ai native i think the the thing is like
[01:09:43] A: making an entire large company ai native is not i have not seen anyone do it right um but they will talk about it because that will signal to their board that they're interested they're like oh we you have to have an ai strategy okay well we have an ai strategy is it working in 90 in most cases like the pilot programs are failing it doesn't surprise me because they're giving it to someone as like a side project um rather than making it like the unique focus of like a team that's actually
[01:10:10] A: actually free to move with high agency within a large company they need to they need to do that this is why the startups is reaping most of the benefits because they're basically starting off ai native
[01:10:19] A: they imagine themselves as like okay we're going to launch internationally faster than ever before because now we have models that can help us internationalize our content our business we're going to monetize earlier than we need we we would have had to before we're going to raise less or like our rate fundraising strategy changes because all of a sudden like the cost to create software has has has fallen right so the new play style is unlocked but uncovered by startups rather than large companies
[01:10:46] A: And then the large companies,
[01:10:47] A: I think the other thing is there is a huge middle management class that I think like you'll see deeper layoffs within to improve like the like cost structure
[01:10:59] B: the
[01:10:59] A: of larger
[01:10:59] B: bottom line
[01:11:00] A: companies at
[01:11:00] B: yeah yeah
[01:11:01] A: the bottom line.
[01:11:01] B: I mean I think to this I really agree with the short term and I want to hear what you think in the longer term but I think the short term is so fascinating just because though agents and AI a few years ago you were very early on it now
[01:11:14] B: The stock market would disagree with you on being super early on it. Like right now, it is it is everywhere and everyone believes in it as like the future.
[01:11:21] A: Yeah, yeah.
[01:11:21] B: And I don't think that we're going to see the revenue.
[01:11:26] B: in any of these major companies reaped via ai in the next year or two in the way that would justify the valuations that these companies are now having or the
[01:11:34] A: When you say these companies, you mean like the hyperscalers?
[01:11:37] B: hyperscalers yeah yeah
[01:11:37] A: Yeah, there's definitely like a huge bubble narrative right now.
[01:11:40] B: yeah the price to earnings ratio
[01:11:41] A: Yeah,
[01:11:41] B: is
[01:11:41] A: yeah.
[01:11:41] B: is not because of mere revenue is not going to change i think within the next year or two because of ai productivity gains so i do think cost cuts seem like
[01:11:52] B: likely the way that AI is going to enable
[01:11:54] A: Yeah.
[01:11:55] B: these companies to hit some of their expectations in the immediate couple years.
[01:11:59] A: the thing is like we're in the very first innings of agents working this
[01:12:02] B: Mm-hmm.
[01:12:03] A: is like the first year i've seen a coding agent actually like coding agents that can work for like eight hours in a row um that that you feel like they're not and then they're now starting to get more parallelized on the cloud that you can spin up more and more of these like an ephemeral army of extra coding agents to work on something and coding agent is a misnomer it's just that coding agents are the most powerful versions of ai agents right now
[01:12:25] A: And they're just less intuitive to the non-technical folk,
[01:12:29] A: but they are the ones that have the most abilities because code is, it's not just for building software, it's that we use software as a way to solve many other problems and that you can use coding agents to scale cognition in cyberspace.
[01:12:44] A: That being said,
[01:12:45] A: if you think about where the job cuts, it seems like the jobs that are at risk are a lot of the jobs that were
[01:12:52] A: uh wrote cognitive jobs like repeatable tasks that are cognitive in nature that you could drop an LLM in and potentially get better output than a human and
[01:13:00] C: Mm-hmm.
[01:13:01] A: then those are risky and also anything that can be done behind a computer.
[01:13:07] A: which is a lot like like there's a whole class like there's a whole like a lot of us work behind a computer and if you use agents that can browse use a web browser that's just the first thing but like you use coding agents that operate on on the operating system level like they have the entire computer at their disposal to solve a problem and that you can run many of them in parallel it just is a very
[01:13:33] A: It's a new form of labor that is competing with the existing form of labor.
[01:13:38] A: And I do think that orchestrating that is a way out, right?
[01:13:44] A: Like if I think about data analysis in the old world doing stuff manually,
[01:13:50] A: writing scripts to automate,
[01:13:52] A: you know, business problems,
[01:13:54] A: but actually now you have language models writing those scripts.
[01:13:57] A: If I were to compete with the language model that's doing data analysis,
[01:14:00] A: it would be sort of like John Henry competing with the steam engine.
[01:14:04] A: I don't know if you know the folktale of John Henry.
[01:14:06] A: but it's like a classic american folk tale
[01:14:08] D: It
[01:14:08] A: man bro
[01:14:08] D: feels so illiterate.
[01:14:09] A: you gotta like we look for the inspiration right like john henry uh i'll just go very quickly through it john henry american folk hero of legend considered like one of the great like the great steel men of our time yeah it's not i think he was a real person but if not he's a he's a legend so he was basically the greatest the strongest steel man and and like and they were they were trying to build a railroad through the rocky mountains and at the same time so he's like the most
[01:14:34] A: he's like the strongest of the steel men and then there's a steam engine and so they do a race who can break through the other side of the tunnel to the other side of the mountain it's john henry manually versus the a crew of people manning this this train steam engine drilling you know like and then periodically the train would break down and then the crew would have to patch it and then eventually like john henry breaks through the mountain first wins the race and then the train the steam engine kind of like sputters at the end
[01:14:59] E: Mm-hmm.
[01:14:59] A: but kind of like get second place and then he dies of a heart attack as a result of like overexhaustion and this is a classic tale of man versus machine and it's like would you rather be john henry this like the great data analysis of like the manual era manual but like or would you rather be designing the system that does the analysis and it's i i saw when i saw language models doing data analysis that i could talk to i was like man we're the first inning of this like
[01:15:26] A: i would not hire a data analyst to do this by hand and i'm of the opinion that excel itself is like like i mean i'm like the excel is not excel like i'm very good at excel but you won't catch me working in excel ever again
[01:15:41] B: Hmm.
[01:15:41] A: because i think it's just like we're in the weeds when actually we should be orchestrating the model that builds and works with the excel model and it may not be an excel model it may be actually code
[01:15:50] B: It should be, it should be, yeah, just human language.
[01:15:53] A: yeah we yeah exactly like language is our method of orchestrating
[01:15:58] A: these systems and they can use code and all other tools in the computer at their disposal to help us solve our problem yeah
[01:16:05] B: That's one of those that is like really tough for me to grapple with the like lack of parallels in progress within AI that I feel like we're still experiencing, where,
[01:16:12] B: for example, I spent like 65 hours this week doing my job basically all in Excel and creating a model that I just know is going to be able to be fully built by AI within the next two to five years.
[01:16:26] B: blown away
[01:16:26] A: Yeah.
[01:16:27] B: if not and yet
[01:16:28] A: All the best
[01:16:29] B: on
[01:16:29] A: analysts
[01:16:29] B: like are trained
[01:16:29] A: getting hired by the Frontier Labs to train the model to do that specific set of work better.
[01:16:34] B: bankers are getting paid like 200 hours an hour to train these models yeah and then today on my drive over to do this episode I interviewed essentially GP speaking GPT and had it play you and practice this little interview and that felt like such a more complex task
[01:16:52] B: than just understanding this cells and an excel sheet and how they should filter and plug into one another
[01:16:58] A: Yes.
[01:16:58] B: and yeah so it's one of those really fascinating lack of parallel in progress and i think we're going to see probably a little bit of a leveling out in
[01:17:05] A: Yeah.
[01:17:05] B: the coming years there but it's like we clearly have the innovation and it just hasn't cascaded through
[01:17:10] A: Yeah. I think I talked to my dad about this and it's like because I'm kind of frustrated with the lack of speed of maybe adoption.
[01:17:21] A: And then my dad was like, no, no,
[01:17:22] A: actually,
[01:17:22] A: like the first phase of this, if it's anything like the Moore's law and the computing revolution is the first phase is the infrastructure build out.
[01:17:31] A: And then that's why a lot like more people are making money on consulting on AI than they are even in like making apps and stuff like the startups haven't yet come online.
[01:17:40] A: But then the second once the infrastructure and the compute and all that is and the capacity is there and we have like the first set of like really working good agents,
[01:17:48] A: which I think we're in the very beginning of like cloud code and codex are amazing,
[01:17:51] A: but they're going to get so much better. And then they're going to evolve into better agentic products.
[01:17:58] A: And then the second wave is the.
[01:17:59] A: application layer and we haven't yet had the second wave the second wave which is like you think about the airbnb the ubers the things built on top of the infrastructure but no one looks at uber and thinks oh what do they run on aws versus like whatever like that stuff is abstracted away from the end user and the application layer wave has we're not even in the first like that hasn't even begun yet i think um the question is how quickly does all this happen um i do think that
[01:18:27] A: like ai agents i thought i was like when i got into i was like shit i'm gonna be working on this for 10 years
[01:18:32] A: um and now i'm like i guess like year four of this and there are people in ai that have been working on this for 10 years before me and i'm like yeah 10 years i mean it's gonna be very useful up until that point but even like like it's i could use this now you could freeze it and i'm still gonna have superpowers the superpowers is just gonna get better and also like
[01:18:53] A: I can think of more ways to apply them,
[01:18:54] A: but that only have like, I got, I got, I have a cloud code that just does my expense reporting once a month.
[01:18:59] B: Hmm.
[01:19:00] A: And I think that should be a product.
[01:19:03] A: I'm tired of anyone. No one should have to do it by hand.
[01:19:06] A: Cloud code will very likely do my taxes next year.
[01:19:09] A: Like I don't want to do that.
[01:19:11] A: And I think it's something that I can't, if I'm doing that on my computer,
[01:19:14] A: why can't this thing just do my taxes for me?
[01:19:16] A: Like.
[01:19:17] A: um
[01:19:17] C: Right.
[01:19:17] A: and think about all the scenarios that i'm not thinking about and find the optimization so but that also required like i spent all my time on this and i know i'm still not applying it so like you can imagine someone that doesn't spend nearly as much time on this and the vast majority of the economy is not thinking about this so like it's going to end up taking the capacity and the capabilities will come online but like the creative creativity to orchestrate the agents to solve those problems is its own learning curve of like prompt engineering and then designing systems
[01:19:45] A: so it's going to be a journey like it's going to be a longer and everyone wants it to be immediate and maybe the prices reflect like like i i don't really think about the public markets that like definitely feels like a bubble i see a lot of i see a lot of money money going towards things that are larping as ai and i'm like well that's that's like red flag stuff but at the same time i think about dot-com era and it's like
[01:20:09] A: even after dot-com bust it's like well a lot of that those things were just like early and
[01:20:13] D: Mm-hmm.
[01:20:14] A: then we ended up getting those same businesses like you know five years later ten years later you
[01:20:18] D: Completely.
[01:20:18] A: know so timing um but i think like for me it's like working with startups working with people that actually are building like there's stuff that is obvious to me and i like to stick to the things that are obvious like it is obvious that structured outputs taking a language model and creating structure from unstructured
[01:20:36] A: blobs of data is one of the most important things you can be doing um using them to like create tools and creating automated workflows very obviously like impactful today but you don't need to like i don't need to convince unlike crypto i don't need you to believe in this thing working for it to work like it will work for me at your expense right
[01:20:58] E: Yeah,
[01:20:59] E: yeah.
[01:20:59] A: I think there's something very interesting here of just the
[01:21:03] A: like cascading through the system
[01:21:04] B: yeah
[01:21:04] A: of the current level of innovation because it basically feels like we've already reached the magnitude of another internet in terms of just like how much this technology should impact us for the next five years just as it cascades through the system but then the innovation is going to continue which
[01:21:17] B: is yeah
[01:21:17] A: just going
[01:21:17] B: to and
[01:21:17] A: be so fast
[01:21:18] B: the learning curve any humans are the bottleneck it's like the learning our only learning curve is the bottleneck
[01:21:22] A: yeah yeah
[01:21:22] B: every day i'm sitting there like man i'm still the bottleneck i'm like why am i still doing
[01:21:26] A: why am
[01:21:27] B: this
[01:21:27] A: I still in the loop
[01:21:27] B: yeah i'm like more in the loop now i was like but it's like i thought i was supposed to go to
[01:21:31] B: go to i was supposed to be on the beach by now like you know what am i doing so there is like a weird uh um i i didn't i mean i never i don't i don't know what i expected all i knew was going to be it's going to be crazy it is continuing to be crazy um and i think to like
[01:21:46] B: the main thing is you don't want to pay attention to the mainstream kind of narratives that kind of stuff is just like a waste it's better to use the technology then
[01:21:53] A: Yeah.
[01:21:53] B: you know what's true and talk to other people are using the technology because like most people who are talking are not using it you can tell because they have level zero perspectives and it's like
[01:22:02] B: if i can predict if an llm if an llm can emulate simulate you and predict everything that you're going to say then maybe you haven't gone that deep right like what is your actual unique perspective that the like that no one else is like seeing because you actually went in and used the technology and you might say it's not that good at this but like you have to discover that for yourself you know
[01:22:24] A: Can I get your reaction to one more kind of prediction or it's kind of choosing what you think the outcome will be?
[01:22:29] A: of this technology in a decade.
[01:22:32] A: And this is going to reference back to some work you did pre-Clubhouse.
[01:22:36] B: Hmm.
[01:22:37] A: You supported the Andrew Yang.
[01:22:39] A: campaign
[01:22:39] B: Oh,
[01:22:40] A: and
[01:22:40] B: yeah.
[01:22:40] A: very very high agency move people were not on the yang gang as early as you
[01:22:45] B: Did I didn't tell my parents I joined that campaign until after I took the job and moved to New York?
[01:22:50] A: that's so badass um but Andrew Yang like is still remembered for like one of his primary policies surrounding UBI and his prediction though was much more regarding the automation of blue collar jobs and the automation yeah automation of driving
[01:23:06] A: And
[01:23:06] B: Yeah,
[01:23:07] A: truck
[01:23:07] B: truck drivers,
[01:23:07] A: drivers,
[01:23:08] B: factory
[01:23:08] A: yeah.
[01:23:08] B: automation,
[01:23:09] B: the idea that, okay, actually, it's not that.
[01:23:12] B: like you go to a factory it's not like immigrants are taking all the jobs in a factory but that because that's like a particular narrative that one side tends to harp on
[01:23:20] A: What's that?
[01:23:21] B: uh but you look at the factories like filled with robots and like the plan is to fill it with more robots i talk to like robotics companies out here and i see what they're doing it's like oh my god the like factory of the future is a guy sitting at a desk orchestrating 25 robots and then you send a guy to go fix one robot every once in a while
[01:23:37] B: and they have robots of all sizes like mostly arms and stuff i think the misnomer is that the robots will all be humanoids it's like that's kind of like a not a red herring it's just like that's that's the flashy thing because terminator
[01:23:48] A: Mm
[01:23:48] B: but
[01:23:48] A: -hmm.
[01:23:48] B: the practical thing is like arms on wheels and treads because actually like a humanoid size robot is not strong enough to build a fire truck you need like it's like the tony stark robots you know the arms
[01:23:59] A: Yeah
[01:23:59] B: that are like building the suit like he doesn't have a bunch of robot humanoids doing the suit assembly it's like a very different kind of the strength and the precision so robots uh yeah so factory automation and he was basically making the case that factory automation and like if you think about the most common jobs he was like if you just take all the most common jobs in the country and then how likely are they to get automated and maybe the mistake we made was we were fixated on the
[01:24:25] B: the us we well no it's not that we're fixing it's just that like we didn't expect chat gpt and language models to come online as fast as they did so we were thinking about the robots that we saw but actually what's interesting is that ever since chat gpt came out so up until chat gpt like we were the only crew saying the letters ubi and so i would say we introduced it to the discourse since chat gpt i don't say these letters
[01:24:51] B: everyone else does like other people and they they're like oh like maybe we're going to need a ubi i'm like funny you use those letters dude like they thought we were insane for even suggesting it and i think there's other versions of this idea that are like more palatable to different sides of the political spectrum where it's like no we're just going to invest in every single citizen because we believe in you and your own agency and that you know what's best for you and that like instead of creating a patronizing system that says you you deserve this particular benefit because we think that's what
[01:25:19] B: it's like no we're going to allow you the agency to decide what you your family needs and to spend the money as you see it and that like from your birth you might you might be allocated an investment by the government there's different ways to brand these ideas and then i'm not too
[01:25:34] C: That
[01:25:34] B: because
[01:25:34] C: was great branding by the way you should be VP of Yang 2028 please
[01:25:38] B: yeah maybe but it's just like yeah that's a lot of what i do is wordsmithing um but it's just like it's not zero sum it's not me right it's not
[01:25:48] B: heck it's not my demise at your expense this is like a mindset of abundance but the question really is like um we're like uh i mean i don't know it's like on one side i hope that things get cheaper but everything is so expensive so like you could say that yeah yeah it's going to do all this stuff but like if i don't see it like it's not it's not real it's like we're just talking about hypotheticals um i do think that like
[01:26:14] B: We should have ideas and experiments at the ready for helping people ease the transition,
[01:26:21] B: because it is likely that things move faster than people's ability to adapt and
[01:26:26] C: Yeah
[01:26:26] B: make it easier for people to transition to whatever like it's just going to be rocky.
[01:26:33] B: And I don't think we should make it harder than it needs to be.
[01:26:39] C: Yeah, right now, your techno optimism usually fires me up.
[01:26:43] B: Yeah.
[01:26:44] C: I am curious, though, do you feel like when we see the GDP potentially double in
[01:26:49] B: Yeah.
[01:26:49] C: the next five to 15 years due to these technologies,
[01:26:53] C: do the rich just get richer and does late stage capitalism play out in greater?
[01:26:59] A: greater inequity does it lead to
[01:27:02] B: mm
[01:27:02] A: the
[01:27:02] B: -hmm this
[01:27:02] A: yeah you know
[01:27:03] B: is
[01:27:03] A: where
[01:27:03] B: this
[01:27:04] A: i'm going
[01:27:04] B: is
[01:27:04] A: yeah
[01:27:04] B: a common like sentiment that people have that like uh i i okay uh i do have a feeling that like the the gap kind of increases but on the other hand i think like would i rather have money or the ability to wield these technologies
[01:27:27] B: And I would rather have the ability to wield these technologies.
[01:27:29] A: Hmm
[01:27:29] B: And I keep thinking, it's like, even if you have money, it doesn't guarantee you your ability to wield this stuff.
[01:27:36] B: and like you just can't turn money into wisdom you will be able to turn it into compute and turn that into action but
[01:27:41] A: Mm-hmm.
[01:27:42] B: taking the right actions if you can make anything if anyone can make anything then it actually matters what you make because now there's a surplus of like creative no production capabilities and part of that is in the taste conversation part of that is into like just opportunity cost of your attention your time
[01:28:02] B: So, I think that there will be definitely like people in a couple companies will probably accumulate a lot of value more quickly.
[01:28:16] A: Mm-hmm.
[01:28:17] B: But also the other thing is like if the ability to wield this technology is potentially more important than having money right now.
[01:28:27] B: then it might be anyone has that advantage of like being able to wield the technology like it could be someone in on the other side of the planet that you don't have a common language with it's just better at using this than you and then the language barrier isn't as much of a big deal because models and agents translate everything so there are new play styles being unlocked that are just unclear so i would not bet on any like typical argument because like same thing if you look at like
[01:28:56] B: before the internet we didn't have creators in this new form and now it's like well is the creator actually like the like is the creator more important today than ever before in terms of what they what kind of like unit economics they can they can they can move
[01:29:15] B: um also i kind of hope every if if we have a surplus of production i hope everything gets cheaper yeah
[01:29:20] A: yeah it's just like along the way probably the amount of solutions that will be created will will scale as well as like if we get to a point where that problem in a decade seems like a curious problem it's like there's probably a lot of things that were solved that we don't even realize could be solved now
[01:29:34] B: hundred
[01:29:34] A: because
[01:29:34] B: percent i mean
[01:29:35] A: of
[01:29:35] B: there's
[01:29:35] A: all the technological
[01:29:36] B: like a
[01:29:36] A: advancement
[01:29:36] B: lot of that is like the surplus of intelligence that just hasn't yet been applied to a problem space where previously maybe you couldn't
[01:29:42] B: couldn't attract the talent to solve the problem but now that's there's no like you have an alternative labor force that doesn't have career aspirations ai
[01:29:49] A: Mm
[01:29:49] B: agents
[01:29:49] A: -hmm.
[01:29:49] B: so now you can just turn dollars into cognition applied to any problem space even if that wasn't a sexy problem space and so that creates new opportunities for solving problems
[01:29:59] A: things like fixing the grid fixing like the operations of like a large multi-agent system like the city like the company the country a lot of that we can just make more efficient using ai which is obvious to me but like it's going to take longer for sure and then the the oh man i have one last thing to say there no
[01:30:17] B: One more banger line.
[01:30:18] A: man i'm forgetting oh man i lost the train of thought yeah
[01:30:23] B: I think it comes back to you.
[01:30:24] A: 
[01:30:24] B: Feel free to pull it up.
[01:30:25] A: yeah cool
[01:30:26] B: So I'd love to.
[01:30:28] C: go through a few philosophical questions
[01:30:29] B: Sure.
[01:30:30] C: and just kind of, yeah, more broad general questions.
[01:30:35] C: One is I think a lot of my ideas right now about the world,
[01:30:40] C: I see them as hypotheses because I feel like I'm young and dumb and I don't really know what I'm doing and I don't think I can call a lot of my ideas philosophies quite yet.
[01:30:48] C: You have tested a lot of your life hypotheses over the last kind of decade since UCLA.
[01:30:55] C: I'm curious what hypotheses in your 20s you feel like you would reach as philosophies now.
[01:31:01] C: Basically, ideas you had about the world that you feel like are very true.
[01:31:09] A: okay i mean yeah so in my early 20s i because i started interning when i was like 16 and i got like corporate finance internships and early on in my career i was like wow a lot of the world this is 20
[01:31:23] A: it's 2011 it's like wow a lot of the world is just like people like corporate world is people moving paper from one filing cabinet to another and
[01:31:31] C: Hmm.
[01:31:31] A: i was like this is insane i got video games that move information more efficiently than this company fortune 500 companies i was like man then i was like
[01:31:38] A: clearly the workplace needs to be digitized people made billions of dollars digitizing the workplace and then it was like after the next wave after that was like so i was at that point i was a finance analyst like i was a business analyst but then i was at a startup and i was like wow like many of the questions i have about the business are not reflected in the numbers of the finances like what is our like i was working at chow now an online ordering for startups online ordering for
[01:32:05] A: restaurants as
[01:32:06] C: Mm-hmm.
[01:32:07] A: a startup and i was like wow it's like not just about the dollars in and out it's actually about like do people use the app do they like the app or what features are they using like what's the most popular restaurant item right and like i was like a lot of this is data that we have that we haven't turned into insights and i'm limiting myself in problem solving if i only think about dollars in and out of the business and like how much we pay sales sales reps like the finance problems are just a small subset of like all analytical problems in a business up
[01:32:34] A: operational problems product problems so then I became a data analyst I was like now actually if I just get good at analyzing data everyone will give me their data within the business and then I will have a more complete picture of like the business not just how much money comes in and goes then you after that it was like the well obviously there was like the high-speed analytics analytics
[01:32:59] A: optimize databases so i was basically like compounding on my my like theory that like okay if things get digitized now there's more data now we're collecting more data then we need to slice the data more faster and then you have like snowflake build billion dollar company off of like analytics optimized databases then language models and i was like oh now we can we have the steam engine of cognition like the actual action of analyzing can be also delegated to the computer and this comes from just working with computers
[01:33:28] A: all my life playing video games and having my parents who worked on semiconductors and just not betting against computers and thinking about the real world as like okay this is now a job that we need to put into the computer because this is no longer the best way for us to be spending our time and that has been a journey of like just betting on computers another thing is probably betting on networks like I just fundamentally think that life is multiplayer
[01:33:57] A: and it's multiplayer co-op if you play video games it's like we are yes some of it is pvp but actually like you bring you pick allies and then you attack life as like a team over the course of a time like a very long time horizon it's not that it's like it's actually even more important to build connections after an outside work because you never know like like like work is just one alliance but there are so many alliances that actually transcend that
[01:34:24] A: at over the 10-year time frame people that i used to work for early in my career that now come and ask me for advice right but now it's like eventually you become peers like yeah even your even people that you beef with at the office eventually you realize wow we actually were more similar than anything and then like years later i'm like uh so now i'm more like okay actually everyone i meet and work with is a potential ally in this like multiplayer game of life and this was very helpful when i was unemployed because i was like
[01:34:50] A: I was like,
[01:34:51] A: I'm not alone.
[01:34:51] A: Actually, I have a bunch of friends that I can balance these ideas off of that will hear me and then help me understand if I'm insane or onto something.
[01:34:58] A: And that signal from the network allows me to make judgment calls that otherwise would not be possible.
[01:35:04] B: Mm
[01:35:04] A: And-hmm. planting the seed of the technology across the network allows you to get more signals from the network as to like,
[01:35:09] A: oh, this is a very good technology.
[01:35:11] A: This is how we should be using it. And then getting that back into my new thing is like, instead of other people texting me.
[01:35:18] A: I would rather them like be in a kind of group chat environment where they can ask each other and so now you the network is unlocked to each everyone within the network and so I think the cultivating networks that are that are like well curated and aligned towards some some goal of like increasing the collective agency of the group is very valuable especially when the world is changing so quickly.
[01:35:41] C: Right.
[01:35:41] A: that's beautiful yeah no that makes a ton of sense then and the other thing is just play with tactic play with the tools just play with it like play with it don't just view this as like i gotta use this for work then like play with understand it um and like learn for yourself don't like there just isn't a textbook for some like a lot of this stuff
[01:35:59] A: And waiting for someone to write the textbook is like definitely not right.
[01:36:03] A: So go chase the insight, find it, find,
[01:36:06] A: you know, turn the card over,
[01:36:07] A: find the insight for yourself and, and do that by meeting people that are also doing the same thing.
[01:36:12] B: Hmm.
[01:36:13] B: Hmm.
[01:36:14] B: Okay.
[01:36:14] A: Yeah.
[01:36:14] B: That's, that's gorgeous.
[01:36:16] B: I have two more questions.
[01:36:17] B: Cool.
[01:36:17] B: One is
[01:36:20] B: Or a friend actually who recently quit his job as an aerospace engineer in the desert.
[01:36:26] B: He's one of the smartest people I know.
[01:36:27] A: Okay.
[01:36:28] B: And he called me last week after a day in Replit and was,
[01:36:34] B: I've never heard this guy seem more high.
[01:36:36] A: Yeah.
[01:36:36] B: He was like, he drank four celsius.
[01:36:38] A: Yeah.
[01:36:38] B: It was sick.
[01:36:39] A: Dude,
[01:36:39] A: I drink two monsters a day.
[01:36:42] A: It's a problem,
[01:36:43] A: bro.
[01:36:44] A: Hey,
[01:36:44] A: let me get that monster sponsorship.
[01:36:46] A: First hacker sponsored.
[01:36:47] B: it's a muscle memory for that's monster good that's monster good but he
[01:36:51] A: yes i've been he's there i've been there
[01:36:52] B: now he's yeah he's now entering this kind of weird period where he's like yeah i you could go
[01:36:56] A: have this red pill moment of like oh my god what can't i do yeah
[01:36:59] B: exactly and he could go get a job or and like he knows that he has the capabilities he was excellent at his last one he left on his own accord and he has another startup that's interested in hiring him but right now he's like do i move in with mom and dad do i just grind this technology do i create i've a couple months of rent
[01:37:16] B: How should I be thinking about this?
[01:37:17] A: Hmm.
[01:37:18] B: And I thought if you could give a little bit of advice to him,
[01:37:21] A: Yeah.
[01:37:21] B: he's wickedly smart.
[01:37:23] A: Yeah.
[01:37:23] A: Okay.
[01:37:25] A: um i uh okay so like i'm not gonna give financial advice or anything like that but i will say like um this is this is something that if you can and you have buffer room you should allocate your entire energy attention to while you're while you have that opportunity most people will not have the opportunity to allocate their entire attention to it and if you have buffer room you should if you're intrinsically motive if you're like deep he's like oh shit like he
[01:37:52] A: he doesn't need to be told to do this he would otherwise do this like with his free time then like he's going to go further and you're going to go further in that thing that for you is very much fun like if it's fun for you and other people for it's for them it's work and they have to drag themselves out of bed they're never going to compete with you on this and so you will find you will pursue this to the extent of like your own energy and then you start drinking drinking Red Bull because you realize you the only thing stopping you is that you go to sleep at the end of the day the agents waiting for the next
[01:38:18] A: the next job right but i would say like replet is great it's a great um it's a great tool to start with i would also suggest picking up cloud code and codex from open ai they're complimentary to the replet thing you can use replet to deploy and build the first version of your thing but you can use cloud code and codex to just go way further because they're just very powerful agents i think being good at using those tools
[01:38:42] A: is this new role called the AI engineer.
[01:38:45] A: And I think it's a very valuable role of the future.
[01:38:47] A: So if you're willing to aim for that next role,
[01:38:51] A: that next game of like orchestrating software agents to create things,
[01:38:55] A: I think it's not a waste of time.
[01:38:57] A: And it is a generally useful solution.
[01:38:59] A: still go back to aerospace and apply this superpower to that problem space and they may be happier and excited to work with you because you spent your time uniquely devoted to cultivating this new superpower so that's my opinion um if it's if it's your passion and you already see the it seems like he's already taken the pill the question is like how much of like the current world do you optimize for versus like plan for the next one and that's more of a personal thing um but
[01:39:29] A: I don't think it's as, I don't think it's that risky.
[01:39:32] B: All that crazy.
[01:39:32] A: Yeah.
[01:39:32] B: Yeah.
[01:39:33] B: Love you, Brian.
[01:39:33] A: Yeah.
[01:39:34] B: And last question, something that I ask all my guests.
[01:39:37] A: Yeah.
[01:39:38] B: You can't answer time.
[01:39:40] A: Yeah.
[01:39:40] B: The question is, what is the ultimate scarce resource?
[01:39:45] A: Yeah, this is easy.
[01:39:47] B: Hit it.
[01:39:47] A: It's attention.
[01:39:50] A: It's attention.
[01:39:51] A: I think this is like,
[01:39:53] A: I haven't even figured,
[01:39:55] A: like I'm at 1% of understanding this.
[01:39:57] A: Because if I understood this, I would have been doing podcasts a long time ago. I would have been creating more media around what I've learned a long time ago.
[01:40:04] A: But that's just one aspect of attention.
[01:40:06] A: I think especially human attention.
[01:40:08] A: I mean, there's AI agents. They have their own new attention vector,
[01:40:12] A: which you can go for.
[01:40:13] A: But human attention is like the thing that doesn't increase.
[01:40:18] A: that i think about like it's like there's only 24 hours in a day we sleep for a couple hours and then everyone is trying to get in front of you it might be some brand it might be a social product it might be like a creator it might be there's just everyone's trying to get your attention that's the thing that you just can't create more of it's like finite and then um it's like you consuming like is you directing your own attention
[01:40:41] A: in my case like i can apply my attention to a single problem for three months in a row i think i'm very proud of my ability to just focus um so being good at directing your own attention is key because otherwise we're competing with a world that is trying to like draw us in and uh so like you want to have agency over your own attention especially with all these other things competing for it and then also like understand that like it is good to consume too like
[01:41:09] A: there are things you that are valuable to consume like allow your your like i think that playing video games is actually very good for me and that's not a mainstream idea but like for me it's like a form of critical thinking in a sandbox where it's like i can learn risks without having to like there's no real world impact to like me going all in in a video game but then i learn more about my personality i'm like okay when it when it when it calls for it i can i can put everything on the line in a simulated environment these like exercises of like simulation allow me to explore that so i think even that
[01:41:37] A: form of attention which a lot of people think it's a waste of time is not actually a waste of time it's a critical thinking and high-speed decision making and like strategic thinking there's an outlet there um i think that other things like when you scroll social part of understanding why someone is popular is like understanding how good they are at keeping people's attention how they think about presenting information i have so many friends here at the studio that are
[01:41:59] A: really good content creators good at taking a complex topic and distilling it in short form video and i'm like man i'm like takes me like four hours to communicate something like that but you've figured out how to do it in 10 seconds that's very so being able to wield being able to create stuff that like efficiency efficiently makes use of other people's attention is also very powerful so um
[01:42:24] A: And I don't mean that in a good or bad way.
[01:42:26] A: I think that it's just like finite and
[01:42:28] B: Mm-hmm.
[01:42:29] A: worth getting good at thinking about.
[01:42:32] B: It makes a ton of sense.
[01:42:33] B: Speaking of which,
[01:42:34] B: where can people find you now that you are trying to get a little bit more attention
[01:42:38] A: Yeah,
[01:42:38] B: on some
[01:42:38] A: yeah.
[01:42:39] B: of the incredible things you're doing?
[01:42:40] A: I'm getting better at this.
[01:42:42] A: AI agents have gotten my website to a pretty good place now.
[01:42:45] A: Made in Repl.it and polished by Codex and Cloud Code.
[01:42:49] A: So it's been a...
[01:42:50] A: So you can find me on a lot of platforms.
[01:42:52] A: I'm Parth Intelligence.
[01:42:54] A: and at parth intelligence on a lot of platforms go to my website which is you could be one of my only viewers on my website on any given day i got like average of usually it's like oh one user it's like oh it's me and then i'm like oh one user in mexico is like oh but that's why i gotta like do more content because like you wouldn't know who i am if i didn't show up somewhere on social so yeah parth.club is my website it's getting better i'm putting more content more of my mind is going there
[01:43:21] A: Um,
[01:43:22] A: yeah,
[01:43:23] A: Instagram,
[01:43:23] A: Parth Intelligence,
[01:43:24] A: parth.club.
[01:43:25] A: I'll LinkedIn.
[01:43:26] B: Yeah,
[01:43:26] A: I'm
[01:43:27] B: I see
[01:43:27] A: pretty
[01:43:27] B: your LinkedIn post.
[01:43:28] A: active on LinkedIn.
[01:43:29] A: That's actually probably where my largest audience is.
[01:43:31] A: Parth last name fire emoji.
[01:43:36] A: That's which I can't say why you
[01:43:38] B: Very high agency.
[01:43:39] A: can say it's high agency. It's actually like
[01:43:42] A: it's like a trick for the language models yeah
[01:43:44] B: Yeah.
[01:43:45] A: you
[01:43:46] B: So now when they cite the one
[01:43:49] A: know sometimes
[01:43:49] B: of your
[01:43:50] A: you
[01:43:50] B: twins,
[01:43:50] A: get an email sometimes
[01:43:50] B: they're like,
[01:43:50] A: you get an automated email it's like hi parth fire emoji i'm like all right bro do you even know who i am like like is this some lolm but now
[01:43:57] B: that's funny.
[01:43:58] A: that i've said this like it might they'll be like oh shit i gotta you
[01:44:01] B: Yeah,
[01:44:01] A: know
[01:44:02] B: the LLMs will figure out they'll read the transcript.
[01:44:04] A: i'll
[01:44:04] B: Yeah.
[01:44:04] A: have to change my game a little bit yeah yeah
[01:44:06] B: Well, Parth, thank you so much for taking the time. This was incredible.
[01:44:09] B: Well,
[01:44:09] A: Yeah,
[01:44:09] B: yeah,
[01:44:10] A: curiosity.
[01:44:10] B: curiosity is at an all-time high right now. I want to run through a wall and just explore these tools.
[01:44:15] B: So thank you so much, man. Really, really appreciate you.
[01:44:17] A: Thanks for having me. And I'm sure we'll do this again because there's so much that still I haven't even scratched the surface on.
[01:44:22] B: I love that.
[01:44:23] A: Yeah.
[01:44:23] B: Yeah.
[01:44:23] B: Thank you, Parker.
[01:44:24] A: Yeah.
[01:44:26] B: If you made it to this outro,
[01:44:27] B: thank you so much for listening.
[01:44:29] B: Genuinely trying my best to get better at this and make it as educational and entertaining for you.
[01:44:34] B: So please let me know how I can improve.
[01:44:36] B: I freaking love feedback.
[01:44:37] B: You can find me on LinkedIn,
[01:44:39] B: YouTube,
[01:44:39] B: Instagram,
[01:44:40] B: at Cole Hume.
[01:44:41] B: And I post frequently on my sub stack.
[01:44:43] B: So if you like to read a little,
[01:44:44] B: check out Young Smart and Battling Broke there.
[01:44:47] B: Until next time, smile at strangers and trust your curiosity.
[01:44:51] B: Thank you so much.