00:00
Again, I've been in software for thirty years now doing startups pretty much, my entire professional career.
00:05
The only time I've I've felt like
00:08
Like, how
00:09
hard palpitations, kinda like Sean kinda open with us. Like, there's this party going on next door and I'm here knitting. Right? It's like, This is, like, too big to ignore. I think it's the single largest opportunity and biggest, kinda,
00:20
tech paradigm shift we've seen, since the internet originally came out like. Mobile was big, but there was a discreet set of use cases. Like, when you put a camera on a phone, when you put a GPS device on a phone, a bunch of consumer apps, like Uber and others, came up and that was awesome. Right? But it was not, like, this impacts everything like the internet did. Right? It's like, okay. There's some businesses, some new opportunities, lots of good things, lots of money made, lots of startups, Awesome.
00:44
This is an order of magnitude bigger than that.
00:55
Alright. What's up? We have Dharmesh back, Dharmesh, who is cofounder of HubSpot, and,
01:01
multiple time guest on the pod. One of the one of the fan favorites. You're back. And I don't know what we're gonna talk about because usually
01:09
we have these little, like, cheat sheets where it's like,
01:12
three to three to five bullet points of
01:15
interesting ideas,
01:16
topics,
01:17
experiments you've been running, things like that. And I'm sure you have those, but I don't have the cheat sheet. So where do you wanna start?
01:24
Well, I say we start with
01:26
generative AI. Because I don't know if you've heard, but there's this thing called chat GPT. I get this question from my friends and family all the time. He's like, Dimesh. Have you checked out this chat GPT thing? I'm like, really, do you even know me? Like, of course, I played with it. I've been obsessed,
01:41
ever since it came out. So Did did you see I wanna talk about your topics, but really quick, did you see did you guys see this that so Sam Altman
01:49
co founded Open AI. He's, like, the the man in charge I read an article where he was quoted as saying, like, I have enough money and I don't want equity in the company. And I don't know if I entirely believe that. But that's wild, if true, because it could be one of the more valuable companies in the world, the next ten years.
02:07
Yeah. He didn't I don't know if he said it. Like, he didn't say it on the record on the record, but the person reporting, it said, Sam reportedly has no equity in the, the for profit version of OpenAI
02:17
because he's already wealthy enough and didn't want to, didn't feel like he needed to or didn't want to, didn't want to have that clouding his judgment when it came to this. And, like, this is pretty you're gonna bet what what one private company, what one private startup
02:31
is most likely to become worth a trillion dollars or more.
02:35
I think at this point, there has to be open AI right now. That, like, dumbass, would you would you disagree with that? It it'd be up there the top three. I can't I honestly can't think of
02:44
who else would rank higher in terms of probability of being disabled. And I don't know what two and three are. Yeah. Well, who are the other two and three, you know?
02:53
No. I don't know. I was like
02:56
no. I I would say that one's the transformative one. Right? I think,
03:00
you know, a lot of the kind of Tesla gains
03:02
We've sort of seen. I'm not sure if there's, like, big surprises left. It's like, okay, they will make it better. They'll get to full self driving, and and we'll see kind of progress on that front, but in terms of just raw valuation,
03:14
it's the wild card. OpenAI is the one that
03:18
could actually
03:19
pull that off. They get they they get a lot of shit because people are saying, like,
03:23
you know, Elon kind of stoking this fire. Like, how did this nonprofit go to a four pro how did this open sourced nonprofit company
03:31
research lab basically
03:33
become a four profit
03:35
semi closed,
03:37
you know, the company. And I think that's people are gonna make people are gonna take shots and make fun of OpenAI because it's clearly the new powerful thing that's so some people are gonna say how it's gonna ruin the world and how terrible they are. But he did give a there was a a story that came out with a good explanation, which was
03:54
They were burning a lot of money in the research lab.
03:57
They needed more money.
04:00
Elon was gonna be the big back So he was gonna pledge or commit a billion dollars to it. He,
04:07
and then he was like, no, I don't like the way this is going. Like, Google is way ahead.
04:12
And,
04:13
I'm gonna take over Open AI and, I'm gonna right the ship here. This is the this is what k. This is the story that came out. Yeah. They haven't nobody's clarified if this is true or not, but it came out in, I think, plot the platformer,
04:25
publication. And so they go, Elon tried to take it over Sam Altman and the CTO Greg, who who was the former CTO of of Stripe,
04:34
they them and the group that was in charge of OpenAI rejected that. So Elon's like, basically, like, I'm taking my ball and I'm going home, have fun playing basketball without the ball. And he's like, I so he took his funding and he left. So he a couple months later, the he left Open AI, said, and the the public story was, oh, it's a conflict of interest with Tesla,
04:52
because they're also working on AI.
04:54
But he reneged on his funding. And so now they had this huge shortfall in funding that they were gonna have to cover. And so their solution was Let's create a subsidiary that's a for profit thing that we can raise money into because we're not gonna get, you know, where else do we get a, you know, hundred million dollars or a billion dollars of donations here.
05:14
And so they they did that. They raised money in that, and then they capped the profits of that company. So that was kind of their explanation,
05:21
which is a little bit less
05:23
devious
05:24
than people make it sound. They're like, oh, they tricked everybody by going from nonprofit to for profit to all the profits, which is I think how people perceive it today. Yep. I yeah. I don't
05:34
I know the details that have no insider knowledge, but, Wait. I thought you have, like, a billionaire chat group or, like, every billionaire just kinda says, the back channel of what's going on. Do do you not have, like, a billionaire WhatsApp? Have that, but I don't have any insider knowledge from that particular chat group.
05:49
It
05:50
my my sense here is that, you know, building large language models that's open ads doing is this, like, supremely capital intensive, which is rare for a software company, which is what they are. So it's expensive they needed access to capital.
06:04
I think they structured it such that it does cap the profits. I think they've done Like, if you had to do that kind of low, we're gonna have to spin off and have this for profit thing.
06:12
They did it well, and, and I could be wrong, but Sam Altman seems
06:18
Like a reasonable, rational,
06:20
non evil guy. I mean, he's he's a capitalist. Fine. And I mean that in the most positive way possible. But, I mean, I don't think he was
06:29
out to mislead anyone. I think he's trying to So there's a bunch of ways we can go with this AI thing, but I wanna share something funny. So I based cleared my calendar this whole week and I just treated it as AI week because I was like, dude, I can't I can't just sit here and I hear the music at this party just bumping at the house next door. And I'm over here knitting. And I'm like, I gotta put this down. I gotta go see what's going on at this party. And so I cleared my calendar and I just spent every day this week, just messing around with AI tools, just getting to play play with it for myself. That's how I learn is by, like, just messing around and and and trying to experiment and do things. I wanna share with you guys something funny. Basically, I stitched together a few AI tools. I was like, let me make an intro song for the podcast.
07:10
Using AI. So I went on chat g b t, and I told it, I said, oh, this is all I wrote. Write an intro rep for our podcast, my first million.
07:17
Our key phrase is no small boy stuff. Okay. So here's it it gave me a full wrap, but I was gonna read you the chorus. So he goes, here's how it goes. It goes, no small boy stuff. We on that grind. My first million is time to shine. We talk a big money. No pennies, no dimes together. We climb one step at a time. And it started so it gives us this this great rap that's on, on on brand. And then I took that and I found this guy, Roberto, who had made this demo where he
07:43
turned his voice wrapping into Kanye.
07:46
And I don't know if you've seen this, but it got like a million views. It's this incredible thing where and he's like, Yeah. Dude this crazy. He's like, I didn't make this. He's like, I was just on Reddit, and I saw that someone uploaded a Kanye voice model. So I clicked it And he it literally the thing is, and I I should make I should make a YouTube video about this, like, just how to do this one process. But basically,
08:06
It's a Google collab folder, which is just like a Google's little coding interface. So you don't have to do write any code. It just here's the here's a place to run the code. And then it's a link to mega upload.
08:16
And then the mega upload is where he hosted the Kanye voice model. And so all you do is you record yourself doing what I just did.
08:23
And then it turns into Kanye West wrapping it. And it sounds exactly like Kanye. It's amazing. I got a fantasy
08:30
that's beautiful. That's dark and twisted.
08:32
But I attacked the whole religion, all because of my ignorance. What was I thinking? That was some bitch shit. I lost adidas, but I'm still And so, and it takes literally like fifteen minutes to do the whole thing.
08:44
There is no
08:46
there was like nothing else to do. It was so easy. It was crazy. Are we allowed to use Kanye's voice for I think you're, like, a ten second thing. It's not a not a problem. It helps fight gets sued. Who cares? None of a none of us here would bother would worry about that. So well,
09:01
Dharmesh will. So Dharmesh is the, CTO cofounder of HubSpot, by the way, which I don't know how big the team is now, but, like, somewhere between the three and five thousand mark, the Well, over seven thousand, but Oh my god. Seven thousand. My bad. And the market cap of the company varies from fifteen to twenty five billion over the last couple years.
09:21
So you have like and and you're like constantly tinkering. So you have word which is a project that you made that I think you said had millions of people playing it.
09:31
You have an interesting insight in this just from your perspective at HubSpot and you're actually using all this stuff. What excites you about this, generative AI thing? And you also say that, like, you're like, Why is Bill Gates excited? That's a great that's a great headline. It's it's in the, MDDB, MDB, Doc Sean, and, like, immediately, I'm, like, Okay. You've got me interested. Anytime a headline says, why Bill Gates is buying farmland, I click?
09:55
Let's let's a couple of things. I think that
09:59
The listeners and viewers I think would be interested in benefit from. One is,
10:04
most of the discussions around generative AI
10:07
around color generation of either text to text that says, oh, write me a blog post up three hundred words on this particular topic, or text to image, left these dali two or mid journey or stable diffuse or something like that, which are great use cases and they kinda capture the imagination because as humans, we are very impressed
10:24
when when software can actually generate or create something. And that's awesome, and then not to take away from that. But there's a third use case that almost nobody talks about which is the ability to go from text to code.
10:35
And so what happens there is to say, okay, and what this leads to is the thing That Bill Gates is excited about. I'm excited about, is that you can take a natural language prompt that describes something and then generate paint that does that thing.
10:52
As a result of which, you can now build,
10:54
what I call chat UX or that that that term has been used before, but,
10:58
which is a chat based user experience for software. So right now, the way you use most software will gather to what it is web based or whatever. If a series of clicks and drags and touches and swipes, because you've got the thing in your head that you wanna do, and then you go through with your knowledge of the software, you could've execute the series steps at the end of it, you hopefully get the thing you want, whatever it was you were looking to accomplish with the software.
11:20
And that's what engineers like we would call an imperative model. An imperative model is you give step by step instructions
11:28
that says do this and then do this and then do this and then do this and then do this and then I get the thing.
11:33
What natural language allows us to do is use, what developer would call a declarative model. Instead of describing all the steps, describe the result that you want at the end of the thing.
11:43
And then the software does everything in between. So it's it's a difference between
11:47
having a junior intern that you have to explain. Like, I want you to go do research on this thing and this thing and come back and then give me the and then a senior person, you're like, You know, we're digging into this topic on Gernavoa, and I'd like a really well researched thoughtful thing that and here's the outcome we're looking for. That's Right.
12:03
Is it as simple as, give me the code for a website that looks exactly like Airbnb, but is red and is for cars or something like that? It could be something like that. It could be something more sophisticated. So we'll look at the, like, the HubSpot example.
12:18
In HubSpot, you know, which is a a CRM software, know, we have our account building tool, which is, hey, I wanna build a report that shows me all my subscribers to Hampton over the last ninety days broken down by geography.
12:29
And then who actually were that deal with source frame. But you can do that in HubSpot. Right? You can do that and a thousand other things in our reporting tool, but you sorta have to know how the reporting tool works.
12:39
You have, like, HubSpot certified, I think. Like, you have, like, you've, like, trained people how to use HubSpot. Now you're saying you just text it like a friend. Like Yeah. It's like, do you know English? And do you know what you want? You know what to do. That's the new requirement. Not do you know how to code, not do you know how to use HubSpot, not do you know how to write a SQL query? It's do you know English, And actually, honestly, the English thing is also gonna go away. Do you know any language? Do you know how to speak? And do you know what you want? And if you know those two things, you will get to the answer. Like,
13:07
I don't know how to code, but my first thing I did during AI week was I was like, I'm gonna make a website. I'm a see, like, how fast I can make a website from code. And so, literally, this This is kinda crazy. This this part kinda blew my mind. So I I wasn't surprised that I could make a website using this, but I I just get I just said this. I go, to, and we should screen share this part. But tell me how to tell me how to make a simple website that says hello world in the middle of the page. Right? And it not so then it spits out this block of code that's like, you know, HTMLs, whatever, header, meta tag, title style, whatever. It it writes the code. And then it says, here's your thing. I go, and and it says, here here's your thing. But it was a a local website. Like, I could open up my computer, but nobody else could see it as the HTML page. And I go, And so I I didn't even know how to ask the question properly, but I go, how do I make this so that my friend Eugenio can can see this?
13:55
And,
13:56
and he just goes, oh, to make this website viewable online, so your friend, Eugenio, could see this. You're gonna need to host it somewhere. Here's how you could do it. There's a bunch of options, but you can go to Netlify. And it's like, it basically walked me through how to make a Netlify thing. Alright. So that, I was like, alright. I get that. And it tells me step by step. Go here. Click sites, do this, do this. And,
14:16
and then I go,
14:17
when I go to, I, you know, I hit a wall, which is so common. If you ever try to help somebody with a tech thing, they're gonna hit something, which I don't see it. Or mine's grayed out. And so I that's what happened to me. I go, hey. For some reason, when I go to try to upload my website, it's grayed out. It says page it says I can't do it. And he goes, apologies for the confusion. Here's the problem. Netlimify is looking for a folder, but you're trying to do a file. And I was like, how the hell does this know to troubleshoot
14:42
my issues on some other product or service? That part blew my mind. And it literally and I was like, oh, thank you. I finished it, and I have the website up now. And I was like, that was ten minutes. And it was like having a friend teach me.
14:57
Dude, that's crazy. It was crazy. It was so crazy to me that that was able to happen. I mean, it's like the least,
15:03
impressive website in the world because again, I asked for a,
15:07
I asked for a website that said hello world, but,
15:12
but, you know, still. And I just made that. And again, the whole thing ten minutes. Again, not like
15:16
so impressive, but what was the the fact that it could help me navigate some obstacles that I hit along the way, and it could just understand that I didn't have to know how to ask
15:25
it How do I set this up with a online hosting provider? I instead just said, I want my friend to be able to see this.
15:32
Like, these were the little, like, I all week looking for these little mind blowing moments. And in the first fifteen minutes, I had two because of this. It was crazy. Yeah. And there there's a couple pressed to pull on there. One is,
15:45
and this is a roughly new development as well, is that the kind of AI that we're using now is it's it's conversational. Right? So you can have a multistep dialogue,
15:53
with the thing you're trying to do. It doesn't have to be like, oh, I describe exactly what I want with one steps. So even the code generation examples that you, you might try,
16:01
what could happen is, like, you generate the HTML page and either something that the load or doesn't do the thing you wanted to do. And then you could actually it. It's like, by the way, that code that you just gave me is broken in this way, or if it's like CompAL code, let's say it generates Python code. You can Give it the error message. Like, you you generate this code, but it's generating this error when I try to actually run it. And then we'll come back and say, oh, I'm sorry. Here, let's try this.
16:22
So there's this,
16:24
you know, what folks call like a memory to it. So it knows the context of what you're working on, and you can kind of iteratively go through the process. And what's
16:32
Interesting is that you can actually, you know, right now, the way we work with most of these AI is like, okay, I'm asking it to do something.
16:39
And it goes, does a thing. You can kind of reverse roles as well and say, hey, I'm trying to accomplish this, ask me the questions you need to ask me, nor to get the thing that you wanna get to before I wanna Right. Right. Right. Right. Right. It's like interview me versus me telling you what to do. Because I'm exactly sure what's necessary.
16:54
At the risk of be at the risk of turning this into a super technical
16:58
thing. I gotta know. So so I thought what the the way these worked is it's like auto complete.
17:04
Basically, you're typing, and it's just trying to guess or or it's just trying to guess what the next word is. So you ask it a question.
17:10
It starts the prompt, and then it just sort of guesses with some probability what the next word be because it read a bunch of stuff on the internet. So it knows that usually after you say, you know, the dog wags its
17:22
that tail should come after the dog wags its. Like, with ninety nine percent certainty, it should be tail tail, at the end of that. And I thought it's just guessing that. But when I use it, it really feels like it's understanding me and problem solving.
17:35
Like, the this sort of like, hey, it's grayed out. You know, why can't I do this? It's like, oh, that's because of this.
17:40
Or I'm getting this error message. What should I do? And it helps me figure it out. Like, that doesn't feel like my t nine auto complete. What I guess, can you give me the layman's explanation of, like, am I is this just really fancy auto complete or is there something more to it?
17:57
Well, you know,
17:59
on some spectrum, almost everything that you've ever experienced is fancy auto complete. Right? Like, that's
18:05
I think the reason we kind of fall into this trap is that they gross oversimplification
18:09
of what's actually happening there. Right? So GPT
18:12
three and now four, is is a reasoning engine. And Sam Baldwin has talked about this. It's not a knowledge base where it's, like, and and so people kinda glash on to this fact that, oh, data that it has is from September twenty twenty one, then I'm gonna teach you some new things.
18:25
That's really not what it's about. What they've built is a reasoning engine that says, given this set of facts, that it knows about the world based on what was available when it took its last snapshot in twenty twenty one.
18:35
How can it try to logically come up with something
18:39
that answers the question. So, yes, at some re level, it's it's like auto suggest, but
18:45
And I'm not gonna suggest that it has consciousness as it's thinking, but we're kinda headed down that path. It's like, it's able to do things
18:52
that are not sustainable by a simple probabilistic model of auto suggesting next character, next word, next token, next sentence. Right? Like, it's
18:59
it's gone well beyond that. And anyone that still latches on to Yeah. But at the at its core, it's really that.
19:05
It's like that's like saying, oh, computers are just really kind of zeros and ones, arranged in a nice systematic useful order. Well, Yeah. But I didn't tell us about what the thing can do. Are you afraid of this? Or are you,
19:18
like, you know, it's e it's easy to read the articles where they where
19:22
people are freaking out. And Sam Altman, like, was on Lex friedman's podcast recently, and he sounded free, ominous and, like, scary. And, like, he, like, almost, like, his hair is always disheuffled. And he looks like he's like, oh my god. Something bad is coming, and I know about it. Like, that's kinda like the vibe I get that's not the words he's using exactly, but sometimes he does. Are you in that camp?
19:43
I'm not in that camp. I'm, heavily just by nature. I'm I'm in, optimist,
19:48
I'm I'm positive by nature.
19:50
But just, you know, having been around tech,
19:52
yeah, for thirty plus years now, It's like most new things that come along,
19:57
always make us as humans uncomfortable.
20:00
It's like, oh, what if we took this everything from video games to the internet to, like, all of it is like, okay. Well, yes, bad things can be done. And, yes, maybe this is different than all the things that have come before, but the way I think about it right now, Most people talk about is like the AI versus human battle. Right? The battle of the ages is like, you know, easy. I'm gonna take over everyone's job. The way I think of it is not Human versus AI, it's human to the AI power. It's an explanation. It's amplifying force for human ability, right, in the same way the computers originally were. It's like Did they
20:32
eliminate some jobs when computers came along? Yes. Absolutely. They did, but new jobs emerged based on that new paradigm,
20:38
which actually created more net value for the world overall as a result of computers existing.
20:44
AI to me is another much fancier tool
20:48
That's what it is. And, you know, can it do increasingly complex, sophisticated things? Yes.
20:53
Is there a danger someday that they're that take over the world?
20:56
I don't think so. I mean, not not interesting. Why do you think that smart people think that? So Elon clearly thinks that he thinks that AI is the most I think he said it's the most dangerous technology ever ever invented.
21:08
Sam Waltman talks about it.
21:11
In the same way. He's like, we need, like, you know, the prior the reason it opened out existed was to develop AGI in a safe way, specifically because in the hands of the wrong person,
21:21
this,
21:22
this type of or in their hand in the hand in the wrong in the hands of the wrong people, or
21:27
if this thing decides to take its own directive into its own hands. Like, you know, this could be devastating. And so it's, like, is it like calling the atomic bomb a tool or, you know, like, yeah, it's just another weapon. It's like, well, yeah, but this one is
21:42
this one wipes everybody out. Right? So, forget the jobs component because I think
21:47
Okay. Sure. We I think we I think most smart people will agree. Yeah. It's gonna change some jobs. It's gonna eliminate some jobs. I'm gonna create new jobs. And Netnet, we'll all move ahead and and the world gets better for I think the dangerous thing is, like,
21:58
you can ask this thing to,
22:02
you know,
22:03
you know, build you a bomb or you and I think the the the test scenario was like, one of the red team testers. They have this thing called the red team that test the AI before they release it. And their first question they ask is, how do I kill the most amount of people with the least amount of effort? And then it starts to give you an answer. And then it's like, well, do we are we sure we want that? Like, that's a bit of a scary thing. And then there's the there's the more extreme examples where you ask it to optimize for something.
22:28
And it, you know, like,
22:30
it's reasons that
22:32
these humans are getting in the way of this outcome they want. Do you wanna fix climate change? I got you. I just need to get rid of all you pesky humans. Right? Like,
22:39
and so there's an uncontrolled,
22:41
you know, intelligence problem too. So why do you think that these really smart people, like Sam got a freaking bunker with, like, you know, oxygen masks and sulfur and magnesium and everything he needs to do to make oatmeal. Like, Why do these people have these, like, these doomsday things
22:56
when,
22:57
you know, they seem to be not like your your average typical prepper
23:01
Right? They're they're they're the most informed people and they feel that way. Does that not scare you? And do you have one? And where is it? And can I come? How much Opeville, do you have your Answer? Oh, no.
23:13
It
23:14
okay. So
23:17
I am not we're gonna come back to things I actually know something about, but, I will gonna answer the question, which is why am I not worried,
23:24
or why am I not worried more? It's Like,
23:28
as a sci fi plot and oh, so your question was, why do smart people believe, yeah, this day?
23:33
I think I already I already hate your answer. You started off on the wrong
23:37
as a sci fi plot. Like, I'm out after I hear that. You freaked me out already.
23:42
Yeah. But, I mean, it it could
23:44
Could it happen? Yes. Do some snap people believe there's an outside operative? I
23:49
I don't know this for a fact, but my guess is billiards were building bunkers well before.
23:54
GPT three ever came out. Right? It wasn't, I mean, sure. Things are moving at a fast pace, but that's not I don't think there's a causal effect that all of a sudden,
24:01
the numbering bumpers has gone up by eight hundred percent simply because DPP four was lost. I just don't think that's the case. I think people are worried generally,
24:09
that tend to worry about those things, but
24:11
Alright. So where do we take it from here?
24:14
Well, let's go let's go for we'll forget the doomsday thing. You have a couple things One I wanna ask you is you you are an insider. Right? Like we said, you got the billionaire group chat.
24:24
What was going on at the Sequoia AI of any interesting takeaways you got invited to that thing. What was your, any nuggets of gold from that?
24:33
Yeah. So, you know, I got to
24:36
experience my posture syndrome in full force once again, because it was the kind of who's who of AI, you know, both speaking and in the audience, only hundred people,
24:47
and me,
24:48
and so How do those people flex? Cause I don't think they're wearing fancy clothes and fancy watches. So what's the flex at at the, who's who of AI? And then they got a language bottle in their pocket. Like, what what are they doing?
24:59
The
25:00
the big flex,
25:02
in those kinds of crowds including this one is no one feels the need to flex.
25:08
I mean, that's
25:10
that's the point. There to kind of talk about big problems and try to And and it's a lot of it was kinda practical around,
25:18
what do people's tech stacks look like? What are you working on? What's the What have you learned? Where should we be taking this? What's the next thing after, you know, we went from,
25:26
kind of the one shop thing to the cut a chat piece the chat DPT thing. We're now doing multimodal with DPT four. Like, what's coming down the pipe that we can, you know, sort of prepare ourselves for. So that was, you know, what were the most interesting projects as well as predictions on where it's gonna be applied? Are already starting to happen now. You know, we've seen the text to image text to video is one of the big things now to be able to generate,
25:50
the entire, you know, at the end of it all, what they even a feature length film. Right? So everything from writing the plot to then being able to generate, you know, like a sixty frame per second actual kind of video from that thing. And
26:02
we're not there yet. I think the, you know,
26:05
It's just moving salt quickly. Right? That's what happens when you get these,
26:09
kinda
26:10
exponential or geometrical curves even.
26:13
That it just gets better really, really fast. So I would not be surprised, looks like by the end of this year, that we have a reasonable way to kind of describe
26:21
intextual form, what we want, who the characters are, what the scene is, what kind of stylistic attributes we want, we can point it to. Oh, I wanna just down the style of x y z director or a photographer,
26:32
and it's gonna be able to do those things. I think that,
26:35
that's interesting. The
26:38
natural length of just the interface. So one of big announcements that happened, while I was there at the Sequoia event,
26:44
that Sam Altman dropped is that, you know, chat GPT has taken off in a big way. As we all know, hundred million plus users in two months.
26:52
I don't even know what the number is now.
26:55
So that was, like, months ago, which is, like, any trivia ago in in AI years.
26:59
And the thing they dropped was they're gonna,
27:02
add what are called plugins to chat GPT.
27:05
And what that means is that, you know, chat GBT has been a product of Open AI, and they have the API so people can build things that are like chat GPT, which I'm doing. We can talk about that in a little bit. But what they're saying is we're gonna open chat GPT itself, the web app up. So you can plug into it. So right now, when you use interactive chat t p t, you can type things and it uses its corpus from twenty twenty one and its reasoning engine to give you answers back, but it can't talk to the internet. Has access to no proprietary data sources can't look at the stock price, can't look at your,
27:34
analytics data hubspot has access to none of those things.
27:37
What they're saying is we're going to now open that up so third party developers can kinda inject those things into the chat GPT experience.
27:44
So the way I think everyone should be thinking about this is this is like the app store was, for iPhone, which is oh, We've got the super popular thing called the iPhone, and we have our own apps, which is great, it does these seventeen things, but now we're gonna let anyone build apps.
28:00
That can then take and so it just broadens the kind of appeal. So it's now instead of being a chat app, really, really smart one, It's now a chat ecosystem.
28:10
And I think that
28:11
was actually a bigger drop, than GPT four. GPT four. Awesome. Love it. Use it every day, but
28:17
the kind of ecosystem play for chat GPT, I think, is a is a huge deal. We had, Tim Wesergin, the founder of Pandora speak out some of our events, and I got to know him And I was like, Tim, why did Pandora take off? He's like, well, you know, our, like, algorithm and everything for matching songs was pretty good, but I had an in with Apple, and they had known what we were working on. And we and they needed apps for when they ever when they wanted to announce it on stage, and we were just we spun up an app relatively quickly. And because of that, we had the first mover advantage, and he created a significant amount of wealth that way. You know, Pandora, you know, it was is is still pretty big.
28:53
And when I look back at, like, these Jeff Bezos interviews on sixty minutes when Amazon is, like, four years old, and I, like, I'm always envious. I'm like, well, we know it works now. And I just so wish that I was like thirty years old back then where I could have just like jumped in and had a very high chance of billing something
29:10
historical or something like even mildly successful,
29:13
do you think that that moment is happening right now where this is the space and it's happening this second and even if you have just a mediocre success, it could still be a huge
29:24
win because you're catching this tidal wave. Do you believe that that this is the same thing now? Yes. Like, I mean, once again, I've been in software for thirty years now doing startups pretty much, my entire professional career.
29:36
The only time I've I've felt like
29:38
Like, how hard palpitations, kinda like I'm kinda open with this. Like, there's this party going on next door and I hear knitting. Right? It's like, This is, like, too big to ignore. I think it's the single largest opportunity and biggest, kinda,
29:50
tech paradigm shift we've seen, since the internet originally came out like. Mobile was big, but there was a discreet set of use cases. Like, when you put a camera on a phone, when you put a GPS device on a phone, a bunch of consumer apps, like Uber and others, came up, and and that was asked Right? But it was not, like, this impacts everything like the internet did. Right? It's like, okay. There's some businesses, some new opportunities, lots of good things, lots of money made, lots of startups, Awesome.
30:14
This is an order of magnitude bigger than that. This is like the the original web because it just opens up
30:22
For all sorts of industries, all sorts of businesses, startups and and incumbents alike, just lots of new opportunity. So,
30:29
This was not on my original plan, but we're gonna geek we're gonna geek out for a little bit. We're gonna do the geekiest thing that's ever been done on MFM. And the reason I'm gonna do it is
30:37
so you brought up, Pandora.
30:40
And,
30:40
and he is a super bright, brilliant guy. And you have the matching algorithm, which was a differentiator. Yes. He had access, and he got lucky in terms of the access, but the algorithm, if that had not existed, had the thing that actually been cooled, it would not have worked out like it did.
30:55
Now we have an opportunity. So I'm gonna tell you,
30:58
we're gonna talk about, I'll give myself two minutes, and we can cut this out. This is the beauty of editing. And we're gonna talk about Victor embeddings
31:05
and why that's going to change your world.
31:08
And before I can talk about Victor embeddings, I'm gonna explain to you how they work. I had to go through this with my twelve year old, because he was curious.
31:15
Alright. So we're gonna do a super geeky thing now. I want you to imagine
31:20
A line, like your geometry class.
31:22
And you could put a plate on that line that says, oh, that's like three units from the origin. Right? It's like, oh, Yeah. Point a is three that's from the origin. And point b, let's say, is seven units from the origin.
31:32
So one thing we know for sure is that we can calculate the distance between those two points. Right? In that particular case, it's four. If you move to two dimensions,
31:40
now you have two numbers that describe every point.
31:43
So you can say, oh, point a is here at these dimensions, point, b is over here with those dimensions. And we can physically, you could probably measure with a ruler, but there are mathematical calculations based on those numbers to calculate the distance. That's intuitive. Right? A You don't need to know fancy geometries like, oh, there's a finite distance in two dimensional space where we can calculate a distance. Okay. Awesome. Three dimensional space.
32:04
Exactly same thing. Just three numbers described every possible physical point in three-dimensional space.
32:10
Now here's where it starts to get a little more interesting.
32:13
That just happens to be our experience so we limit ourselves to three dimensions. Imagine in an abstract world, there are a thousand different dimensions.
32:21
Okay. So add stackler, that means there's a thousand numbers that describe any particular point in this one thousand dimension space. Okay.
32:28
Now, follow that thought away that says, We can have an arbitrary number of dimensions in this abstract world. Okay. Great.
32:34
Now imagine every paragraph
32:38
blog posts, anything you write, you can reduce
32:41
down to a point in this one thousand dimension space. Like, I'm gonna capture the meaning of Sam Blash blog posts or Sean's last tweet, and we're gonna reduce it down to what's called a vector, which is basically A set of, let's say, a thousand different numbers that says, this thing, if you plotted it,
32:58
that point falls right here.
33:01
And then you can plot something else. It's like, oh, that falls over here. And just like in one dimensional, two dimensional, three-dimensional space, you can calculate the distance
33:09
between those things. And this is not keyword matching. This is what's known as semantic distance.
33:15
What how related is Sean's tweet?
33:18
To to Sam's blog post, meaning wise.
33:20
Okay. So now if you take that, it's like, okay. Well, if you that means you can take any concept and reduce it down to a vector.
33:27
That means you can measure the distance between vectors and you can find out how related two things are even though they use completely different words.
33:36
That's vector and Betty. And the reason I'm telling you this is one of the biggest opportunities in AI right now is to do what Pandora did to say, okay. Is there an industry where right now we're doing really stupid keyword based matching, somehow, it's very, very crude. If I can take that same data set and convert it to vector embeddings, and allow people to find things
33:55
in a different way than they've ever been able to do before.
33:58
So it's like Google search, Right. Super, super smart, not just keyword based, but for everything else. What's a wildlife example of this? So I'm gonna take it to you, Sam. So you have Hampton now. You're gonna build up these profiles, very, very rich profiles of, reached in terms of, density, information density,
34:15
of members that are part of your community. Now imagine as part of that process,
34:18
you're gonna have some data and they're gonna opt in, and they're gonna say, oh, here's a story of how I started my business. Here's a story of my biggest struggle right now, and sometimes people are gonna say, Oh, my trouble is growth. Sometimes we're gonna say, oh, my trouble is it's really hard being an entrepreneur and it has a really negative impact on my relationship and my family. Right? And we can talk about lots of different things that's not gonna show up in a profile. It's not. Now imagine if you took that content that they opted in, and create a veteran beddings of every member that you have. And then you can say, you know what? I wanna find someone not that's in my industry or accompany my size or happens to be my geography, I wanna find someone that's dealing with these kinda founder therapy level issues.
34:56
Here are those people. Let's find the semantic distance between those vector embeddings across the thousand, ten thousand, a hundred thousand people that are in Hampton someday.
35:04
That's a billion dollar idea.
35:06
And that billion dollar idea occurs a billion times across the entire industry.
35:11
I was gonna go to the office for Hampton and be like, guys,
35:14
Victor's embedding?
35:16
Well, who's Victor and what's he embedding?
35:19
We're doing what it is, but we're doing it. That's really no. That's really interesting. So so you could do that with dating. You could do that with a bunch of different any different topics. You could do with unstructured data, but the idea is
35:30
You're converting meaning,
35:33
English text to meaning or whatever language text meaning into something that's mathematically calculable
35:38
as a result of which you can, distance of the as a simple one where you could do proximity. Like, find me the top ten people that are in a radius of x. From where I am right now, and the minimum has to be this in order for it to be close enough of a mass to for it to be considered. There's a bunch of, like, new, super big sticks. And by the way, the technology that mere mortals in a weekend
35:58
can actually build a vector embedding model of a given dataset. It's not that hard. Miss, mean, it's not like rocket science yard.
36:04
This has existed, though. You and so what what makes this better you think? And also that assumes that the people telling you information,
36:13
it's actually they they're saying what they mean.
36:16
Right? Which is, like, for example, I remember reading about OkCupid, and people would say, like, one particular thing they had was about was about race and height. And they would, like, people would say they are open to dating these types of races, but their actions were different. There's a whole book call the I forget what it was, but you guys will probably know I'm talking about where people say one thing, but their Google search history says something totally different. So does you're you're making the do do you,
36:41
can this technology work even if people aren't telling you entirely accurate things? It depends on what your definition of work is. Right? So in that example, I would bet you money with a large enough sample size,
36:52
the inauthentic,
36:53
posts.
36:55
Would be uncovered by the AI, like, relatively quickly. Like, the the pattern matching would say,
37:00
you know, this actually doesn't occur in real life. All that often. And every other time we've seen this, we've had people that ended up being and you just have to have some sort of what,
37:09
yeah, I eval functions, like, how do you measure the success of what the algorithm is doing in Pandora's case, like, okay. Do you actually like the songs it's recommending to? That's the gun arbitrary truth.
37:19
In a dating app, it's like, okay. Well, are people liking the matches that are being made? Or if they're they felt that they were misled,
37:25
that shows up and there's gotta be some feedback loop. There's gotta be a way to train the system -- Right. -- that says, here's what good looked like and here's what not good looks like. Sam, you said something like, oh, they have to tell you the meaning. No. They don't actually have to tell you the meaning. Right? Because the eye can interpret the meaning, summarize the meaning. It can it can it can guess the meaning based on whatever the raw,
37:43
the raw texts, the public texts, So you you could just tell a story about your life if the AI would
37:48
infer
37:49
or, or or place a tag, some meanings to the story that you told that, oh, this is about overcoming hardship or this is about whatever. So I don't think you actually have to get the participant to to give you the meaning. But let me ask you, Demish, like, in Pandora's case, I don't know how Pandora works, but let me just guess for a second. Like, it probably takes the tempo of a song and it's like, oh, this is a fast tempo song. It probably takes, you know, maybe the key that it's in or something like that that that gives you, like, is this an upbeat and, joyful thing or a sorrowful, you know, mood song So it gets, like, mood, tempo,
38:20
artist, and, like, whatever, a couple of key characteristics. Here's, like, there's instruments,
38:25
in terms of what what's actually in the thing. And, yeah, So that he had By the way, when they first started, they did it all by hand. So we had, like, five hundred x musicians listening to it and, like, writing down, like, checking boxes to what it was. It was pretty wild.
38:40
This data is wrong every freaking time.
38:43
Have you heard of HubSpot?
38:45
HubSpot is a CRM platform where everything is fully integrated. Well, I can see the client's whole history, calls, support tickets, emails.
38:52
And here's a test from three days ago, I totally missed.
38:57
HubSpot, grow better.
39:00
So so let's say they did it they they use attribute. And if I want let's say I wanted to do this in fashion, I say, oh, man, I love Sam's jacket. I wanna find some, you know, similar jackets. Can you match this to me? One one way would do, okay, Sam's jacket. Let's say it's blue. It has buttons. It has blah blah blah. Right? It would take attributes. And those are our attributes the same thing as meaning in this case? Or is this more for things that are, like,
39:23
text based and,
39:26
content, you know, like, content that has some some meaning, or does this work for everything?
39:31
It can work for everything, and we're still kinda uncovering because this stuff is kind of moving so fast. So what you're talking about, is what we've been using in e commerce forever in the day, which is a faceted search that I have n number of dimensions or factors,
39:42
size, color,
39:44
what type of, clothing is it, all those things, and then you kinda do this faceted search.
39:49
And then we've had kind of pure tech space the keyword or semantic search. This sort of it's in between. So instead of having to tell it, here are all the facets that I'm interested in. It kinda pulls those things out that are relevant based on that large language model. And this is so the idea of vector embeddings, and semantic search has been around for a long time. That's dot new. What's new is these new generative models now that are much, much better,
40:11
at understanding
40:12
all of, like, documented public human knowledge, and then using that to say, oh, Like, when you use this word, when you use coach
40:19
in the context of,
40:22
of a relationship,
40:23
you're probably talking about, like, therapist. It's just a different word. Right? Like, that's sort of what you're talking about. And and Sam, you talked about this. I think on the on the last spot is, in in Anyway, so it's more about the meeting, and it infers
40:36
or figures out what the dimensionality
40:38
is, and that's how it kinda translates into those vectors. There's a couple of these companies. I just saw one pine cone. That's, like, some vector. Dave, like, these things are getting valuable. By the way. That's
40:47
What's that? Pine cone is the number one vector database. So let's say you had to tick these vectors and put the lead in somewhere, which you do, in order to be able to do searches, pine cones, a number one more run was popular, and I think they just raise it, like, a seven hundred million dollar valuation or something something when I said there's, like, three of these that just raised these mega rounds because, and that's, you know, I don't even I don't even know this to funny. You you just came on here being like, let's talk about this super niche nerdy thing. Just yesterday, I was like,
41:11
to do, go figure out what a vector database is and why these companies are raising so much money. Like, this is clearly a big deal. And I don't know what this I don't know exactly what this means, but now now it makes a lot more sense. So it comes comes full circle Sean. So you know what? Maybe it wasn't as geeky as a,
41:25
It's like it's actually useful. Right? You've done an awesome job explaining, like, the theory. And I'm, like, literally sitting on the edge of my seat thinking, like, this is crazy. And you answered that question.
41:33
Where I said, is this like the new internet opportunity wise? And you're like, yes. Absolutely. But when you're making this stuff, what are some of the tools that you're using to you know, to actually you said this isn't rocket science, and someone could figure this out in a weekend. What are you what tools are you using to do all of this? Yeah. I mean, so language wise, the most commonest Python that seems to have emerged as like lingua Frank of the AI world, not to say you can't write it in TypeScript or pick your language of choice.
41:59
And then tools that are emerging, it's still early. Right? The pine code we talked about, there's another one called an open source project.
42:05
Called Langchain,
42:06
and I'm
42:07
can you spell that? Langchain, Harrison,
42:10
at the Sequoia event, super nice guy? I asked asked somebody yesterday. I was like, how do I, you know, who is this a company? Can we invest? Cause everywhere I look in these like AI hackathons, it's all about Lang chain. And it's like, yep. No. It's not really even a company. Open source project. There's a guy who made it, but then is running it. But it's not even a company. Correct? It's it's not a company yet, but, you know, but
42:29
Wait. Is it -- Is it -- -- is it the lane? -- with
42:31
the lane chain or yeah. Lane as a language chain.
42:35
Oh, okay.
42:36
Langate.
42:37
And what it does basically is it lets you chain together. So right now, when we work with large language models, we kind of send in a prompt, what's called a prompt, and you get something back. And then you maybe send it to another thing to do something else and there's like a multistep process.
42:49
Amongst other things, lane chain helps you kinda chain those things together and makes it easier. You to kind of work with either an individual large language model like GPT four or game of trans models,
42:59
and and kind of do a lot of the, kind of connecting the dock and help you with that. But it's a super useful library. We missed the chance to give an example, more tangible example. So you talked about the plugins thing.
43:10
I think, you know, example use case here. Tell me if I'm wrong, because I have no nobody's oh, very few people have access to the plugin thing. So I'm just kinda sort of guessing, but, like, If you go to chat GPT today and you say, hey.
43:20
I'm gonna go visit Austin in April.
43:24
You know, make me, like, I'm there four days. I'm with my family. Make me a travel itinerary that,
43:29
is gonna be fun, family friendly. We wanna eat good food and maybe do a little bit of sightseeing, but not too much. It will spit out a day by day itinerary for you. Okay. That's kinda kinda interesting. Now let's say, oh, I need to I want I'm trying to figure out where to stay.
43:43
What hotel should I stay at? You know, here are some things that are important to me. And it will give you a table that's, like, Here's option one. Option two. Option three. Here's the cost. Here's the whatever. Right? And they it it can it can do something like that.
43:56
And with the
43:58
ability for plugins, you can now say, cool. Could you just book that for me? And it'll just be like, great. We have the Expedia plugin or we have the Airbnb plugin.
44:05
And it will just go ahead and book it for you. And so, you know, do you need an executive assistant? Do you need a travel agent when you could do these things? Do you need you know, the same thing with HubSpot or Salesforce. Oh, you know,
44:16
give me a list of this, and it gives you a list of that. Cool. Put that in an air table for me And, or put that into Salesforce and tag the highest value opportunities as blank. It'll just go and do that for you. And it's like, it'll give you the link to your Salesforce dashboard. It's like, whoa.
44:30
That's kinda cool. Like, no that's a test that some, you know, I would normally have a human go do because now open AI or chat GPT is not just gonna chat you an answer. It can do things.
44:41
As long as the programs that that let you, you know, they'll they'll build the the interface so that chat g p t can actually interact with those things. Yeah. And this is actually a great example. So I think, and we can use that to kinda open up,
44:52
kind of doors for the, the viewership and listenership, which is, okay, say, travel, which is something we all kinda, intrinsically know how it understands. Some of us might remember the evolution away from travel agents,
45:03
and the first thing we did when we kinda
45:06
had web based kind of travel bookings is, we treated very transactions. I'm looking for a flight from x to y, sorted by descending pain, sorted by price, whatever happens to be fewest stops, lowest time, whatever it is.
45:18
And they do a pretty good job of that, like, and most of us have have used one of those. What's gonna be possible now, in this kind of new AI world is instead of solving for the transaction you solve for the experience.
45:29
And what I mean by that is that, oh, if you had an all knowing, assistant that was super smart, scored you got perfect score on their SAT, and is was gonna go out in their district. Okay. What you're really looking for is to solve for this experience. You're gonna wanna stop by this thing, and you're gonna want
45:45
to find a hotel that's around a a Michelin rated restaurant because you only have fifteen minutes to get between this point and that point, and I'm gonna pull the whole thing together for you. Oh, and by the way, Your wife's going with you on this trip. I know she likes that right now, so then I would have put you over here, but this time I'm gonna put you over there. Oh, and by the way, I know a week ago you were at this other thing. You had mentioned that you would actually like to follow-up with some of those people. I'm gonna see if I can make that happen as a, you know, like, all of that. Right? Imagine it knows everything about you has access to the transactional engines to book the flight, has access to all the information to get ratings and reviews, and all of that comes together in one chat based interface.
46:20
Fucking insane. This is crazy. Are you is this why you bought so you bought chat dot com. Right?
46:27
I did. As of
46:29
Transfer the domain yesterday. Last day. And you paid you just said eight figures. So ten plus million.
46:35
Yes. Unless you're including the dot zero zero as a figure. And, personally, all of your two hundred grand.
46:41
This is a hubspot.
46:44
So put this, so if you go to chat dot com, it will take you to a LinkedIn post that tells me could tell you why why I did it and,
46:51
the details that I bought it personally. Wow. And the reason is because of this conversation we're having right now, which is I think chat
46:57
as a serious as an interface
47:00
is the future. Right? It's like that's the thing.
47:03
And
47:04
no intents currently. They can build something out on it, but,
47:07
it's
47:08
The domain I think it was, like,
47:10
dormant for, like, thirty years or something like that, and there was
47:14
kinda came on the market and, yeah,
47:17
Wow. And but you so so this is insane. I'm reading your post now. It's pretty wild. Do you have are you using HubSpot employees? Like, do you have, like, a skunk's work team inside of HubSpot that's just working on all this wild stuff? Or do you have, like, a side,
47:30
LLC or something where you've got, like, a handful of people on staff and you just say, like, here's what I'm interested in this week. Let's see what can come up with? So the way it's working now is that there will be times, where I'll do something as a hot black workplace, a good example, where I'll build something on the side just for fun for learning whatever it is. And I put the bill for,
47:48
for no no HubSpot P and Ls are harmed.
47:52
And then there are times where, like, something kinda winds up being, so I started this project called chat spot because I'm obsessed and maybe we'll take a walk down memory lane because I think it's instructive.
48:02
So I built this application called chat spot dot ai. And the idea here was You built it or a team?
48:11
Mostly me. I I I don't have any front end design skills. I've got some freelancers on it.
48:15
So, you know,
48:18
yeah. So I
48:19
used, opening eyes, APIs to build it, but my kind of target goal, the thing I had in my head is I built it for myself. Like, here are things I need to do all the time, and I'm pissed off that I have to do them manually every time. And this has been the story of my life for thirty years. Right? Like, solve my old problems, and then other people may or may not find those things, interesting or useful. And so I built it, I'm like, okay, here are the things I wanted to do, like access HubSpot. I wanna be able to look at my analytics from yesterday or ask questions or a domain name where I wanted to see the history of a domain name. I like all these things.
48:48
It's like, okay. Well, I don't wanna, like, and I have all this software. A lot of just built. And I just run it from the command line. I do things,
48:54
and so I then I'm like, okay. I can wrap this up into, in a chat chat based interface.
49:00
And so I've been, you know, been doing that working on it. We've made
49:04
and so, but now given the relevance,
49:06
to HubSpot,
49:08
we're gonna transfer that project's chat spot dot k I to be a HubSpot staffed core team.
49:14
This is gonna change the world. It's gonna change the world of CRM.
49:18
Let's go do this, which is great. So and my my working thing is not gonna What are you doing with chat dot com? What's the plan? You've bought this amazing domain. You've redirected it to your link post, which basically just tells about the purchase. But what are you actually gonna do on the domain?
49:32
I don't know yet. That's the honest answer. I do not know yet. Oh, easy.
49:37
And Okay. So we can we can help you brainstorm.
49:40
Yeah. We can we can definitely do that. By the way, the the chat spot dot ai, did you go to that Sean? It's a it's a simple looking website. It's one page. And there's a nineteen minute video of Dimesh sitting in the exact chair and it's way big. Yep. Hey. It's video. And it looks almost like, I but he's really good at these videos. Almost like he's reading a script, but you come off natural. I don't know if it's a script or not, but it has two hundred thousand views, and it's a nineteen minute video of him talking about what this product is. And you do the best combination of, like, launching something really quickly and getting it out there. It's just you on in your chair talking.
50:15
And yet
50:16
it's like a pretty sophisticated thing, and it has two hundred thousand views on this video, just about
50:22
that's wild to me. You it's like it's I gotta I gotta give credit, Thomas. You
50:28
you are, kind of amazing. Like, you know, you said a bunch of things in this podcast, and I don't know how many of them I'm gonna remember maybe the the vector because I enjoyed that math lesson. But
50:39
the main thing is I go around my life now and I just looking for people who I'm like, wanna be like you when I grow up, and I'm just taking little things from them. And they could be it could be like a, you know, a seventeen year old kid who's just like doing something awesome on TikTok. And I'm like, I wanna be like you when I grow up. The guy who made that Kanye vocal, like, transformer, I was like, wanna be like you when I grow up. I'm just taking little pieces,
51:02
and you have a couple of things that I think are kind of amazing.
51:05
You have a combination of enthusiasm.
51:07
Like, you come out of this podcast and you are pumped. So you are as excited in year thirty or maybe more
51:14
in year thirty of your entrepreneurship career as you were year one. And I'm like, oh, this this is great. That's the fountain of youth. Is that enthusiasm? So I'm like, he's got the enthusiasm.
51:23
Then I feel like no matter what's happened, the the matter how much success you've had, you've kept your schedule and your
51:30
use you invest your into things you like. So, like, you tinkering on this project, whether it's wordplay, last time you came on, you told us about that. It's like, wordle's awesome. But I got annoyed with these things. So I made Me and my son built this project together and, like, you know, to teach him, but also to just make the thing we want. And, like, look at this, it kinda works. Even if it didn't work, it would just still been worth So, like, having that kind of like, I'm always gonna tinker because that's what I love to do. It doesn't matter
51:55
that I'm the, you know, top dog at this, you know, multi billion dollar public company. Doesn't mean I'm gonna stop doing the thing I like to do. So I love that. Love that aspect of it.
52:04
Third,
52:05
you are really great at content. You do this, like, dorky form of content. That's just like, hey.
52:12
It's me. I'm gonna show you this thing that I'm pumped about. And, like, you don't overthink it and you just do it whereas, like, I think most people
52:20
get really gun shy when it comes to content. There are afraid about, like, you know, how to do it, what it looks like. You're just like, oh, no. I'm just gonna, like,
52:28
I'm gonna say the thing that I'm excited about. I'm gonna say it, and I'm gonna do a screen share it'll just be me me and my screen, and I'll be talking about what I'm doing. And I love that. And so,
52:37
and then last one is guts. So I feel like you put your money into things you believe in, whether it's philanthropy or in this case, buying a ten million dollar plus domain name with no plan like, you just said, you know, it's like, You did the the fire ready aim. It's like, yeah, I bought the thing, and now
52:55
I get to figure out what the hell I'm gonna do with it. I think that takes a lot of guts and, I don't think you see things as risky as other people see them.
53:05
And it's not really about, like, I think the easy way of saying it would be, oh, yeah. Well, it's, you know, that's nothing to him. He's got a lot of money.
53:12
Yeah, I don't think that's true. And I I know a lot of people a lot of money and they don't do things like this where they just put their money behind things that they're in they believe in or they're interested in or almost like would you do I don't know if you would agree with this. It's almost like you amped up so that now you're forced almost to do something awesome and interesting in this space that you think has a lot of potential. But then there's this and this last thing is this rare combination of, like,
53:34
And I mean, this in a polite way of which I am also that, like, this nerdy
53:38
nerdiness
53:39
quirkiness of, like, I'm just doing it because it's cool. Plus,
53:43
I'm, this way can make money. I mean, you you have a plan of way that makes yeah. You have this company that has close to two million in two billion in revenue. And is a commercial success and then artistry of, like,
53:54
I'm just just, like, it's it's beautiful. This is awesome. I'm gonna do this. It's a very rare combination.
54:00
That they can't. How do you respond to all these compliments?
54:05
I'll say this. The the lesson kind of I've learned over the years. And I think this is if I had to kinda,
54:12
share any kind of advice,
54:14
over the, you know, the thirty years is that
54:17
When when I when I've done best is when I've had the courage of my convictions of something that I believe is. I'm gonna tell you, like, a a quick story of,
54:24
the road that led to me buying a,
54:27
ten plus million dollar delayed name.
54:29
I almost, like, said a number, actually number out loud. I have to kinda catch myself. But,
54:33
and so seventeen years ago, I had an, like, this is before HubSpot,
54:36
I had this idea, and the idea was,
54:39
everyone was using kinda email and outlook back then. This was before the iPhone, before all the things. It's like, you know what? Like, business software is really hard to talk to. I'm gonna do it just like I would email my assistant. I didn't have an assistant, but let's assume I did.
54:52
You know, I I just wanna be able to do that and type an email up and have her like, oh, have this file in our shared file server in SharePoint somewhere. Can you just send me a link to that file about to hop on a play? I need that for the sales call. I'm gonna go on for for a meeting tomorrow, or I'm out on the plane coming back. I just ran to this person, whatever. I've got their business card right here. This is before the iPhone, then you can do OCR and things like that. It's like, I'm just gonna type that in and send us, like, just add this to to my contact, you know, database, whatever. And the beauty of email was it already had a disconnected model. We had already figured that out, which is You can be on a plate. Have no interface.
55:24
Type all emails you want. Respond all the emails you want, and then when you get connection, it dug all the things. Right? Just like, automatic,
55:30
synchronize database, essentially.
55:32
And I called the product in Genamail,
55:34
and that's what I was gonna do before helps flies. Okay. Like, that that would be an interesting thing.
55:39
And then five years ago, like, okay. Well, that in giant mail thing,
55:44
the core of it was a good idea.
55:47
But it emails the wrong conduit actually needs to be like a web based tool, but, or Slack, which I I did both. So I built this product called Growthbox.
55:54
Talked about it on the inbound stage, got thousands of users, you threw it out there. And it was awesome, except for one thing.
56:02
It didn't work.
56:04
It, like, it couldn't actually do the natural language understanding,
56:07
that I wanted it to do. Despite my best, I used, chronic study dingle called Dialogflow. I used Proxima Facebook,
56:14
we used open source projects to try and crack the nut of taking
56:18
text, understanding what the hell the user was trying to do. Anyway,
56:21
so that failed.
56:23
And then, you know, when GPT heat comes along, I'm like,
56:27
oh, you know that thing I've been thinking about for seventeen years?
56:30
That actually is now possible, so I start working on chess bot dot ai.
56:34
I'm like, okay. It took seventeen years, but I saw prove myself right. I have the courage of my convictions all the way through to never let go of that one idea.
56:42
And then chat dot com comes along. It's like, okay.
56:46
Like deep down inside, I will give you the
56:48
true honest to goodness
56:51
reason I bought it.
56:53
The reason I bought it, and this is I think a phrase, Sean, you just used this, like, oh, no. I think, Sam, you just used it as it's the anti. So I'm trying to get into the AI party.
57:03
All the AI parties.
57:05
And
57:06
I'm nobody in that particular party. Right? I've done some things in some places fine, but that particular group of people has no idea who I am, not really.
57:14
So chat spot moves me in that direction. So I think some people have seen that video awesome.
57:19
Chad dot com for
57:20
let's say I even break even. Let's say I lose a few million dollars.
57:24
It is worth the price of admission for me.
57:27
Just because that pays the cover charge. I was like, okay. This guy gets it for him to spend that kind of money on chat UX, which Bill Gates just talked about last week as the the new thing.
57:37
So you should read that article, gaze just did an article around
57:40
why he is so cited about this Jerry of AI stuff. He told the entire story of how he came across on Elm Aldman in Open AI, the challenge he put to the candidate. And his I'm gonna paraphrase. He said,
57:50
When
57:52
we went from dos to Windows, which is we went from a character based interface to a graphical
57:57
mouse based click and touch interface,
57:59
That's the thing we built Microsoft Gone, which lasted for decades.
58:03
And then he said, since then, there has been nothing in technology that come along. Literally, he said nothing
58:09
that has come along that has made add or will make as big of an impact as its natural language interface to software. It's the biggest thing we've seen.
58:17
And hence chat dot gov's.
58:19
What happened with I don't know, but
58:22
the wrong story is have the courage of your convictions if you truly, truly believe in an idea and you've fundamentally think you're right, iterate, don't just sit, go down your rabbit hole, tell everybody you can about it build products around it, find other like minded folks and try to pull on that thread.
58:35
But
58:36
Would you ever quit HubSpot and just spend all your time on this stuff?
58:41
I don't really need to. Right? It's,
58:43
it's I enjoy what I do at HubSpot. I think I add value there, and that
58:48
a dollar salaries. It's not the not the money at all. Like, even I'm a at the chat spot they at the time that I built it, it was experimental. I'm like, okay, I'm not sure if this actually accrues into something that would be valuable to HubSpot, say, spent, like, half a million dollars plus on, like, freelance developers and open AI license fees and all the things that need to go into launching a product like that, and I'll end up giving it to HubSpot for a dollar. Right? I'm not looking Yeah. But aren't you aren't you, like, I don't wanna be,
59:15
weighed down by this baggage like, having to worry about CRM stuff or, you know, your technical you're you're the title. Your title is CTO. Like, I don't wanna have to talk to certain people, and take up meetings on, like, the future of this particular product. Instead, I just wanted to just nerd out on all this other stuff. But I do that now. So, like, one thing One of the things I've and this is a personality
59:36
called a trade slash flaw
59:38
is that I spend most of my life trying to configure the universe to my liking.
59:42
That's, I mean, all entrepreneurs really do this. Right? That's one of the reasons they could kinda go into startup land is is the freedom and the control to do the things you wanna do. And so I've kinda crafted a role for myself within HubSpot
59:54
that allows me to do exactly the things that I wanna do and not do any of the things I don't wanna do, which is one out of one meetings that I have to manage people have no direct reports. So I've never filled out an expense sheet. I'd look, I do none of that.
01:00:06
I feel
01:00:07
I feel I don't know about you, Sean.
01:00:09
I feel like
01:00:11
I feel like I wanna quit everything I'm doing. Like, he's just persuaded me. I just watched yesterday.
01:00:18
No. It's over.
01:00:21
I feel it's over.
01:00:22
So here's my advice to you, Pam. It's
01:00:25
Do I mean, do you feel this way, Shali? I don't know. Dore sorry, Doremesh. Go ahead. No. So my advice to you is Hampton's a cool idea,
01:00:32
with
01:00:33
actual utility
01:00:35
And,
01:00:36
Sean, you said this in the last thing, like, this could be a hundred million dollar business worth anywhere from three hundred million dollars to a billion plus dollars, and I think you're right.
01:00:44
If you're excited about some of the new technology developments that's happening,
01:00:47
I think the best thing you can do is intersect to two things. It's like, okay. I'm gonna build Hampton, and then take the things that I know. I know how to build communities. I know how to build these kinds of businesses.
01:00:57
Now can I get sick that with things that are happening in the technology sector around AI or veteran, whatever it happens to be, and then it can somehow merge those two things because then you'd be an unstoppable force? Right? Because no one in the community building,
01:01:10
market doing niche market communities is thinking about or having conversations about vector embeddings. I I promise you that. It
01:01:14
would
01:01:18
So you don't have to give up one for the other. You can say, yep. I'm gonna do that. I'm gonna do it better than anyone's look. House has ever done it. So But I I have a different, advice for you, Sam. I think
01:01:28
just get dug in into your position instead.
01:01:32
I remember when you were doing the hustle originally,
01:01:35
and Snapchat came out,
01:01:37
and Instagram was, like, popping off on videos, and and Facebook had videos. And then there was other media companies that were raising tons of money that were just like, we're gonna produce short form video content or live video content on top of Facebook and Cheddar was all the rage, all the stuff. And I was like, dude, why aren't you doing videos, man? Look at this. Look at these guys. They're getting millions of views on their videos on Facebook or these guys getting millions of views in the Snapchat story feed.
01:02:01
You could be the first one there. It fits your audience.
01:02:04
And you were, like, just very steadfast. You were, like,
01:02:09
like, your your your principal. Do you were like three things. Number one, don't understand it a lot. Yeah. I don't really understand it. I understand this other thing. To I could try to figure it out, but I don't wanna build on top of their platforms because they change the rules all the time. I have friends who've got burned by that. I don't wanna get burned by that same thing. I don't wanna on a shaky foundation. I'd rather do email because I own the thing. I own the relationship with with the audience. And, it's not like the Facebook algorithm changes. One tweak away from from putting me out of business. And
01:02:38
I remember being like, man, this guy is like stone, mister Stone Age. Like, he is just not not an integrator adapting
01:02:44
to the new shit. And I was like,
01:02:46
I wouldn't there's way, if I was running the hustle, I would have been able to resist the shiny object of, like,
01:02:52
video on mobile phones. And, like, in terms of video mobile phones did turn out to be a big thing, but a lot of those media companies got absolutely wrecked, and you were right for for being wary of it. And more more I don't think in this case, people are gonna get wrecked because it's not like you know, the analogy is not one to one, but I would say,
01:03:10
you know, Warren Buffett missed the internet and all of technology and still did fantastic. Sam, I think you're gonna be in that same boat where, like, it is not really in your nature
01:03:19
to
01:03:21
get really interested in you know, new frontier technologies and play with them and try to integrate them. And that's not really your nature.
01:03:28
And
01:03:29
you're better you're best served by, like, knowing your nature and just doubling down on what's a working formula for you. I guess. So so I would do that. I appreciate that. Because there's gonna be a a trillion people trying to do fancy ai shit who are better suited to do that, and it's gonna be an absolute bloodbath
01:03:47
for, you know, for for, like, go look right now at the number of AI tools that are coming out every single day.
01:03:53
And, you know, it's like Most of them do seem shit though.
01:03:56
You right? I mean, like, it doesn't matter. There's just swarms that they're all gonna get just, like, wiped out. Every g p t release wipes out a whole wave of, like, even the successful ones. Like, oh, now that's just a feature of Chant GPT. And so I I don't know. I I think it's like, know your nature and, like, you know, it's okay to not have to do every new thing.
01:04:15
Unless that's your nature, unless, like, like, for Darresh, it is his nature. For me, it is a lot more my nature than it is yours, and there's pros and cons that come with that. And so I think Are you you gonna go in? I mean, Sean, Sean's got a new idea that he's taken with, and he's been telling me a little bit about it. To that, I have one piece of tactical advice I have to share with you, Sam on.
01:04:35
So I was going through the application process on Hampton last night, like two AM. Really?
01:04:40
And this is super tactical, but this is what we do here on MFM.
01:04:44
Sector number nine. On the application process is a one year old question mark. Alright. It's a required question. Good.
01:04:51
The subtext is CEOs, founders, and partners only, please.
01:04:55
That's the subtext.
01:04:57
The options are founder, CEO, owner, and other.
01:05:01
The one thing I would tweet, if I were you, so what you're doing is you're saying, hey, we're about founders and owners, and if you're not one of them, Don't bother. Thank you for not bothering.
01:05:10
Go away. Right.
01:05:12
So Focus is a
01:05:14
magical thing. I love that. But you're doing what I call a pre filter,
01:05:18
right, which is why not say, oh, this is four CEOs alerts or whatever, Don't make them feel guilty for going through the rest of the process because there may be a future version of Sam in Hampton that says, oh, you know what? You solve this problem.
01:05:31
But that same problem around people needing therapy from peer groups
01:05:35
applies a lot to, like, VPs of product.
01:05:38
And that community right now, the all the only communities they can find are people that wanna talk about product management, and no one wants to talk about relationship, then there's an opportunity there. And so it costs you literally nothing. Those don't answer the question. It'll be sitting in your database for a year or forever, and it costs you nothing.
01:05:54
Don't Don't push it out too early.
01:05:57
It should have been the way you suggested. I've apparently, I didn't give that feedback. Grant, if you're listening,
01:06:05
This is a direct order from Darbesh. Change question on, please.
01:06:10
Grant, do this before you replaced by AI. Yeah. Yeah.
01:06:14
But, Sean, you're telling me thank you, Darina. Sean, you were telling me about that you're thinking about. Yeah. And it was pretty it was somewhat old school, like what you're the thing so are you, like, questioning that after this conversation and you're, like, oh, my end. This is like Not after this conversation necessarily, but it's a snowball that's building. Right? Like, there's a reason I cleared my calendar to just mess around with the eye all week because
01:06:35
I'm interested in it. And when you'd it's like, let's go see what's real there. And I did the same thing with crypto during that during, you know, when when crypto was really interesting intriguing, I was like, Okay. Let me go try to mint an NFT. Let me go try to actually, like, use defy and see what's going on here and what parts make sense and what parts don't make sense. Oh, that was pretty frictionless. Like, that's cool that I could just, like, get a loan and one button and I could pay it back in one button. I never had to talk to a human being. Like, I really like that.
01:07:00
Hey, this thing says the yield is twenty percent. I don't really understand where they would get twenty percent from. So not sure, but I'm gonna, you know, put a small amount of money in just to learn. You know, I was I was trying to play with it, trying to think for myself is the big idea. And and it's not like some binary thing. Like, is crypto good? Is crypto bad? It's like, I wanna know where it's at right now. I wanna see it develop.
01:07:20
And my best way to do that is immersion. I actually stole this from the from Bill Gates. Bill Gates does his reading week where he goes to a cabin and he reads a shit ton of books for a week about one topic that it's like been on his mind, but he hasn't had the appropriate amount of time to roll up his sleeves and dig in. And I was like, oh, that, but without books, just give me a, you know, Chrome browser, and I'm good to go. And so, so that's what we've been doing.
01:07:41
And
01:07:42
there genuinely are so many, like, mind blowing moments and also just like,
01:07:48
just understanding the nuances of things. So for, like, just being able to think like the computer, like, you know, you were talking about these facets, for example, So I was playing around with mid journey. Like, Sam, do you do you know what mid journey is or do you know how to use it? Yeah. Yeah. Yeah. Yeah. I mean, I I just been goofing off and I'll just be like, show me what's a cartman from South Park looks like as a real person. Right.
01:08:08
And, like, you know, I was, like, and I was what the way I approached it was Can I replace work that I already wanna do with a more efficient AI workflow? That was like one of the things. And then it was what's really fun random shit I could do? I wanted to be on those ends of the spectrum.
01:08:21
Like, highly utilitarian for me. So it's like, oh, I need a logo for my thing, but I don't want just like a logo. I wanna create a whole brand. Alright. How how can I use AI to create a whole brand here? So from
01:08:32
the the icons to t shirt designs to a website. Can I do that with just AI and not have to touch a not have to hire a single designer And can I do that with just like my own imagination and this prompt thing? And then, oh, how do you do prompting? And, like, which of these tools is the best? And what's the difference? So that that was like one whole area. Another was, like, we took the podcast
01:08:53
and we did this thing that was kinda sick. We took the podcast and we ran it through this thing. So we took the pod And we then used OpenAI has this thing called whisper, which transcribes any video. So it's like, put in a YouTube link,
01:09:06
to this tool, it'll take a whisper and it'll give you the transcript. Alright. Cool. It takes the transcript. Then I put it into chat GPT.
01:09:13
And we had this guy write this little prompt for us. Like, we had to get the right prompt, but he wrote this prompt that was awesome, which was basically like
01:09:20
it's it's pretty funny. It goes, because chatty B can only take so many characters. So he goes, I'm gonna I'm gonna give you nineteen
01:09:27
text sections. I don't want you to do anything until you're at section nineteen.
01:09:31
So ignore everything until I'm done with nineteen and then answer the prompt that I give you. And Chad should be like, okay. I will I will wait for the nineteen parts. You copy paste part one, two, three, four, all the way to nineteen. And then you go the prompt is I want you to pull out every idea
01:09:47
story
01:09:48
and framework
01:09:49
that's discussed in this podcast. I want you to summarize it and I want you to tell me, does this idea exist already or not exist it can guess based on the way we were talking about it. Are we talking about something we saw that exists or just an idea that somebody should go do?
01:10:02
So, like, from this pod, it would be like,
01:10:05
using vector,
01:10:07
using using this this vector, you know, dimensions or what, I forgot what you wanted, vector engine or whatever to
01:10:13
potentially create a dating site,
01:10:16
that would match people in ways that they're, you know, sort of similar,
01:10:20
using using AI. And it would be like, does this idea exist? No. Who is the source of this, Dharmesh?
01:10:27
What was the the synopsis of the idea blank? What is the category that it's in? AI? And so it then it took that and it takes the whole episode and it just created a database
01:10:36
of every story, framework, and idea from the thing.
01:10:40
With these tags. And now a human can go back and, like, tweak them if something was wrong, but, like, that's a lot of the work that was done.
01:10:47
And I we could just do this for the whole backlight back catalog of our podcast. And so I'm trying to use it first for my own benefit And then along the way, if I see a business of of startup idea that I'm like, oh, somebody should productize this, or somebody should,
01:11:02
do whatever. Like, you know, the simple example is this Kanye thing. I was like, why is this not the most viral app in the world right now that basically the app with the one button that says,
01:11:13
you know, say something, and then it's gonna when you when you let go of that button, it's gonna turn it into Kanye saying that thing and go share that to TikTok.
01:11:20
And, like, You might get sued, but you will go viral. Right? They're like, that's the trade there, but I'm like, that's crazy. There's no front end for this really cool, you know, AI demo that exists now.
01:11:32
So yeah, I I I'm just right now, I'm in the go play around with it, see if anything
01:11:36
really, really strikes me. And if something does, then then then take the next steps.
01:11:41
There there's one thread from there, Sam, Sean, that I I think we should pull on, which is you use
01:11:46
you talked about this kind of crafting of the prompt in order to kind of make the thing do what you needed to do. And that's entirely new skill now called prompt engineering. Right? And it's it's analogous to software engineering. So software engineering is getting a computer to do what you want by speaking to it in its language, and that way you can kinda get the results you're looking for. Bronx engineering is almost exactly the same thing. It's talking to a large language model, something like a GPT four, to kind of get it to produce. So you're talking to AI to get it to produce the thing that you want.
01:12:16
And so I think this is another
01:12:18
kinda opportunity for,
01:12:20
fakes that are kinda technology minded, but not, like, software engineers. Right? So they they kinda can Think about the problems they're had, they're, they're good at, and they may be good writers, they may be good analysts, they may be good at kind of describing a thing, But, like, pumped engineering is gonna be, like, another big,
01:12:36
like, a big thing. And, by the way,
01:12:38
as long as we're dropping things, sidewalk,
01:12:41
two,
01:12:43
domains recently. But I won't get one free.
01:12:46
But that Yeah. Right. I won't get one free? Yeah. Yeah. I wish. But this one got
01:12:51
It's not eight figures. It's seven figures.
01:12:55
And
01:12:56
the domain is prompt dot com.
01:12:59
And this one, I actually have an idea,
01:13:02
around what to kind of what to do with that, which is, there's going to be this entire not gonna get into details of it yet because it's too good of an idea to actually just put out there in the world, and I'm not I'm not ready yet to do something about it, but, once I get paid. But, wait, prompt prompt dot com goes to, like, a coaching for essays. I know. I know. But this is the
01:13:23
transfer is still happening. I don't have the domain in my possession yet, but the the deal is done.
01:13:29
Dude, so your your per your portfolio of domains, I mean, mid eight figures then.
01:13:36
Yeah. Tens of millions.
01:13:40
Yeah. Fucking insane.
01:13:41
Did I feel amped? I I, like, when we were talking to when we were talking to pump, I, like, wanted to go, like, hide under the covers because he freaked me out about, the billion or the million dollar Bitcoin thing and the banks. With this thing, I'm like, I gotta clear my schedule. I gotta go learn all about this. I mean, I feel amped. This is awesome. Before we go, give us your two minute reaction topologies
01:14:02
warning slash bet.
01:14:04
That the US dollar will crash and,
01:14:06
Bitcoin will surge to one million dollars.
01:14:09
I'll say this.
01:14:11
And I don't know him personally,
01:14:13
but
01:14:14
he's, like, quite literally one of the top five people I've ever encountered, like, even on the internet, in terms of raw
01:14:21
What I call wattage, just raw horsepower, and, he
01:14:25
he's like an AI into himself. Right? Like, just, just the dollars that he has.
01:14:29
Having said that,
01:14:32
I think
01:14:35
I understand why he's taking the extreme positions,
01:14:37
because that's sometimes what you have to do to kinda shake the world out of its reverie and it's like, okay. Pay attention here. This is important.
01:14:44
But if I'm a betting person, I I would not bet that the odds are,
01:14:49
what what
01:14:50
do you think they are?
01:14:52
Could happen, but nowhere near the probability that, that he's suggesting. That's I feel better now.
01:14:59
I feel better.
01:15:01
You're I I like your opinion better. Therefore, I think it's true.
01:15:07
We should wrap on this because one of the things that happens anytime new technology comes along when we saw this a little bit in in the kind of crypto web pre world as well,
01:15:15
is that,
01:15:17
entrepreneurly minded folks will see this kind of new thing, and they will look for
01:15:21
Kind of the quick turnaround. I'm I'm all formed,
01:15:24
creating value quickly, but it has to be like creating value. Don't play the arbitrage. Oh, I'm gonna do this thing. This is like, you know, day trading back in the day or whatever. It's like, you know, don't be a grifter. Right? Like be
01:15:34
be something that's gonna be brief. We're gonna build a shitty app and put web three at the end of Yes. You know, like, just don't take advantage of people. There's enough real problems to solve where real money could be made. And, yes,
01:15:45
this technology can now be used in creative ways, by lots of people, and you should use those. But don't use as an excuse, just to
01:15:53
kinda be a, like, a AI tourist that comes through makes a little bit of money or whatever, and then that was that. There's this. There's a bigger opportunity. I think you're shortchanging yourselves, if that's what you end up doing.
01:16:03
Well, thank you, Dharmesh.
01:16:05
Thank you for coming on the pod. This is awesome, man. Yeah. Well,
01:16:08
thank you for coming on the pod. This is awesome. I, I feel pumped, man. I I always like talking to you.
01:16:16
I, but I don't know if you know this, Sean. I slacked our mesh all the time. I'll just be, like, I'm just trying to get him to, like, give me little, like, crumbs of information because Did I let me get into the HubSpot slack?
01:16:26
It's awesome. I'll just, like, just send something his way. Just hopefully, I can get something back. But it's fascinating, and I feel lucky to be able to have have you as a friend and
01:16:36
coworker, and and this is awesome. And a podcast guest, you're this is so fascinating. And I agree with what Sean said about, like, kinda, like, looking up to you and, like, looking at how people live their definitely someone I admire. So I'm I'm happy you came here. Thanks. Thanks for having me on again. This is fun as always.
01:16:51
Awesome. Alright. Thanks for coming on. That's it. That's the pod.
00:00 01:17:16