SPEAKER_00: yeah ai's ai has gotten pretty pretty crazy just reminds me of like seeing the internet for the

SPEAKER_01: first time and you're like how does html work and they're like look view source and i'm like okay and they're like okay now put it over here and use this hot dog editor i'm like what hot dog

SPEAKER_02: editor you dreamweaver and i'm like okay wait a second and now wait you reload okay reload the

SPEAKER_05: page remember those conversations reload the page that's really good yeah it's it's definitely feel like mid-90s uh discovering the web and then and then mid-2000s of like we had ajax he had like like a bunch of just came together yes and it all just worked this week at startups is brought to you

SPEAKER_07: by squarespace turn your idea into a new website go to squarespace.com twist for a free trial when you're ready to launch use offer code twist to save 10 off your first purchase of a website or domain masterclass learn from the world's best minds anytime anywhere and at your own pace get 15 off an annual membership to masterclass at masterclass.com startups and hampton are you a startup founder or ceo seeking expert advice join hampton the private highly vetted community for high growth founders get invaluable insights connections and support to accelerate your business at join

SPEAKER_01: hampton.com quiz today all right everybody really thrilled to have a long-term friend of mine incredible entrepreneur and part-time internet comedian aaron levy is back on the program for his fourth appearance

David Friedberg: just to tell you how long he's been around episode 224 in 2022 episode 389 2013 episode 1173 february 21 and again today this uh puts you getting close to the five timers club what's the what's the record

SPEAKER_13: well there are some journalists who have done like news roundtables on a regular basis so taking them

SPEAKER_01: out we do have a number of five timers uh andy ratcliffe um has been on i think five times um glenn the ceo of redfin's been on maybe four or five times but it's it's it's rarefied air that's

David Friedberg: a good that's a good club all right it sounds good it's a pretty good club and it's um but brian chesky uh joined the first timers club just yesterday he did a great episode and convicted felon

SPEAKER_01: um uh from fire festival uh was on yeah and that was our first convicted felon if my pr team had

SPEAKER_22: known about that i don't think i'd be on right now so this is uh remarkable that uh we snuck this one in

SPEAKER_19: we did we're doing we're doing the felon now this is okay all right you know billy mcfarland was like

David Friedberg: i'm a super fan of yours i've been tracking you since high school and i am turning it around i mean i learned a lot of lessons and i'm like what's it now fire festival too oh okay okay

SPEAKER_30: good he learned a lot of lessons uh would you like to sponsor it okay but he has 28 million

SPEAKER_32: dollars in restitution he's paid off 40k he's charging eighteen hundred dollars an hour to do

David Friedberg: marketing uh for people yeah uh so he's just basically like a marketing guy yeah who's two out

SPEAKER_01: of every i think like two out of every three dollars he makes goes to the government and restitution he makes like 30 cents on whatever dollar he makes for the rest of his life wow okay so 20 30 years from

SPEAKER_38: now it's paid off and and then he'll be he'll be making profit exactly so you i mean it's kind of

SPEAKER_41: like a series d company in silicon valley today uh hey oh um but i wanted to have you on uh because

SPEAKER_01: you and i were uh just talking about my lord ai is moving fast yeah and box uh i was uh my poker game last night and somebody said well box is the obvious best company to incorporate ai because i mentioned you were going to be on the pod uh so you got a nice shout out there at the poker game and i noticed you started sharing some demos so i think just your general perception at the start here to level set of the impact of this technology and how quickly it's moving because it does seem like this was a very slow kind of grind and then very quickly became wildly impressive so your thoughts on

SPEAKER_26: that as a technologist yeah i mean i i would characterize it almost exactly the same way which is and i think most people really deep in ai would probably say the same thing i mean it's kind of like you know 10 years we've been you know incrementally making this progress and you know you had the the transformer paper five years ago and it's like well you know that's obviously a big unlock and then you had gpt2 and three and and you know i i think we probably both played around with the early versions of gpt that you know the gpt versions and and it was like you know super interesting in terms of oh that's kind of cool a computer can do that but there was like i don't think i don't i certainly didn't have an aha moment of like all of a sudden this is going to be incorporated into all software i thought it was like a really you know compelling um you know demonstration of of what we can now do with text prediction and and whatnot and then obviously chat gpt kind of both the combination of of its improved you know 3.5 model and the just the right interface um you know to capture the zeitgeist of of what we can now do with with ai and interact with ai and so um so that combination you know obviously um you know put us in a completely different conversation about where ai would be incorporated and so um so we had we've been doing seven or eight years of work in ai um and uh that the challenge was every single use case a customer had you know i i want to understand my contracts i want to understand my film scripts i want to understand my blueprint files every conversation we had was a different ai model that you had to narrowly you know kind of train and implement for that one use case and so it never really scaled because it would be like you know be like if we were building on the web and every feature you wanted to build you needed a different you know you know tech stack or cpu for that feature just would never scale out to all the different you know kind of scenarios we had and you know with three with gpt 3.5 and now four it's like it can just solve all the things so it can do the contracts and the film scripts and the um and the press releases and the marketing documents and the blog posts and so it just understands everything and um and then you can implement it in these much more generalizable ways which is which is a real breakthrough in terms of

SPEAKER_49: just you know how many use cases we can now solve with with ai so when you saw uh you know gmail

SPEAKER_50: 2018 2019 you know predicting your next word or two you know okay pretty clever yeah um that's helpful uh and but it wasn't like an aha moment what was your aha moment in the last couple of months

SPEAKER_57: where you said okay i need to and i'm assuming this is the case correct me if i'm wrong i need to get

SPEAKER_48: the entire company dialed in yeah 100 on this opportunity yeah i mean i i mean the the um the

SPEAKER_26: specific revelation was probably no different than anybody else on the internet is just you can give it literally any prompt and you know at 99 likelihood it's going to come back with a response now now accuracy aside for a second and we can get into kind of how we solve that problem um uh just the fact that it will attempt to do everything was was sort of the mind-blowing moment yes i remember uh like probably my first like like big aha was was you know you you initially start with use cases which are like these like very straightforward kind of facts um because like we're so used to like we go to google and we type in a thing and then we get an answer and so your first things are like wow like it's really cool that i got that answer um so it was like really basic questions of like you know what's what's the better way to to travel uh you know between you know x and y place and and you're like oh wow that's actually pretty cool like i thought through you know you know you might have to wait at the airport for this long and so maybe it's actually more efficient and some in this case to drive and so that was pretty cool but very fact-based um and then and then like when you when you start to give it things that are not fact-based but actually things that it has to take two pieces of distinct information and and kind of combine them and reason through it and i was like that was really where i was starting to be you know my my head started to explode where um i you know we were giving it like um uh so you know peter um uh michael porter uh uh uh sort of five forces framework which is this sort of competitive framework of how you think about suppliers and competitors etc and so so take that um uh take that concept and apply it to apply to things that that no one has ever done uh a michael porter five forces for ever like like in the history of of the world yeah and and it just did a really really good job like we were like do michael porter's five forces on an airport and and it and it it was able to take you know one set of information it has and then combine it with a completely unrelated topic and and basically completely exceed what even a human would probably have answered yeah you know for that and that was the big breakthrough of like okay so this is not just going to be this sort of question answer engine of of raw facts it's actually going to produce new information for people and then become really an assistant where you can just go to it um and ask it anything and so that's that was you know some more of the aha moments when you start to take and combine those those you know two unrelated things and you're actually leveraging the fact that it has a wealth of knowledge within it um and um and you know way more than any what any person would would be able to keep track of um that's where you really get the power of it and so then we said well what if we combine our data set with that and and then you start to you know kind of create new use cases that just never before would have been possible and that's that's where we you know kind of you know sort of didn't like do a full company pivot but but about as close as you do when you're you know 2500 people and we just said okay this is a big moment for us we're going to go in and incorporate this technology if you can tell from the podcast lately

SPEAKER_64: we've been doubling and tripling down on founder university to launch in fact it's basically the future of our venture capital firm and that's awesome because i'm working with a couple of hundred early stage founders really early and getting to see what tools they use you know what tool they show up with most they show up with squarespace they put up their first website instantly quickly with squarespace and it's beautiful and it makes them look like a million bucks the thing you may not be aware of is that squarespace beyond the beautiful templates that make your company look like a million bucks and that work on mobile it's not just a pretty website it is a powerful e-commerce platform now and they have member areas what's a member area you know people like to sell content now and premium content it's a big business well they have that built in to squarespace and they

SPEAKER_66: don't take you know double digit percentages of your revenue like those other platforms do and those have appointment scheduling so you know if you're doing a business where you're a consultant you want to charge for your time well you have scheduling built into it as well and this is the the brilliance of squarespace it's going to look beautiful as you know so here's what i want you to do just head to squarespace.com slash twist for a free trial when you're ready to launch use the offer code twist you save an extra 10 off your first purchase of a website or a domain we love your squarespace you know how it is when you're a technologist everybody in your family your friends your circle your network come to you and say hey i got to get a website up can you find me a developer a designer a product manager and you just say you know what yes i can find you all that and more

SPEAKER_01: at squarespace.com twist how many customers broadly speaking do you have how many documents

SPEAKER_57: are in the repository and then how do you start this process of uh the very scary um prospect i think

David Friedberg: for some customers of oh my god am i feeding my data to this and is it going to wind up jumping the fence am i am i training the box model or the open ami model and and are they going to use some corporate secrets and a strategy document and then somebody else says hey how does michael border you know reinvent an airport and a new airport in new york and that was their proprietary stuff so that that's like got to be objection or concern number one yeah yeah so let's let's start first with

SPEAKER_71: that and then and then we can kind of talk about actually what we what we're doing so so first and

SPEAKER_26: foremost just emphatically um uh first of all uh you every interaction you have with box ai is is explicitly your you have to decide to use it um as either a user or the enterprise so we're never having ai kind of do anything in the background um without your explicit you know kind of consent on using the service that that's the first thing the second thing is that that at least for all of the use cases that we're talking about right now there's no training whatsoever um you're you're just using the ai model in its sort of stateless form um as uh as really a reasoning engine um uh to be able to to help us with natural language uh you know type tasks and so um so there's no training of the ai model there's no um there's no logging of the information that you gave the model so it can train later all of that is done um in this very kind of stateless ephemeral way where we're just kind of asking the ai model to help us um with the the user's query and then and then probably the third big element is just we have a very very high standard for security compliance data privacy just by virtue of of our customer base our you know very you know large enterprises across every industry you know hospitals federal government etc and so we really really take um you know security and privacy very seriously so um so we're not you know trying to lean into any of the privacy elements from a risk standpoint this is completely um uh you know meant to be a very very um uh uh you know a conservative approach to how we're going to treat you know data privacy and compliance

SPEAKER_57: now certainly there must be some early adopting folks and some ceo calling you saying hey i do run

David Friedberg: this organization i would like you to create a language model for me across these 4 000 employees and i as the ceo god king or queen uh would like to be able to do queries or my management team across our entire corpus of documents so is that on the road map and are you starting to get those you know

SPEAKER_57: sort of um i'm all in requests from your customers we we are actually and and uh and what's really

SPEAKER_77: interesting about this is um is it's not even um it's not the obvious sort of cut lines of you know

SPEAKER_26: kind of conservative businesses versus more aggressive businesses and and you know sort of unregulated um uh we're seeing that most cios most ceos are recognizing that you know ai is a real platform shift um this is much like you know mobile or the web in terms of we think about it as a platform shift it's a scenario where um where you know this is now me talking but but our customers are kind of reinforcing this which is it's a general productivity uplift where we can use this technology technology to you know make decisions more effectively find information faster um spend more time on the right areas of our business that only humans can do as opposed to computers could do better um and so we're seeing you know almost universal optimism about how to leverage this technology of course there's a long list of you know um you know items you have to just go through from a compliance security privacy standpoint but but in general the it's um you know across our 110 thousand plus customers um obviously you know we we we spend more time talking to some of the larger ones but there's a lot of a lot of excitement around it and um and you know there's a lot of nuances though so for instance this idea of training you know um a model with your enterprise data it's actually not not clear that that is a a problem that that you know we can really easily solve at the moment um because because when you train a model um you know with with proprietary data it's very hard to sort of figure out well which things should we leave out of the data set because they might they might accidentally inform the model and then and then give up you know kind of sensitive information

SPEAKER_57: to you know the wrong employee as an example so so we have permissions are paramount here and permissions are in the previous file sub file organization are just not the paradigm that we have just shifted to

SPEAKER_84: the paradigm is here's everything and well well so that that's actually so this is i mean humbly this

SPEAKER_26: is where we think we play a a role which is which is actually you do want permissions on on the data that um that the user is going to want to be able to query against it and and the ai model is really used as as basically this you know uh brain to understand the information that you're giving it that the user already is allowed to access um and and that and you're using that that basically ai model to reason through what what that user can already access so so you know at least in today's architecture landscape and there'll be you know different approaches that different companies take um the the uh the point is not to train a model on your enterprise data because again then then all your permissions are going to be leaked into that model it's to separate the underlying access controls that people have to information from the ai model which you use as a reasoning engine for that data and that got it that's at least for our kind of use case which is a lot of sensitive data but you do want to be able to work through it with natural language um that might not be as relevant for maybe if you wanted to have a train against your code base where all of the engineers are allowed to see all of the code base that's something where you might want to have then a kind of a

SPEAKER_87: specific enterprise example would be legal and hr the legal department everybody being able to query

SPEAKER_24: the legal departments could be any kind of settlement agreements or confidential agreements exactly come

David Friedberg: up and then somebody typing in who are the most underpaid people at this company and they're like oh it's me that there's the most overpaid people at this company oh yeah so you can instantly imagine

SPEAKER_26: like past like 10 employees you can't train you know your entire enterprise on on you know uh your entire entire enterprise data set on a single model so this is the this is basically where our work has has gone it's only you know we're only four months into it um but it's it's gone to this abstraction layer where we can um keep the access controls in place but use an ai model to reason through information that the user is allowed to access and that's we think that's going to be the breakthrough

SPEAKER_57: for how we implement this makes total sense the head of human capital has access to all of the human resources information but a recruiter might have only access to 10 of the information and they might do different queries about different on different data sets and summarize or whatever so how about some demos here of uh you know the i would suspect there are things that are really easy to implement uh and uh provide massive value you know like we like to do as product people we put those on an xy chart uh those would be like the quick wins yep big impact everybody's going to use it and it's uh easy to implement what did you get to first and then we'll get to the harder ones uh sure so we um uh

SPEAKER_77: i feel uh this is this is fun going back to like the startup roots of uh a forced live demo so um here's basically how it works so i'm in um i'm in my box account right now just looking at at one file

SPEAKER_26: and uh this is actually it's a little meta because it's the press release for the announcement but um it's just an easy kind of public document so um uh so this is the press release and you'll be here you know you just click this box ai uh icon we're still going to continue to play with with the ways that this gets incorporated um in the product but but for now it's this sort of chat interface on top of your content and so now um you know this would work whether it's a three-page document or a 500-page document but again for demo purposes we want to keep the symbol um and you just say you know um please summarize this announcement and um if it if it works uh um pretty quickly because we're in a

SPEAKER_38: dev environment yep it'll just go in and summarize the announcement and and then you say what are three

SPEAKER_77: use cases for box ai and and so the key is it's saying according to this document here are three use cases so it's not it's not attempting to kind of go into the large language model and say what do you know about box ai and can you respond to it it's just saying from this document uh what are you finding inside of this piece of information that could answer this query so that that's sort of the

SPEAKER_26: the way that we've set the prompting up and that also then dramatically reduces kind of hallucinations um that that you might see because it's not attempting to make anything up um it it really is we're really kind of forcing it to stay um you know within the document but there's one little there's one you know kind of cool thing which is which is while we're telling it to only answer questions based on the document we're giving it a little bit of free reign when you want to do more transformation you know transformative type use cases so um let's say you want to take this document and turn it into something we're we're you know instructing the model to um uh to go along with that so so as an example um i'll just we'll just see if this works out um uh to prove my point or not um

SPEAKER_99: please write an email to an automotive company pitching box ai and please include three auto

SPEAKER_81: specific use cases so so in this query um you know there's not this information is not in the document

SPEAKER_26: but we're we're sort of you know having to go along with that instruction to say use this source information to answer this question still we'll see if it if it kind of comes up as a desired answer um and uh and so you know it's a it wrote this email to an auto company um about uh about use cases that they might have for box ai and so so now you can imagine you know you're a sales rep and

SPEAKER_77: you're looking at you know a product marketing you know pdf and you really quickly want some ideas in

SPEAKER_26: front of a customer of like so what are some use cases for this new technology you know box ai would be this assistant for you to go and quickly you know answer that question um and so any basically any kind of um you know tasks we give it other than just using the large language model as the the sort of

SPEAKER_49: database of of answers um it will it will generally do on your content and then um yeah sorry well i

SPEAKER_57: was going to say this you know when you when you have a good demo like this your mind starts to just come up with ideas yeah i was immediately like who in the organization has to approve this and uh i wonder if i connect this to my email and i can source 100 leads from the database who haven't been contacted so you start to get into information you probably have which is the org chart and the permission so who you know you could be asking who handles the automotive category on our sales team in the united states can you get them to approve this and in our sales force or wherever

SPEAKER_24: that data is stored can you get me uh you know all the sales leads in automotive that haven't been

SPEAKER_77: contacted this year yeah yeah exactly and so your your mind can instantly kind of extrapolate now what's

SPEAKER_26: possible now what's interesting is this is where this is where you know we in the valley and everybody you know i mean you know figuratively or literally you know have to respect that um the technology can do all that but we're probably like five years away from from you know society actually understanding how that would all come together and having the technology actually integrated in this kind of capacity and so this is where and i remember i remember when we were first you know rolling out um you know cloud to enterprises it was you know oh six oh seven oh eight you know we were in front of enterprises and and you know we had our early adopters and and my hunch was like okay in like three years from now obviously every single enterprise workload will be in the cloud it's so it's so clearly obvious to the entire world how much more efficient this is how much more scalable it is how much more secure it is and you know fast forward it's it's now you know uh 15 years after that prediction and and we're we're still in the phase of like mass adoption of cloud computing and so and the reason for that is just like you know the world takes a lot of time to change on these really big tectonic shifts and so um you know the use case you just may you know mentioned it's got to connect email and salesforce and your data from box uh that's going to be a lot of wiring together that we have to that we have to you know uh come up with and then what will be interesting is do the ais talk to each other so yes does the box ai talk to the salesforce ai which talks to your email ai and they are coordinating um you know that that information exchange um in a in a you know a secure way um uh and and we are again we're at the just the starting point of how does that actually get

SPEAKER_114: architected one of the reasons why criticism can feel obnoxiously aggressive is that sometimes people use criticism to sort of dominate or assert superiority and that is not helpful criticism

SPEAKER_117: so state your intention to be helpful that was radical candor author and friend of this week in

SPEAKER_119: startups kim scott and she just did a master class session called tackle the hard conversations with radical candor if you're a business leader you can learn so much from masterclass there are amazing lessons from bob eiger on leadership chris voss on negotiations and our friend alexis ohanian on startup investing and so much more legends of their craft are a masterclass teaching you whatever you want to learn paying for an unlimited masterclass subscription is a total no-brainer we just had an awesome insight from kim in just 15 seconds imagine how much you're going to learn in 10 minutes or an hour or maybe two if you invest that in the next couple of weeks i highly recommend you check it out get unlimited access to every class and as a twist listener you can get up to 35 off for mother's day what a gift go to masterclass.com startups now that's masterclass.com startups to get 35 off for mother's day

SPEAKER_57: yeah this guide on the side um concept feels really powerful um in terms of just efficiency when you look internally at your own company what would you predict if i had to ask you in a percentage basis that you know the average team member or the entire organization how much more efficient will they be by the end of 2023 yeah if you get everybody to adopt using chat gpt and other ais how much more

SPEAKER_26: efficient will your company be yeah it's this is this is the you know the the big question i think for all of us and so if you if you kind of imagine let's say every every knowledge worker uh for for now just starting out with that demographic um you know has an ai or multiple ai assistants that do relevant tasks for them um you know workday will have one for hr salesforce has one for sales um you know yeah everybody but everybody has kind of ai incorporated their workflows um i think that the way that we should think about it for now is is how much time do you spend in your job trying to you know triage information sources find answers to questions um sort of do more information you know based tasks um you know writing something brainstorming something you know discovering something um uh and you know depending on the job uh you know if you're in let's say you know customer support that could be like 50 of your time because you're always going back to the knowledge base and you know trying to get an answer to something um if you're an engineer you know you'll you'll go talk to engineers and and they're spending you know two or three hours to to find like who on the internet has optimized this particular sql query before and and like that's like you know theoretically instantly solved um inside of gpt4 or copilot and and that just becomes this unlock and so i think depending on where what your job looks like um you know somewhere on that continuum uh is is you know you might get back 50 of your time you might get back up you know 20 30 of your time and and my um and my kind of like like totally amateur hour macroeconomic you know kind of um uh you know kind of view of that is is that is that we won't really even notice what what you know how to measure that because because the that engineer or

SPEAKER_59: that that customer support rep will just be doing they'll be doing more of they'll just get to the next

SPEAKER_24: task faster they'll get down the road map faster they'll get to the next sales call faster exactly

David Friedberg: so it's not eliminating their position it's augmenting them and when i talk to brian chesky about this you know what number he came up with what 30 and i had come up with 30 because i was like of efficiency improvement across all of airbnb employees and i just thought about that well hiring has

SPEAKER_57: been in that 10 or 20 a year range so on a meta prediction i think you could see organizations

David Friedberg: instead of trying to hire somebody you know to throw a body at it kind of management culture i think the next two years of management culture who knows how long will be how do we get the ai to do this is there a prompt we're missing is there a different ai tool should i be using poe from quora is bard

SPEAKER_48: going to do a better job you'll be just ai shopping chatbot shopping and i think 30 is the right number i

SPEAKER_71: think it's like yeah so so so i think that this this is going to be this have been this will be um extremely interesting to watch um you know clearly but um i think there's a couple ways to

SPEAKER_77: cut it so so there are some things there are some tasks in a business that are are not kind of like

SPEAKER_26: infinite they're they're like they just have like this one discrete thing has to get done and so if you make if you make that one discrete thing 30 more efficient then you scale that out and then almost by definition you would you have 30 less labor you know across the economy or across a particular business for that thing but then there's a lot of tasks that that are are are not kind of finite they're they're uh they are like literally kind of you know bottomless and boundless in terms of ongoing yeah ongoing and so i think engineering is one of those things which is we are always constrained we are universally always constrained by the number of engineers we have and so if i can make our product roadmap go 20 or 30 percent faster that does not that we are going to hire the same number of engineers that we can afford we're just going to accelerate the the we're just going to be on a relative basis to what we would have been doing 30 more productive yeah no different from 10 years ago we were probably 30 less less productive then because we had engineers working on you know different open source libraries or different you know systems that now the cloud just does for free for us but we didn't hire fewer engineers as a result of that efficiency we actually if anything we hired more engineers because they could actually go and do more productive tasks as opposed to these sort of lower level maybe a lot less differentiating tasks and so i think for areas of your business where there's no particular upper limit there's no upper limit on how many sales reps you need how many engineers you need um you know how many um uh uh you know you know how many account customer success you know managers you need because those things are only constrained by how many customers you have or you know how innovative is your company and your roadmap and so so i think these just become accelerants into the future and then there are going to be areas where there was the finite limit um that you actually need and and we can make that that area of the business more efficient but i'm i think there's more areas of businesses that are boundless and and um uh and kind of limitless than those that are you know inherently finite yeah i i i agree strongly

SPEAKER_57: because if you just think i was trying to think of which category would be one that could be like telephone operators you know like okay that's just completely been replaced or you know travel uh agents who book your tickets for you right and they type in the search instead of you doing okay obviously those went away um and then i just thought well okay maybe customer service or success and then i thought

David Friedberg: about and i was like you know what you're always trying to get a customer to be more successful with the product right so instead of dealing with login issues or navigation issues those will be done by the ai yes but then you'll be getting to like here are some scenarios for you to use our product here's some you know advanced scripting stuff you can do with this product you're going to just

SPEAKER_72: go to the higher level stuff that makes people turn less um and yeah it just feels like for there's going to be a group of people who resist this but i don't think they should be scared i think this is like an incredible opportunity it feels to me like we just went from dial up to broadband right all that did was increase joy uh you know and usage when this is going to speed up developers i think the developers are going to be stoked to be more efficient and get more done

SPEAKER_77: yeah there's no developer uh that i've talked to that has been using any form of ai for for productivity that has been like i really wish i could go you know do that research again of how

SPEAKER_26: how people you know optimize this query or or how they interact with you know this external library or api like like no matter what everybody is like if i could just see a quick example of of you know how everybody on the entire internet solve this problem i'm going to be able to leap forward faster it doesn't mean you like copy and paste the code and you just you just implement it you know with without um you know without any additional labor um but the speed of of which now you can jump to the next uh task and the ideation you have uh is just so much faster and so i don't think there's any any returning you know from that um but i'm i'm way more in the optimistic uh camp of this just acts as a general

SPEAKER_57: productivity lever uh for the the economy yeah it this feels to me like the way out of whatever economic situation we're in um just like mobile broadband it just kind of helped the economy uh and you know and founders get enthused i mean i can hear the enthusiasm in your voice you're in the office on a friday you know just getting it done and are you feeling that the enthusiasm enthusiasm level inside the org has gone up because listen it's been a tough 18 months stocks going down layoffs and big tech is this changing morale yeah we we we we have um you know we've been in kind of

SPEAKER_26: hunker down mode for for three plus years we went through an activist battle and and so we've kind of already had this grinded out you know kind of mindset so fortunately so fortunately that's been kind of baked in but but i think you know independent of our specific uh you know um uh you know morale on that front i think this is this is sort of what we all live for in tech is like you want there to be a platform shift at some at some interval you know 10 years 15 years um that just shakes things up and um and you just i mean it's it's exciting that the companies you thought were monopolies now are are you know they actually have you know real um you know strategic crises that they have to go solve um there's an all new technology that is just really fun to to play with i mean um you know most of the the work that went into to box ai was you know these are like 1am sessions um you know with with the the the team or cto on like okay can we how do we solve this and and how do we figure this thing out we hired a we hired an intern at at midnight on a saturday um uh and just just you know some some kid at stanford that was just like online and ready to rock right away um love it so it's just like those are like the fun i mean i'm probably being like overly nostalgic in uh in our uh in our strategy here but like that that's what makes starters fun is is you know something comes out of left field you have to adapt to it you have to figure out you know is this a tailwind or a headwind how do you incorporate the technology um the other fun thing about about ai specifically is that it has the surface area of it is just so large where like every day you're either somebody externally is doing a discovery that that opens up you know we saw the auto gpt thing just yeah a month ago and you're

SPEAKER_151: like okay well that's a whole new vector of of innovation plugins well the plug-in data analysis

SPEAKER_51: did you use the data processor yet um i have not used that one uh is that is that pretty nuts like

David Friedberg: you upload a csv file and you're like it's like okay here's the columns in it and you're like okay um tell me about the data and it's right tell me three trends and it's like okay it seems like uh and i just uploaded like an airbnb csv of like all the different la things and it was like yeah it seems like santa monica has more than this place and this you know and the average price is this and i'm like whoa i said make some charts and it's like okay here are some charts and somebody did it internally we were doing diligence on a startup and we just took the diligence folder uh and uh took their revenue and projections and everything and said make some charts and tell us about this and he hallucinated there were some bum charts that didn't make any sense you're like this makes no sense um but then there were some that were like oh yeah that would be something that an associate in a venture firm

SPEAKER_57: would spend two hours on and you know the the researcher just did it and it's like okay great

SPEAKER_77: it's it's it's totally crazy and the fun thing is actually like you know even the demo i just gave

SPEAKER_26: you are kind of like the obvious things that you would do with ai but um when you start to think about about like the non-obvious stuff and actually part of our problem is just gonna be how do we help encourage people to leverage this um in these non-obvious ways that's where it gets really fun so um uh so what one scenario we gave it like our earning script from from one quarter and we said um uh you know if you were warren buffett um how would you improve this earning script and um it's like a random use case like nobody in the entire world would ever have you know asked that question of an earning script but all of a sudden it starts to amp up the cash flow message and the share repurchase message and the capital allocation message and so now you know when you're preparing to go in front of a whole bunch of financial analysts um and you want to you know figure out

SPEAKER_77: what's the right tone what things should we lean into you have this in you know instant expert uh that's seen the entire world of finance everything ever written online about you know every earnings call

SPEAKER_26: every you know ever and you have that now instantly at your disposal and so yeah you know if you if you have a little bit of imagination on how you can start to incorporate ai you know per your due diligence use case or um or any way that you want to work with your data the you know literally there's just not not there's not a limit to what you can do with this stuff the most interesting thing i've

SPEAKER_57: found is when you push it to become more creative and you say give me five more ideas give me five

David Friedberg: ideas that nobody's ever thought of before give me 10 ideas that are crazy and like you literally use words like this and it's like okay permission granted and like then the genie starts doing your

SPEAKER_72: wishes and you're like whoa when you're the founder of a high growth startup things can get chaotic we all know that you face a ton of questions you got problems all day long and you don't know the answer to everything especially if it's your first time as a startup founder but you don't have to face these

SPEAKER_119: issues alone that's where hampton comes in hampton is a highly vetted private community exclusively for founders and ceos like us hampton's mission is to create the most valuable and engaged community for high growth founders here's why some hampton members have already called it life-changing when you join hampton the membership team over there carefully handpicks seven other members to join your core group this group is like your own personal board of directors they provide you with advice critical feedback and will aim to help you accelerate your growth hampton members run some of the fastest growing startups in the world and you probably use their products and services like morning brew blank tree coffee dribble and more the connections personal accomplishments and a sense of belonging are what make the hampton membership special and you know community is super important it can get very lonely out there as a startup founder so here's a very simple call to action if you're ready to scale your business join the hampton community today at joinhampton.com twist that's join h-a-m-p-t-o-n dot com slash twist today joinhampton.com twist today i don't know if you've been following the writer's

David Friedberg: strike which started this week in hollywood and on page two of like the update to their members the last like item before like the coffee and donuts or something completely meaningless in their negotiation was uh we're asking for a ban of ai to write scripts to ingest previous scripts and to use it in the future to create derivative works and uh then there was like what the uh studios said back to them the studio was like we will agree their counter was we will agree to do a yearly meeting on new technologies and i was like yeah you know what you need to do writers and i just took i asked it to come up with just for giggles and to you know put it on twitter i said give me like five themes about biden and five themes about trump that a late night writer uh for a late night talk show could use uh to brainstorm jokes and it was like yeah biden you know sometimes makes gaffs and he loves ice cream and trump uses weird words and he's a narcissist and he's addicted to twitter and i was like okay well that nailed it then i said oh do a twitter exchange between the two of them uh that's funny and it started making some and they weren't zingers like they weren't ready for prime time but they were good brainstorms and so i guess the question is like did you get early access for

SPEAKER_176: your twitter because you're hilarious on there and what impact is this going to have on your joking

SPEAKER_77: on twitter um i think um i have not i have not yet fed it uh uh any any twitter stuff on and you know twitter is its own vector of uh of uh you know kind of landscape right now but um yeah on the on the

SPEAKER_26: writer on the writer's strike thing here's the thing i'm actually uh uh super sympathetic to uh to to any uh any demographic that that thinks that ai is going to have an impact on their job simply because it is this foreign technology it's coming out of nowhere nobody wants to feel um you know vulnerable um in in everything they've learned their whole life so i actually i'm i'm like i totally am um um uh uh you know of the view that that these are super important conversations there's not like an obvious thing of like you know select value is really gonna have to you know try and avoid the the kind of like like oh i you know learn to code yeah exactly exactly it's just it's like it's like we have to be thoughtful about about these kinds of of trends the reason i'm optimistic is is just because i think there's still you know um uh there's uh to even your point like they weren't zingers like like you know and so um so i i think there's a lot of of stuff that that you know is is still in this like it's novel because it's new but it it is not actually going to you know really be able to go and replace the level of creativity that a human has for the vast majority of of ways that that you know we actually pay creative people for you know today and and i think there's a kind of a little bit of a divide i think there's there's the use case that you'll see from something like mid journey which is which is you know really really compelling you know images um and and i i think the scenario there is that we just end up having more ubiquitous creativity uh from so many more people but the experts get even better um and and the idea generation increases you know tenfold across the world because now you can be you know some random kid in in high school and you could you know be ideating on a new product you know design that would never have you know existed in the world but now you have this ai engine that can help you with that so i think creativity just explodes because of this and on the on on the you know and more of the professional trade side um i'm i'm just bullish long term on on humans really really like other humans to create things and yeah of course and there's some and it's just totally different to imagine going to a movie that that ai generated from you know something that that quentin tarantino made um and so i'm i i just don't think that our brains are wired to care about about you know if a human didn't make it but and the field is entertainment i'm i'm skeptical that that's going to replace you know what the humans are doing if you look at cgi

SPEAKER_140: they thought okay this is the end of acting this is the end and it's like yeah blade runner and star

David Friedberg: wars use miniatures right amazing and then you go back and you look at the miniatures and you're like it's kind of taking me out of the experience like right it doesn't look that good and then you see cgi today and you're like you know what we can make you a star wars series every three months for you and your kids and yeah so are there less creative people no there's more right because now

SPEAKER_01: you can go down the long tail of content and you can make the ashoka series about anakin skywalker's padawan and it's like okay great go for it actually i mean exactly to this right like this is actually

SPEAKER_77: i mean you remember i mean you know oh six oh seven and oh eight we thought like you know well we're just going to be watching youtube um and ugc is going to disrupt all hollywood and like all the tech people were like oh this is the end of hollywood and it's like no like like if anything it actually you know contrast the quality of the really good stuff even better and we get just as excited or

SPEAKER_26: more excited about the about the good content and so to your point i mean ai is an enhancement um to

SPEAKER_77: to that creative task but but from everything i've seen not a replacement of it's going to do something

SPEAKER_72: great for startups too like when we started what did you spend on your original logo this is like a question you can tell like when a founder started the company and how much you spent because in the the to that oughts or whatever they call them like you would actually pay to get a logo done in all likelihood and what did you remember what you paid for the first box logo um uh i actually designed it

SPEAKER_151: uh so uh so so um it was free in our case but but yeah i mean that that's a five ten thousand bucks um

SPEAKER_26: actually i probably spent 20 hours just rounding each of the letters yes um so way way too much time

SPEAKER_84: uh it would be way better to have a headache but you got quoted five to ten oh easily yeah yeah and

SPEAKER_24: you're like well i have more time than money so i'll just do it myself on the weekend uh and now

SPEAKER_01: you know then there was like this medium period where like these websites dribble behance whatever fiverr you can find all these folks and you can get a logo that's reasonable there were design competitions like 99 designs and other ones for like 500 bucks 250 bucks and designers were really upset about that but if you're doing a high-end logo like you still can charge five or ten grand there's

SPEAKER_72: people who will pay it like if box is going to do did you ever do your logo over again and do like

SPEAKER_189: a whole brand treatment in the last 10 years um no but i'm not trying to ruin your questions only

SPEAKER_151: because you're just that cheap well we're either that cheap or we do that all in houses so um got it but but but the but the theme is is completely accurate yes yeah and things like this uber

SPEAKER_57: redid their whole pack i remember travis redid all of uber at some point he hired an outside firm

David Friedberg: it'd probably cost a half million dollars or something like that we can afford to do it we want to have a thoughtful discussion about it and yeah i mean ai can make a seven out of ten but we want to you know 9.5 or ten out of ten we're going to go that way right i bet you all these writers are already using chat gpt to brainstorm ideas just like they took out old joke books or old scripts and

SPEAKER_176: look for ideas or watch old kurosawa movies and decide like hey this is an interesting character set

SPEAKER_73: from fortress so let's do r2d2 and c3po for the next generation yes yeah i think i think that that

SPEAKER_22: that's my take and i think the only the one asterisk that i'll i'll add is just i do think

SPEAKER_26: the copyright piece is super interesting so say more yeah well they're just just these ai models are are trained on everything they they can get their hands on um seems unfair to you you saw barry diller was like you know now is the moment you have to you know fight um if you are a content creator and um and so i think we're in for for you know a couple years of really really interesting you know case law you know coming out uh around what how this all plays out so where do you stand on it somebody

SPEAKER_57: trains on every you know song ever written and then they make new ones that seems profoundly unfair

SPEAKER_24: to me uh i mean getty images busted stable diffusion like right instantly that was like right dude you

SPEAKER_211: you're literally blurred the getty image like come on bro like that's just not cool yeah oops i i uh

SPEAKER_212: yeah where does it where does it hash out for you what do you think what do you think would be fair

SPEAKER_77: i i the the problem is is that um is you know fair uh is somewhat different from technical po technically

SPEAKER_26: possible and so we're gonna have to figure it figure that out you know i think the like intellectually like ideal outcome would be something where you know you know data gets licensed to model training um easy and and there's a you know that we all put a little tag in our website that says you can train our our public information or you can't um and then this is just txt for ai exactly it's a ai.txt and

SPEAKER_77: and um and i think that and then what is the new creative commons for for that and actually then

SPEAKER_26: probably as a result of that outcome you know the the models will be basically as good as they are today because there'll be enough information that is in more in that public domain um and maybe you know it's it's just not as good as quentin tarantino scripts um uh and that's that's sort of the one

SPEAKER_215: the one yeah i mean i think there's an opportunity there so you start thinking about as an opportunity

David Friedberg: newspapers are struggling right right um all kinds of content creators are struggling you look at something like reddit you look at something like quora you want people to participate in those

SPEAKER_24: communities so licensing quora licensing reddit yeah um and then you would have google and microsoft and facebook while competing to who gets the reddit corpus who gets the twitter corpus

SPEAKER_38: yeah maybe they maybe they give exclusives maybe they don't i'm gonna pour a little water on that one unfortunately because because you can also imagine that that the costs uh of running these

SPEAKER_26: models or training them will become so high that that it all of a sudden drops the productivity that you get from using them because like if if if the price of a token were 10 times more expensive because it had only licensed data within it a lot of the use cases i just demoed an example would would be a lot harder and so um to just just do in any kind of affordable way so then what would happen is you would end up having um you know more of these public domain large language models would probably be the ones that end up taking off um and so so i mean so it's it's like it's a nice theory that that everybody could start charging for this data but then the models would ultimately then get trained on the stuff that was was cheap um because it would just be you know we we can't have uh i i mean i don't think you could have the equivalent of the you know the comcast um negotiation wars with with you know x cable you know station um uh cable channel like for ai models um because the the the many-to-many problem on that one is just going to be at insane so imagine you know somebody comes in reddit says well we're going to pull our data and you've got to you got to pull it out of your

SPEAKER_50: model it's like like yeah it's impossible i mean basically if if if getting images wins at injunction

David Friedberg: like again like damage is being caused they could get like this injunction a preliminary injunction against stable diffusion they got to just turn the model off and start over i mean that would be

SPEAKER_151: wild it's gonna be totally wild so we're i have my popcorn um and we're gonna we're gonna stay out of that one and just and we'll use whichever ai model is legal so i like industry i like when the

SPEAKER_01: industry comes up with something like self-policing like robots.txt so i think your idea ai.txt it's

David Friedberg: great start and then you know a little bit of uh cash here and there and then citations i noticed yes i have been grinding on about this which like i don't have a problem with you using my stuff but can i get a link back uh that's just courteous and uh in the new version have you played with the

SPEAKER_72: web chat gpt4 yeah it's kind of janky it crashes constantly but when you hit the drop down it shows you what web pages it's crawling uh out on the web it shows you what search it did and it links to it

David Friedberg: yes so i thought that was kind of dope i was like okay at least i can link back to that and they get some traffic or whatever um but i think this brings like a really interesting micropayments

SPEAKER_57: concept this is where i think google i'm curious your thoughts on like google's vulnerability right now because that was the big topic last night at the poker game um i feel like this could be like

SPEAKER_72: google's way of actually cementing in like some revenue sharing with the people they index where like

SPEAKER_231: hey if i use you in an answer i give you a fraction of a penny right yeah super interesting i mean i

SPEAKER_26: mean um you could you could certainly imagine a world where they strategically would uh would want to kind of make it very very hard for any subscale player um to to you know commercially operate and so you know if you were really really like um you know game theorying this out like you'd want to be on their policy team being like oh we've got to really lock down the copyright issue um because they're you know then then you'd have to be at their scale to go and actually do that yeah um but um

SPEAKER_77: i still don't my brain can't figure out how you do the the kind of like sub penny um you know type

SPEAKER_26: type model because even in the example you just mentioned which was which is the web browsing thing that one's easier to do because it's pulling out the web pages and then using the ai model to reason through them um so then you obviously know then what what it's citing um you know if you interact with the ai model directly um and it in a sort of black box fashion where it's not connected to the internet i don't know how we uh you know eventually track like how what portion of the of the model you know uh you know came from you know conde nas traveler versus new york times travel

SPEAKER_01: section exactly yeah it's it is a but you know that sometimes these problems are opportunities all i can

David Friedberg: say is and i think you'll agree with me thank god this is the platform ship and not crypto and not vr because oh my lord the two most annoying people i've ever met are people with vr headsets trying to get you to put them on and crypto people not shipping products thank god that's something i i

SPEAKER_151: i rest my i've rested my case on crypto last year so i've i've been able to uh to move on from the

SPEAKER_24: topic but um yeah yeah i mean it's just unbelievable like this speaking of hallucinations like yeah has so much money been pumped into a space with so little to show for it yeah i think the challenge with crypto

SPEAKER_77: is is basically like the um you know there's been tweets over the past couple years which is like

SPEAKER_26: what's the best you know demo that you can do of crypto um uh and then like somebody will will record something or show something and and it always requires you to be bought into a philosophy as opposed to uh as opposed to caring about the the use case itself so so you're wowed by the fact that you know with no intermediary i could do x thing but x thing is not like wasn't like a new thing that that you couldn't do before it was just it was just a thing that we already do but now with no intermediary and so the problem is is like translating that to regular consumers like we there's not enough bandwidth to tell people why they should care about that philosophy because they just like no i just feel like like i can already do i can already move money to people i can already you know communicate

SPEAKER_246: i can order a cup of coffee with my watch exactly i can use apple pay yeah and this is better why

SPEAKER_77: you really had to care about the the underlying architecture to to get bought in and versus you know something like ai is like you just show people like the thing and they're like like their mind explodes and they're like i like what gene give me more yeah exactly when can i get it produce this

SPEAKER_26: but my mom um is you know she she keeps asking me like you know can i well she she's asking me to

SPEAKER_151: do the chat gpt queries um so uh but like she keeps asking me for for also the laser printer in

SPEAKER_50: the basement aaron yeah exactly exactly again that's right so there's a pretty good test if if

SPEAKER_151: you know we uh we have um you know people texting people to ask chats gpt to uh to run a request for

SPEAKER_49: them so um that's like when you you know cross the chasm in in technology when is all this going to be

SPEAKER_248: available on box and how are you going to charge for it because i just got a bill from notion

David Friedberg: i had all of my team sign up for chat gpt for i said pay the 20 bucks put it on your personal card put on your corporate card whatever just start playing there's no like multiplayer buy mode or

SPEAKER_57: whatever there is in the sandbox i did that too but not for the actual consumer product um but then

David Friedberg: notion was like hey you're paying like this amount per month but the ai is 20 bucks more per person 10 bucks per moment i was like i gotta make that decision now right chat gpt4 or the notion version of it it's embedded i like both yeah do i just spend 250 on each individual my organization a year and it's 500 i kind of i'm like maybe i'll just buy both yeah um when is this going to be

SPEAKER_47: available how are you going to charge for it yeah i think you actually got to the heart of of the issue

SPEAKER_26: of why you know why you'll have comp you're actually gonna have competition driving prices down as opposed to up um you know uh you know vis-a-vis that that licensing question because um the only reason notion is charging you so much is because you know the amount of tokens that they're outputting you know from the ai model are are you know pretty vast um and also unpredictably broad um you know depending on which user is using it and so they have to charge more for for the product um for us you know our goal is to incorporate uh some degree of the technology into the the core of box so that way as many people as possible can leverage it and then for things that are extremely high volume you know we'd probably have to have some some additional monetization but but we think about this more as a scale play of like how do we just completely you know transform the product overall but dbd on on some of the specifics on that yeah when it'll be when will it be available so it's rolling out right now what i just demoed um in uh we're starting with a number of kind of private beta customers we want to get the user experience right we want to again figure out that kind of pricing and performance side um and then i would say you know the coming months and kind of

SPEAKER_57: quarter or two um it would be all right listen continued success congratulations on uh you know getting back to the office you you got people back in that beautiful office in redwood city

SPEAKER_77: we do we're in like a two to three day a week model um and people enjoying it what's the reaction well well uh you know they're telling me it's good um and i mean i think i can see

SPEAKER_26: happiness um you know from a distance um but uh i i you know there's a lot of benefits to remote we actually still have a large remote um you know contingent box uh but um but i do think having hubs getting people together you know we're in new york we're in austin we're in chicago we're in sf and and redwood city and then internationally and so i think having convening you know a convening place where you can you know spitball ideas you know get mentored you know new and newer employees you know have a have a way of learning the the craft and the trade um i think these are all important things does it need to be five days a week probably not um but uh but i do think you know having people coming together is really important so we're getting the benefits of that yeah i'm going back to an office

SPEAKER_72: i'm actually looking for a space in san mateo now because i'm like i just don't want to be at home anymore i want to hang out with founders more i want to do like i want to do this in person again

David Friedberg: yeah so maybe you know be able to do some in-person interviews have lunch with the person after and

SPEAKER_176: just you know see more people it's just like so dystopian yeah to be only remote it's just i think

SPEAKER_77: i think that's the thing is like is like we got into this battle of like god's remote versus the office and it's it's you know even from our remote people they love that um i'm speaking you know generally but they love that we have offices because when they then come into town oh their colleagues are there and they can see them and so and so it's you know it's it's not like these things have to be these extreme polarizing topics that i think we've turned them into so yeah

SPEAKER_57: the finance people in new york are like everybody get back to the office right you know every day

SPEAKER_01: you have to suffer and then like they're in italy and aspen for four months and i'm like exactly i'm like really okay yeah sure i mean i guess you can take a helicopter to work so it's all good all right everybody uh follow aaron on the twitter l-e-v-i-e sign up for box.com if you're looking

SPEAKER_68: for a great job and a great boss and just a legendary company go to box.com look for their careers page

SPEAKER_276: and uh get a job yeah i i always like to build you up at the end i appreciate that that's yeah that's

SPEAKER_151: great i'm glad you're still hiring right you got you got some job we are we are yeah i mean the the boss credentials that you just gave me i think were a little bit uh overstated but but appreciate

SPEAKER_252: it so i i i've known you for over a decade you've been on this pod for over a decade now you're a fun

SPEAKER_176: guy you're thoughtful you make great products so it's a good place to work folks and and you can learn right you can learn from a legend all right we'll see you all next time you will learn in person

SPEAKER_282: yeah all right exactly all right we'll see everybody next time bye bye