Bret Taylor: Why Pre-Training is for Morons & Companies Will Build Their Own Software | E1209

I think we are in a bubble I am inherently skeptical of companies doing pre-training unless you are a AGI research lab doing pre-training on a Model I believe is just burning capital software is like a lawn it needs to be tended to it's not like you write software once and it just works forever ready to go [Music] Brett I am so excited for this my friend I've been a fan from afar for a long time you've had such an incredible career so thank you so much for joining me yeah thanks for having me I know

this one's a little bit off back because it's not even on the schedule so you're like you're breaking the rules from round one but when I go through the different achievements you have it really is incredible when you were young did you know that you were going to be successful did you have that innate Feeling I don't think so you know when I was young first I wanted be Indiana Jones which I know is not a job but to me he was by far the coolest example of an adult that I'd ever seen by the

time that I uh you know was in school and started thinking about a job I wanted I thought I wanted to be an attorney um in high school and I'm happy to tell the story it's actually kind of an interesting story but I ended up getting a job at a gas station and then uh sort Of hustling my way into making a website for a mechanic that was nearby um I was getting paid $425 at the gas station an hour which was minimum wage at the time and ended up getting paid $400 for the website

so I quit the gas station job the next day and ended up making websites for a lot of local businesses in my my hometown most of those websites endured for decades you know because it turns out if you're a florist it's not like you Actively SEO in your website so you know my my fingerprints on the internet in 1996 and 97 lasted for longer than you'd expect and even when I went to Stanford I um I think if You' met me that summer before I probably would have said I probably want to be a lawyer

but then the combination of My Accidental entrepreneurial um experience plus going to Stanford and the dotc com bubble my first quarter at Stanford I took a class called CS 106a which is sort of the Intro class and the rest is history I I was so obsessed with software at that point I would do it in my spare time um it had nothing to do with school I was just totally obsessed with the the craft do you think people are born entrepreneurs or do you think it can be learned I think most things can be learned

uh I've through certainly through my career I have most of the time when I've thought of something as an innate skill um I've later Recalibrated and felt that with like enough Focus one can um improve at most things I I could never become like an olymp big track star nor could I ever you know win the fields medal so I I obviously I don't mean to trivialize True inability but on skills like public speaking or leadership uh or um even things that aren't quite Fields metal like becoming you know good at Finance I think most

people can with with Focus the thing that is unusual about being an Entrepreneur is um how intense it is and I do think there's a certain personality type that is conducive to that you know I think uh it's hard to be an entrepreneur if you're prone to anxiety because everything's on fire all the time you know that's just the nature of the business um and uh as a as a consequence it probably there's certainly some nature not just nurture there but I have met folks who you know might not have identified as an Entrepreneur earlier

in their career who develop the confidence in their own you know resolve uh through early parts of their career and end up great and it's really interesting too if you look at the enterprise software industry versus uh consumer you know a lot of the greater enterprise software companies were started by entrepreneurs later in their career um which is I think really interesting as well I mean if you look at PeopleSoft and an Neil I guess it was A second you know there's so many great examples and so I I don't think there's a reductive stereotype

of entrepreneur that resonates with me um you know I I really think it's one of the defining characteristics of the United States and Silicon Valley and I have a sense as like we should keep the the the door with the open sign brightly lit for anyone who wants to come you know forward to their path Brett what do most people think is an innate skill that Actually can be learned so like for me people think oh I could never be an interviewer or do content and I just say listen I was [ __ ] I've

just done 3,000 over 10 years I learned to be a little bit better hopefully so I'm now tolerable but it's just like going to the gym what do you think everyone thinks is an innate skill but actually can be learned leadership I actually made so many I mean you've probably heard the phrase oh This person is such a natural leader and I clearly if you're a sociopath you probably won't be a great leader you know but if you have decent amount of EQ uh the innate skills of becoming a leader at different scales of organizations

is absolutely something I believe can be learned it's interesting because if you meet uh people have served in the armed forces uh in the western world most of the military treats leadership as a Craft that you learn um and it's in part because of you're you know uh growing through the ranks of say the Army you know at each step you're managing larger and larger uh groups of of soldiers and you know they theyve formalized a lot of like principles of leadership in contrast I I think the you know if you go into most large

companies and you go into you know a promotion discussion you know corporate promotion discuss like that person is just not a natural leader Not that person needs to you know train or learn these skills and I think we've um well it's not true of all of corporate America um I do think it's one of those things that I think you know companies should invest in more uh which is like formal training of characteristics of leadership uh how to motivate you know uh people who are different than you how to motivate I mean if you've ever

managed a researcher versus a sales lead leader the Conversations you need to have to align and motivate are pretty pretty damn different and and I think it's something that is fundamentally a skill like any skill some people are more naturally um prone to it than others but I think it's something that can't be learned I do have to start though with some semblance of structure you know we've seen some Mega rounds go down in the last few months from some of the biggest people in AI Ilia recently raised a billion Dollar seed round I just

want to start on the foundations first billion dollar seed round by the way of all time go on who was the first no that's what I was asking I think it is the first right must be AB I I wanted to think like if Elon did another company I mean sure might be Aon um I'm I'm here El ready to write the check um my question to you is are we in Peak Ai and is this the ultimate sign of a bubble I think we are in a Bubble but I think um bubbles have different

shapes um and there's a Mark Twain quote that history doesn't repeat itself but it Rhymes and I think the AI bubble will rhyme with the dot bubble and I believe with the benefit of hindsight most of the excess of the dotom bubble might have been Justified um if you look at the top market cap companies in the world they include Amazon they include Google um you know if you Look at across segments it's PayPal eBay if you look at the you know enterprise software companies like Salesforce started in 1998 if I'm remembering correctly all of

these companies were started in the.com bubble and I think people associate mentally and emotionally the dotom bubbles associated with webvan and pets.com but actually if you look at the most frothy statements about the dotom bubble and the transformation of the economy and you Fast forward almost 30 years from that point maybe it was true uh you know when you look at how much Amazon disrupted Commerce how much uh you know uh consumer payments have have trans been transformed by digital technology it took a few waves of of Technology like smartphones and NFC to really you

know fully um realize that vision and you know a huge percentage of you know the gains in the stock market over the past 30 years have more or less been these Digital companies created in the dotom bubble and so I haven't done the math on you know how much money was burned in that period but I think that doesn't mean that the excitement around the impact of the internet on the economy was false so I think the same thing is likely to happen in AI we will look back and laugh at some of the excess

but I confident we will have you know a a a brand defining likely trillion dollar consumer company come out of this 10 Plus enterprise software companies that are enduring you know public companies coming out of this that are native to this new technology so I think it is both a bubble I think there are areas of access just there are like their areas of excess in 1997 and 1998 um but I think it would be dangerous to Miss uh a bubble as as strictly excess uh and in fact there'll probably be outsize returns within it

can I ask is it not different in the way That the risk was priced in and what I mean by that is Salesforce first rounds were not done at billion doll valuations Amazon's was not either you know the companies of 1998 to 2002 were priced not insanely when you have x. AI raising 18 billion I mean these are potential trillion dollar companies where with dilution you get less than 100x I think it's a reasonable point and it's as a venture capitalist makes a ton Of sense you're thinking about it that way I you know I'm

more thinking about it as the impact on the economy so you know I think we we're in a world where there's a lot more Capital than there was there's a lot more um I'd say structure around how people invest in technology companies as you you talked about the private Equity surge the past you know 20 30 years it doesn't uh surprise me that you know given the amount of capital available valuations Are sort of you know markedly different than they they perhaps were um though I think it seemed excessive back then too right I don't

think people could contemplate a trillion dollar company in 1998 rationally anyway um so I I think you know it's what you're saying is reasonable I also think that from my vantage point I'm not investing I am creating and you know my perspective is like where are consumer behaviors going how Will the automation implied by large language models and agents change productivity change the structure of companies change the economy and how do you define a generational company based on those Trends it's up to you to figure out the the nuances of whom to invest in and

why I'm happy to give my perspective but I think um my but it you know for what it's worth you know for companies that are pursuing artificial general intelligence it's hard to figure out Like what's the valuation of a company that creates that it's the numbers might be insane so maybe it's completely rational um and I I'm not the one Mak writing those checks so you know um but I I I also don't look at it dismissively you know I look at it and say there's probably a case to be made um I'm not sure

I would write all those checks but it's also I wouldn't say it's entirely rational either just because I do think this technology current form has a ton Of value but particularly as you project forward towards things resembling super intelligence or general intelligence uh there is so much value in in platforms like that um it's a very unusual investment but it might not be irrational before we discuss I love that also a venture investor thinks multiples an entrepreneur is like generational defining company impact I feel like a school boy who's been told off brat didn't it

that way I feel terrible I Feel really guilty for that but uh anyway uh you mentioned kind of AGI and kind of the value that could come from that absolutely there is kind of a step before that though which is you the models themselves are actually so good and so Advanced that they bundle all verticalized or unbundled software products really and subsume them so to speak to what extent do you think that is a threat that everything will really just be subsumed by very sophisticated Models I don't believe that will happen personally um I going

back to analogies are dangerous but I I think they might be illustrative in this case I actually think the AI Market commercially will play out like the cloud Market did over the past 20 years so if you look at the cloud Market I would say there's really big three big categories of cloud software the first is infrastructure as a service so Amazon web services Azure Google cloud services like that there's Tool makers so you know snowflake data bricks data dog you know basically what is the software that you need confluent what is the software that

you need when your company is moving to the cloud and then there's software of service so Salesforce service now Adobe um and the extremely long tail of solutions there and I would say you we were talking about the companies the public companies in the stock market in that kind of two billion to 20 billion range there's a Huge number of really interesting and really valuable software of Service Solutions why did that play out that way um you know one could argue and and you know certainly I heard isn't isn't Salesforce just a database in the

cloud I'm like come on you know like it's a solution you know it's a solution for sales service and marketing teams and and it has a ton of value and the same you know um reductive backhanded comment could be made of Indie software as a Service application and I think it's borne by companies cios CTO CEOs knowing that actually they don't want to be the one building software they just want a solution that works uh you know software is like a lawn it needs to be tended to it's not like you write software once and

it just works forever and the total cost of ownership of building and maintaining software is so great that I think almost every company that has chosen to build their own in a um area Of their business where there is a software solution service available has regretted it and you've seen this like secular Trend towards you know away from build your own uh towards software as of service I think the same will be true of AI I think there's a bit of a uh Focus right now on both the data centers and the models because it

because the future is so unclear it is by far the clearest way to sort of invest in AI right now is to invest at the lowest layer of the Stack because you know that whatever happens on top that those layers will collect taxes of everyone working on AI above it but I don't really um see why companies would want to take bag of floating Point numbers and morph it into a solution themselves because I believe the same Dynamic that played out in Cloud will play out in AI you know so at Sierra which is my

company we make a solution we're not doing pre-training where you know we're fine-tuning other People's models to to build this solution and helping companies build customer-facing agents primarily for customer service so for companies like Sonos or SiriusXM or Chubbies there are other companies like Harvey who are making legal agents uh there's companies making coding agents that are you know essentially you know building software and I think that if you are a head of a legal department or you're the CTO of a company why would you want to take a Model and try to you know

build all the workflows for your engineering team or take a model and say okay like let's work with our it department and see how our partners can use this instead of a paralal what you want is a push button solution that solves a problem and so I think this idea that somehow the way the world wants to buy software will change because these models are really smart doesn't resonate with me and I think the area actually of AI that I am most Excited about obviously everyone's excited about AGI it's why I I chose to work

with open AI but I'm really excited about applications I think it's early there and I think there's a bunch of companies saying you know uh we're going to actually build a product that solves the problem it doesn't just you know help with productivity it actually Sol solves a problem and we're going to cater that solution to a department or a buyer that isn't Technical and it's Going to be magical there's a ton of value there and I believe that's the way most companies want to buy software there's a couple of things I just have to

unpack that you said about kind of companies wanting to buy Solutions and the ease that they require when implementing these Solutions Solutions I actually said before uh on Twitter that I think AI services companies over the next 3 to 5 years will actually be the biggest winners in Ai and you've seen a Lot of these consulting firms post billions in in profit there was one that actually had more Revenue than open AI do you agree that AI services companies will be a dominant strain of this community and that they will be needed though for the

implementation of this next generation of application l in the early days of Technology adoption you tend to have very low-level platform building blocks available and quite a bit of Professional Services spend Because there is no option other than building it yourself so you tend to get a short-term spike in Professional Services spend along with some low-level building blocks and my guess is at least some of that Revenue you're describing is companies not having an out-of-the-box software of service solution available they see these amazing models like gp4 available and if they want apply them to their

business you know a year and a half ago two years Ago their only option was essentially to pay um one of these firms to to do the last mile themselves over time I do think that that will diminish as Solutions become available that um have shorter and simpler implementations I think that's what companies like mine are doing is essentially you know reducing the The Last Mile to actually configure the software however the reason I think you know this is nuanced and and you may be right and and Actually think it can be a a lot

of value that Professional Services firms provide is around change management so if you manage imagine you have a contact center uh in the Philippines uh managed you know as a as a BP with one of these customers and you're migrating you know a huge percentage of your cases to AI it's not just a technology change right it is actually a huge change in the operations of your company um and then similarly if you imagine you know these Technologies becoming even more advanced whether it's reskilling your Workforce or um actually transforming even the way an entire

department operates because there's a agent that comes to you know comes out that actually means you can completely restructure the way a department is run I think one thing that software companies have always been bad at for good reason I don't think it's necessarily what we do is actually helping companies manage the adoption of This technology uh you know I think that most software companies you know try to be trusted advisers to uh their companies but at the end of the day they're you they have a vested interest and the product that they're selling and

you know it often helps to have a third party there to help you actually manage that change so I do think that my if I had to you know answer more succinctly with all that Nuance is I think there's probably some short-term Professional Services spend that reflects the lack of the maturity of the AI applications market right now uh you know and I think that when there are solutions like Sierra and others for specific domains available you shouldn't have to spend as much to deploy those effectively in your business however I I think that as

AI changes and and disrupts the way companies operate you know I would uh hope that the best Professional Services firms have Consulting arms that can help Companies with that change management and it might compensate it for in a different way so I think if you itemize the receipts the revenue might change over time as AI changes one thing that's really striking to me is the speed of commoditization among the models is this not the fastest technology to commoditize I mean every week brat I see like you know M draw kills it next we Gemini kills

it next we open AI crushed it and I'm sitting here [ __ ] I'm getting Dizzy like which one should I use oh my God CL then Claude comes and it's like five things you can do with Claude that you can't do with anything else and I'm like Christ I've got no idea what's going on are they the fastest technology to commoditize let's start with the high level I really like Reed Hoffman's framing of this Market as Foundation models and Frontier models so Foundation models are any of these large language models that aren't necessarily the

best Of the best or the higher highest parameter count but particularly now where you have relatively low parameter count models that are me or exceed the quality of say GPT 3.5 uh that market of foundation models is quite important um and quite commoditized you know I think that in that market uh probably if you need a model like that you should download llama that's that's the answer it's like you don't need much of a cheat sheet on that you know and or maybe mraw But pick one of the open source models that are adequate and

fine-tune it the Frontier Model Market is a little different when you talk about this um you know the the experience you've had being dizzy using these tools my perspective is that uh we've seen real leaps there so when chat GPT came out that was a meaningful step function change that lasted for a while um and the Insight around instruction tuning and the quality of sort of the GPT Models after gpt3 was pretty remarkably different similarly when GPT 4 came out I I haven't done the math on it but it certainly had a meaningful lead for

quite a while um and now you're seeing a lot of a lot of models sort of catch up to that my sense is we see a lot of incremental Improvement followed by step changes um in quality but going back to the market itself I am inherently skeptical of companies doing pre-training uh unless you are a AGI Research lab um doing pre-training on a Model I believe is just burning Capital um it's roughly the equivalent of an entrepreneur coming to you and saying you know we're building this software solution and the first thing we're going to

do is build our data center from H by hand and you know I think you know for 99% of software companies they should lease their servers from an infrastructure as a service provider not because it's the most vertically Integrated and efficient but because it's not what their company does um and similarly as you're exploring and finding product Market fit the last thing you want to do is have a big upfront investment to build a Data Center and I think that there was a number of companies that were started by incredibly talented AI researchers and you

know step one of their product plan was build pre-train a model and I think for especially with the existence of These high quality models like you know GPT 40 mini that you can f- tune or um the open source models like llama 3.1 uh to spend capital on pre-training now unless you're one of the behemoths um I think is is nonsensical can can I ask can you continue to have step function changes with every model in terms of gpt3 to GP 4 like obviously there's gbt 5 coming next uh don't mind that's not a spoiler

it would just be a natural guess unless they're going for a Radical num I'm not that smart Brad I'm a VC but you know gbt 4 left me with one thing as an option but like do you remember in the early 90s I went from like Windows NT to 95 to 98 to 2000 you know something like I might be mixing it up so you know we could pull that out to start changing I was born in 96 oh so yeah you uh but I I I you know remember reading about it there we go

but but we Can't continuously have step changes can we are we at a stage where you start to see slightly diminishing returns those questions are distinct to me so starting with the step step function maybe maybe not you know I I don't think it's a foregone conclusion that we'll have step function changes I do think that you know I believe the most responsible way to develop AGI is responsible iterative deployment and the reason for that is I believe that as you're thinking about Things like the societal impact access to this technology and the safety uh

side of AGI as well that the best way we can learn about how to you know ensure that these models benefit humanity is to consistently release them learn from those experiences on the safety side learn about the harm learn about really specific vulnerabilities like jailbreaking and improve it at every turn we could end up with a plateau of progress or as you said diminishing Returns the three inputs to you know progress and AI are number one data number two compute number three algorithms and methodology um so if you look at the history Short history of

sort of this current wave of modern AI you know it started I think with the Transformers model which was a um paper from Google called attention is all you need which changed the scale uh uh with which you could um build these models which led to you know many of the sort Of gbt breakthroughs that that came next um you ended up with instruction tuning uh which was how you turned one of these models into a chat interface which was a breakthrough as well so you know given even existing data existing compute we have all

of the best Minds in computer science thinking about different techniques is similar there's folks even looking beyond the Transformers model and things like that so I think that there's that's one area where you could Have a a big breakthrough um you have compute and you know there's you you just pick up a newspaper and read about the investment in gpus and you know these clusters are getting even bigger and bigger um and even with the same amount of data you know training and both pre-training and post-training can have a really big impact on quality and

then on the data side um the there's a lot of writing about sort of running out of some of the textural data but there's A lot of really interesting companies working on simulation there's a lot of interesting um Explorations in synthetic data generation there's multimodality so you know what is true of text is you know there's lots of video audio image content as well so you know in any one of those you could probably make a very rational intellectual case that we're going to hit a wall but then you have the two others and I

don't think you can make the case for all three that they're All coming up on a wall and I think like any big scientific effort it will probably be a mix of of progress and all of those and um as a consequence I am uh quite optimistic you know and the progress of of these models towards something that resembles artificial general intelligence um and I'm excited about it I I have to again take things in turn in terms of kind of the pursuit of AGI and then also building useful applications For consumers a company has

to have a priority I think we both agree on that how does one hold dual priorities of chasing AGI and building a great consumer or Enterprise product at the same time what is the purpose of building AGI it should be to benefit humanity and so what does it mean to benefit Humanity um I think that you know the open AI mission is to ensure that artificial general intelligence benefits all of humanity And that can mean a lot of things uh I think it means a lot different things to different people which is why open ey

has been sort of a a Honeypot for controversy uh you know in a lot of ways because it's very important in this space and that mission uh can be reflected that the lens of your own values to mean a lot of different things um but it one it can mean access so when you think about how do people access this amazing new technology one could Argue that chat chbt has perhaps been um the biggest breakthrough and providing universal access to AI um you know it's uh I'm not sure the idea of you know building this

conversational agent that everyone can just use by visiting a URL that was not a thing people conceived of probably before that it's why at least my understand why it has sort of a goofy name is was a research preview that turned out to be the most important product of the past decade you know and Um and I think that you know one of the things I think about is wow what an important mechanism to deliver the value of AI and AGI to the world um and I think it's very aligned you know with that that

high level Mission um and I think that you know to your point on are there things you would do building consumer products that are different than AGI yes and that's sort of the complexity that all of these uh research Labs or Mission driven companies are Dealing with but to uh imply that sort of building a widely used consumer experience is somehow contrary to delivering value of AGI I don't buy because how else are you going to deliver it and and there there could be different Answers by the way uh but you know you really want

to ensure that you know once these Technologies exist that it's broadly available to everyone in the world uh obviously in a resp responsible in a safe way and so I think It's really great that a lot of these research Labs have found a form factor that resonates with so many people I get you but like Arend perplexity is like no we're not we're not doing that we're building a Google killer that's what we want to replace and then you know open AI has like an Enterprise product with an Enterprise division uh and then like AGI

and safety teams and it's not as it's kind of Cloudy do you see what I mean I think these issues are complex to Be honest with you har I mean I don't think it's uh you know you can describe it you know as a Enterprise team you could also say if you're trying to take the value of these models and ensure that they benefit Humanity do you want every product that benefits Humanity to be built exclusively by open AI you know and so enabling developers to build on top of it is a meaningful part of

Distributing the value to the world so uh and then similarly you know I think The so I don't want to uh minimize the the complexity of all of these decisions but I also think that um you know if you as you think about delivering the the value of these models in a way that maximizes their benefit uh it doesn't seem that far off you know and and it's and I'm and it's also you know what a lot of other research labs are doing for I think similar reasons with similar missions and uh so I think

it's um I'm Excited about the impact it's having you know I I ended up so many of the uh entrepreneurs I know who are working in AI do in large part because of how inspired they were by using these models as consumers using the apis and I think it's having a super positive impact on the world right now do you think knowledge is proprietary to companies given the incestuous nature of just some of the movements we've seen between people and teams certainly some Knowledge is I also think that there's a right now a lot of

these companies are pursuing a mission that's bigger than any one organization and so and then similarly uh you know a lot of these the folks working on AGI are in or come from Academia where the ethos is to publish um which has obviously uh shifted you know a bit over the past few years so it's a very complex question um but I think that right now I think the Breakthrough ideas um you know uh sort Of like I I don't know the story actually but you know the right Brothers invented the plane apparently there was

another group of you know I actually don't know who it was like came close as well and they the ones who hit it I think there's also this Dynamic where these ideas are sort of in the air you know between different researchers as well we mentioned the commoditization of foundation models as a technology we've also seen price dumping and a race to The bottom in terms of price as well in a lot of cases how do you think about AI business models that are sustainable given incredible training and inference costs so when I made the

comment earlier about skeptical of companies doing pre-training it was really based on on the premise that most companies should be applying AI to build Solutions and most companies should have relatively modest training costs and most of their cost should be correlated with inference Which should be correlated with revenue and usage of your product uh and and I think that that's and essentially because if you end up pre-training a very large model you know you end up with s such upfront Capital requirements you have to have a really valuable business model on the other side of

that to justify that investment so first I think companies should really focus on how to find product Market fit you know prior to taking on meaningful training Costs that are fine tuning might be fine uh you know but you certainly sort of pre-training models on the inference side um I actually think uh the costs of AI are going down really really rapidly um I've seen a lot of people tracking sort of the cost of the GPT models over time and what's remarkable about the cost going down is the quality is also going up you know

so it reminds me you joked about when you were born but uh but well around the time you were born Every time I got a new computer in my house it was twice as cheap and twice as good so I think you know on the inference side I think that uh margins will probably improve for a lot of these use cases um there's a lot of interesting technology trends like distillation you know taking a large parameter count model and making a smaller parameter count model from it that has similar levels of quality and essentially what

that means is you're Sort of transferring some of the you while you trained a very large model the you can run inference on something that's much smaller cheaper and faster um and then there's obviously a bunch of improvements on the hardware side as well and uh I'm incredibly optimistic that just the cost of running AI will um could uh probably track something like Moors law like Mo's law I don't think it's a law I just think it's a trend you know that um and I think that's a really Exciting thing for for all companies if

we think about that reducing cost uh over time and mors law proving out we're also just seeing you know Mata we're seeing Amazon we're seeing Google I say they are going to invest ungodly amounts in the next three to five years does that go against Mo's law and reducing cost for them and how do you think about those two seemingly kind of paradoxical things I think the large hyperscalers uh you know are in a Challenging position where there's a big difference between you know owning and operating one of the best Frontier models and not um

so as a consequence I think that you know I probably make very similar decisions to all of those firms because there's so much value and you know for Consumer products for uh infrastructures of service providers um to have the the a differentiated Frontier Model available to their customers um that you know the betting On the future and then similarly betting on breakthroughs and AGI I think is is really rational um but the reason I was talking about the sort of Moors law part of it is I think that sort of like in the infrastructure as

a service Market it really consolid Val ated around a very small handful of of companies and much like AI you know building data centers like scale helps so you know the more data centers you operate the more you can afford the capex to expand your Data center footprint um it's just one of those things which I think you know it should be financed and built by the large hyperscalers because of the capex requirements to do so and I think as the training Market sort of consolidates and people start you know I think it will probably

help because the revenue will sort of consolidate you know around those providers as well um so it is a complex situation I think these companies have An imperative because of the potential impact of AI to spend uh and you know the capex numbers are mindboggling but I I probably would do the same thing can I ask you when you look at Google and Amazon their cash count to fund this is cloud Zach and meta do not have a cloud business being their Cash Cow to fund this what does that enable or mean Zuck can do

differently with the c with the cash cow not being Cloud say that after T Tequilas Uh uh is there anything he can do differently is there any freedoms that he has yeah I thought it was you know one of the things that uh I have changed my mind on over the past year is how quickly open-source Foundation models would be impactful so I had a the when we started Sierra uh in in March of of last year that eventually we'd end up with a few Frontier Model uh Frontier models essentially uh built and financed by

some of the hyperscalers um in Partnership with the research labs and that we would eventually have a meaningful open- Source model or two the equivalent of postgress and MySQL in the database Market that would come out eventually be adopted by one of the larger tech companies that that wasn't one of the hyperscalers just in the same way Google adopted Linux or Facebook adopted my SQL and mcash uh you know and contributed a lot of patches Upstream to to those Projects um and I would say Mark Zuckerberg sort of accelerated that by a meaningful amount not

only the timing of when that happened but the quality you know llama 3. one is a really high quality model um so I think it comes from what you said you know without a cloud business to finance it his incentives are different than you know the the cloud providers uh and I think he wrote no need for me to say it I mean if you just read his post on why he Believes that this is the right strategy I thought it was a really well articulated post I think it's probably good for the AI Market

overall you know I think if you look at um just look at the cloud infrastructure Market you have a lot of proprietary Solutions like you know Dynamo DB to store data and you have a lot of open- source uh things like kubernetes to manage your infrastructure and then you have commercial companies commercializing Those open source projects like confluent with Kafka so I think that you know a healthy AI Market probably needs all of the above you know and you're going to have the frontier models that are the best of the best that are licensed directly

the cloud providers will probably provide both you know both options and you know I think it's you know if you're building these Frontier models you need to Main main a quality lead on on the rest and I think it's Really great for the ecosystem that there's a super high quality open source model available right now is there ever a stop to the cash tap that's been turned on someone said the other day it's kind of like the Manhattan Project for them which is just like you you're in and you can't stop and the sunk cost

is there and you're like oh [ __ ] another 20 billion is there any turning off of that cash tap requirement uh yeah one of the big big questions is you know what Scale of supercomputer and what methodology and what data is required to create something that might resemble AGI or create that breakthrough and economic value that would justify the investment no one really knows that you have a lot of theories you know about it but I think when you look at these companies investing this kind of capex in that future I think it's absolutely

great you know I think it's totally understandable investors would look you know at these The cap back and say give me the spreadsheet that justifies the returns I think um well that's completely rational and I'm sure there's folks doing that I think the the idea that we have this potential to create something that benefits Humanity this much to have this kind of impact on the economy to create something that valuable I'm very grateful that there's some bold CEOs investing in that future I think at every stage you end up with that sort of Increasing resolution

about how it will be monetized um what the great products will be you know in the first wave it was lots of co-pilots now you have as I said agents my sense is there could be a ton of value created here and I think you know you're in this position now where you um you don't want to be sort of Pennywise pound foolish when you're sort of investing in this future it doesn't mean that as I said that's why when I mentioned I'm skeptical of Startups doing pre-training like that's a risk that I find irrational

because you don't have the capital structure to take on that risk it's probably you know uh essentially putting your your your company on a running towards a cliff that you probably won't you know have wings to fly off of by the time you get there if you're a you know one of the larger companies you're referring to you know and you think about how do you grow your Revenue by a meaningful amount over The 10year period is the tell me the better option than this you know and so uh I think there's a lot of

understandable skepticism but I also think it's a very exciting future everyone on the show has said that we will see consolidation in the market we've had the founders of adapt on we've had character AI we've had coh here we've had we've had Reed obviously from inflation do you agree that if you are not one of those core then we are in a Cons consolidation Market I think we'll see consolidation of companies uh pre-training their own models uh you know and I think that the cost structure of um the tools applications companies are different and perhaps

more sustainable so like any Market you'll see consolidation when there's winners but I think it will um happen over a more measured time period I do want to you mentioned agents there I do want to move into kind of agents and the future Of Agents first off with Sierra why did you can literally do anything brght If we're honest why did you decide to do Sierra so let me just describe what s does and then I'll I'll tell you why that's I think it's very exciting so at SI we help primarily consumer Brands build branded

customer facing AI agents so if you buy a new Sonos speaker or you're having a problem with your speaker you'll chat with the Sonos AI powered by Our platform um if you get a new car and it's got SiriusXM you'll chat with Harmony which is their AI agent if you go to retail sites like olai or Chubbies you'll chat with um I think the chubbi agents named Duncan Smothers or something it's a really great person ality agent um that will help you everything from finding your order to order returns and exchanges um so we're essentially

helping companies build their branded AI agent um for all parts Of their customer experience the reason why I think this is a really exciting area for our customers and and for me personally is that I think we're in the era of conversational software so I I remember when uh in 2007 when when Steve Jobs announced this and now I'm guessing 11 then based on our previous conversation so you may not remember it as vividly as I do I remember it well Brett remember this thousand songs in your pocket the iPod it was mindblowing Yeah it

was mindblowing it really was what's interesting though is in the corporate world the dominant smartphone at the time was the Blackberry and if you talk to anyone who had a Blackberry they like there is no way I'm going to ever type on a touch screen like the Blackberry keyboard is and what was beloved people still talk about how efficient they were with it but you fast forward 10 years and 100% of those people had iPhones in their pocket why Was that I think the reason was is the multi-touch interface in the iPhone plus all the

benefits afforded by having a big touchcreen from having a full featured web browser to be able to watch media um we crossed a quality threshold where it was actually effective enough relative to the Blackberry keyboard that everyone said this is just better we're just going to adopt it and now we have more smartphones in the world than people and I think if you measure what Percentage of human computer interactions are coming from smartphones touch screens today versus mice and keyboard it's got to be 95% plus I think with gp4 we crossed uh that quality threshold

of Effectiveness with conversational AI meaning you can now have a conversation with a computer and it actually works it understands Nuance it understands sarcasm uh you can actually you know have a really nuanced conversation and It will actually work and as a consequence you know I think that you know if you fast forward four or five years when you're interacting with any of the consumer Brands you work with your insurance company your phone company um a car rental company you will probably be having a conversation with an AI more than you'll be clicking around on

a website or clicking around on an app and just like mobile apps didn't replace websites they just sort Of uh took a number of use cases away from them if you think about when do you go to your banking your bank's website versus the app on your phone um I don't think conversational agents will replace apps and websites but I do think that every company will need one we like to say like in 1995 the way you existed digitally as a business to have a website in 2025 the way you will exist digitally is to

have An AI agent um so in the context of Sierra in the context of that word agent we're trying to enable companies to build their own the one with their brand on it that does everything that their customers want to do and really in the fullness fullness of that Vision if you think about everything you can do on a company's website it's it's pretty expansive um so the reason I'm really excited about it is I think that it isn't just about automating uh something That exists and helping with customer service so that's a meaningful part

of it uh we really think this is a new category of digital experience and uh companies uh will and do want to be present in this world of conversational AI but it's very hard to do and that's why we're building a solution to facilitate it why is chat the right form factor and is it multimodal is it like I can take a picture of the Domino's Pizza and put it in my agent and it's like Ah That's the mighty mey 17inch you can tell I'm not a vegan uh to all vegans I'm sorry I just

lost a big sede of our audience uh uh and like image basic it's like me on a run being like ah you know I want this how do we think about multimodalities and like why chat isn't has and may be the dominant interface I think chat and voice and multimodality I think the reason why I think conversational AI is a meaningful form Factor is because it's low friction so if you look at the use of WhatsApp around the world this means that you can essentially exist as a business in WhatsApp and be a completely full-featured

customer experience if you think about carplay which of you you know tried to use apps while driving your car and using carplay it's fairly limited right but now imagine that you can have a full productive experience on your commute into work you look at what Was it five or 10 years ago when every Alexa was exploding and everyone was putting smart speakers on their kitchen counters we have them in our house as well all of a sudden you know right now for our family that's getting the weather turning on music right that type of thing

imagine that was a full featured computer and you could uh order an Uber you could you know check your calendar you could you know follow up on an email where you're making your coffee Having these conversational experiences both text voice um well I'm not arguing that it is the perfect form factor for every experience but just like the the same way I don't know what percentage of your email you type on your phone versus your keyboard majority not 90% probably 90 plus percent and you wouldn't say it's because typing on your phone is easier than

typing on your keyboard it's a convenience thing and so my point on going through those different form Factors would being in your car being in your kitchen um you know being in WhatsApp and not having to install an app those things like I think consumer experiences are driven by convenience and and lowering friction and my thesis is just like touch screens have come to dominate our experience with computers uh because of convenience you can have a conversation in so many different places you don't need an instruction manual I think it will be the main way

we work With computers do you think we see the removal of the phone though as the primary interace face you've seen Zach with the Rayband glasses why do you why do you need the phone at all if I can just talk to myself which would look kind of weird but normal because I do often as a venture investor with too much free time clearly uh like you know I could ask myself hey like get an Uber uh I'm here do we see the removal of the fight it certainly seems feasible but It's I temper that

with the if you look at the past 15 years of consumer electronics Innovation how many companies including the ones that make smartphones have tried to make devices that you know replaced or augmented the phone unsuccessfully you know this this device here this phone it's so good at so many things and everyone already has one it's essentially completely removed the market for almost every other type of consumer device um so in the short Term my intuition is that the combination of a smartphone with Rayband glasses or airpods or the like um probably you know meaning you

might need to look at your screen less uh than you do today but my intuition is because of the prevalence of smartphones around the world it will still end up being you know the the primary computer that mediates those conversations but to the point that you made you know as conversational experiences start working More the I always get the big phone you know just because I like the big screen you know I think there A lot changes and you know always go back to the early App Store days and the early apps being such skew

morphic apps like flashlights and then you have the mobile native experiences like WhatsApp door Dash you know Uber um instacart it took one generation for for those things to to Really um exist I have a sense that we will it will take a little while to see Agents native consumer experiences and agent native devices and the hard part about particularly consumer Electronics is you kind of need the consumer experiences to lead a little bit to have the market available so it might take a while but I it certainly seems in the cards now and ways

it wasn't before are WhatsApp not best placed in terms of installing an app store for every Big Brand in the world to implement their own channel and then you have existing Distribution to a billion however many uses it is integrated already into functionality and apps that they use already I think WhatsApp is very well situated um and it's in particular if you look at the usage of WhatsApp in places like Brazil and India um you know it is uh approximating this already but I think you know large language models and agents like the ones we

build at SRA open the door to sort of much more full Featured experiences um but I also think the true same is true as most mobile platforms you know I think that you know when you install an app on this uh it's probably going to be an app and an agent in the future like when we work with our customers you know we want to enable them take their AI agent and whatever form factor becomes a dominant consumer experience you should be be able to install your agent in that in that experience Brett what was

the hardest Thing with Sierra that you did not anticipate being so hard I'll describe a technology problem and then I'll describe the human problem that was harder than I expected around it so generative AI is very creative but inherently non-deterministic uh you know it's very hard to create determinism the same inputs creating the same outputs in particular because if you think about the breth of human language you know not it's just Inherently less precise than than most and then similarly if you afford um AI the ability to reason um you know sort of by definition

you can't enumerate all the possible outcomes from there so when you're building industrial grade agents you know for businesses that have real business rules they need to follow follow um we like to say software is going from the age of rules to the age of goals and guard rails and the hard challenge there is how do you enable Businesses to express their goals and guard rails what's the difference between rules versus goals and guard rails a guard rails not rules when I think of uh rules just imagine um you're a retail website uh you probably

have a menu at the top left and you click it and it has you know the ability to sort of filter down all the items that you sell men women shoes socks pants that type of thing you probably experienced this you've essentially enumerated you Know the rules by which people engage with your site here's the categories here's what you can click you could probably have someone actually click through all possible pages on your site and verify that they look correct if you wanted to now imagine you put an AI agent on your site it's a

free formed text box people can type whatever that they want whatever they want and um if you EXP explicitly enumerate all the things the agent can say it's going to Feel like a robot you know it's going to because and that's essentially what chat Bots from like three or four years ago felt like and actually in fact many of them had almost like the multiple choice options available to you because they were they couldn't figure out how to express that Universe um nor did they have the natural language understanding to to create a meaningful experience

so with an agent you want to enable the AI to have agency and creativity to Actually understand and really comprehend what the customer's problem is but then once you go to say a um let's just say you're a streaming service and you want to use your AI agent to process cancellations so when someone wants to cancel their account probably the thing you should do is ask why you might want to offer a discount and if the person doesn't still wants to cancel you might want to cancel their subscription the goal might be to Process the

cancellation and the goal and you know do you probably want to afford the AI and some creativity on how to present those discounts to really do some Discovery like a good salesperson was on like what value you hope to get from the streaming service you know things like that and then eventually you want to cancel within that there's lots of areas where you want to afford the AI agency and creativity just like a really good um salesperson would you know have That conversation with you um and and an empathetic not pushy way just try to

figure out if there's a way to retain you as a customer and that's nuanced right empathetic not pushy that's where you need to get the a lot of agency you don't want the AI to go off script you know there was a be quite funny if you're like I'd like to cancel well you're a dick yeah or even worse there was an airline that had a chat bot that hallucinated a bereavement policy you Know someone had a um death in the family and the chat like the ticket's on us I won't name the brand on

your podcast but it was like it was a pretty bad thing so you don't want the a to have so much agency that in the extreme case it hallucinates and in the you know the case that you mentioned you don't want the to basically represent your brand poorly as well so essentially when you're making a AI mediated customer experience like a conversational agent You need to really be able to declare both the goals of what the as are supposed to do and the guard rails which could be around language and brand it could be around

tone how pushy you want to be how forceful um and and then similarly like here's the offers that are available things like that so that's the technical that we solve it s I think fairly novel like in a novel way does that mean sorry then you only see kind of agentic implementation for bluntly Lowrisk activities hey I want money back on my dominoes listen if you [ __ ] it up like kind of who cares but if it's like you know my operating system for finances you know whatever that may be or your Salesforce I

really don't want to [ __ ] up pipeline for a billion dollar business you know I think that as AI improves you'll see these agents adop Ed for increasingly more Mission critical systems so you know I think the adoption Curve rationally starts with relatively low risk interactions and then progresses from there you know but our customers already are using it for Revenue generation sales uh subscription turn management for subscription Services things like that so uh you know I think that as companies develop confidence in their agents they can go to sort of increasingly higher risk

um areas but this is actually sort of getting to the the challenge where we Started this conversation is it's a very different design problem than traditional consumer design problems you know if you think about um designing a website or designing a marketing campaign you know you can have quite a bit of control over it you can sort of enumerate all the different permutations that your customers might see um the uh you know a AI agent in addition to your consumers being able to say whatever they choose to the agent the more you Give it agency

the more it will have empathy and feel delightful the less control you'll have over it so the really interesting discussion we have with our customers is you know if you want you know your agent to have a ton of personality and a ton of empathy you probably need to turn the knob up on agency um but with that comes risk you can turn the knob all the way down to zero which by the way our platform supports for the high-risk cases you Know there's some cases where you don't want a ton of creativity or or

non-determinism but in that case agent might sound more robotic you might sort of regress back to the chat bots of a few years ago so we don't come in necessarily with a prescriptive view on what's right for a particular you know customer workflow or a particular brand but it's a really interesting discussion and I think that just like the concept of a user experienc designer was a new Category of job as the web took off um you know and it wasn't just the domain of box software to design user interfaces you know we think that

there's the a role of an agent engineer who builds these agents on their platform we think there's a role of an agent AI architect who's a customer experience leader whose job is to do the conversation design and shape the behavior of these agents and we're essentially building products and tools For these different new types of jobs that we think are just as meaningful as UI designer or web developer and and I think that's really exciting but it's also creating this natural tension at the at at our customers and I mean tension not in like the

personal way but just actual intellectual tension which is how much agency do we want to afford our Ai and you know if you and and making the guard rails more narrow um makes the agent slightly less delightful But making them more broad reduces control and that's such an interesting discussion to have with brands on the flip side how much agency do you give a human who's been trained for a week and sits in your Detroit customer service department and could get high and then abuse a customer like do you know I always think we forget

when we talk about AI hallucinations we're like yeah and humans hallucinate a shitload too this is the interesting thing about Modern large language models and what I think the industry has come to call generative AI is I think it violates most of the rules we have in our head about computers you know computers are designed to be reliable you click this button the same thing happens every time you click it um they're designed to be databases they're not designed to be creative right they're designed to like give you facts uh follow the rules that we

have really really fast and you know Just think about uh software engineering the craft of software engineering you know there's entire methodologies now about how to get increasingly Reliable Software which involves using Source control like GitHub and using immutable binary so that you know you can roll back and have the same behavior you had yesterday if something goes wrong we've essentially spent decades trying to make things deterministic repeatable reli able and now you make this new piece of Software that is slow somewhat expensive extremely creative and fairly non-deterministic it like blows people's minds I think

that as a consequence people are modeling like AI through the lens of how do we make it as deterministic as software was two years ago I'm not sure that's the right model I actually think you know the the thought exercise you did is okay let's assume that you know our salespeople or our call center agents occasionally go Off script how do we deal with that and there probably are operational mechanisms at your company to deal with those situations okay why don't you just use the same mechanisms to deal with the AI as well and actually

thinking of stop putting you know AI software in the bucket of computers and and that rule set and how you deal with it to try to get to you know five nines of of repeatability and say okay this is actually going to be a really creative a Really impactful much lower cost solution it will do some things that are incorrect some of the time how do we deal with that eventuality rather than try to fully prevent it which right now is is almost impossible can I ask a slightly of tangent one but it makes me

think of moderation there when you said about kind of how do we really think about uh determining whether someone went off script or not and what we do with it my biggest concern honestly is Like it or not I look at most of the stuff on my like Twitter timeline and I'm like Is that real or fake and I send it to my family and they're like fake or real and we've it's unbelievable the switch in terms of our questioning the verification of content um and someone said on the show very recently Arvin Naran who's

at Princeton University I now get to interview professors very very intelligent uh uh but uh my mother's like really um but he said you Know the thing is Harry it's not that we will believe stuff that you see that's not true it's that you won't believe anything at all do you agree with him and what are your biggest worries about this next wave I really do believe for most of the problems in AI there are AI solutions to those problems as well um you know I you know for a lot of content you're looking at

you know it would be interesting to put it into things like chat GPT and ask it is this real you Know how should I determine if it's real and you might get some good advice as we think about you know information veracity authenticity um you know my hope is that you end up with the sort of white hat and the black hat you know and the white hat um you know teams and this just like in the world of cyber security will give us all the Iron Man suits we need um to you know be

successful and Trust um or distrust uh the information that we see so I think just like with All these things that's why I mentioned that that Outlook worm you know I think as these Technologies get developed you know you end up with you know collectively our learning about the ramifications these Technologies which is why I believe in responsible iterative deployment of AI because I think it's very hard to in an ivory Tower predict all of the first and second order effects but then it is an imperative for as an industry that we Develop Technologies and

mediations and to you know for um uh these different downsides of the technology but I feel confident we can I think you know all the great AI minds are are trying to think about how this benefits humanity and you know for every problem there's a great entrepreneur technologist or researcher who I think will come up with ways of of um meeting that challenge can I ask a weird one before we move into a quick fire Brett Taylor when you go out To fundraise must be a little bit different now brat like how does that work

do you know what I mean it's like so just help me understand you just you going to do Sierra and you're like ah like what yeah I mean I guess it's kind of a question of like why fun right but then there's also a question of like how did you approach that now you could raise from anyone well first why did I fund raise um I really believe in the Importance of boards and having stakeholders and the accountability of you know having a board and investors and employees and I want the employees coming to S

to know that clay and I aren't doing this as a side hustle you know we want to build the generational company and then similarly I really value the advice I've been a board member as well as an exec and I really value the Strategic advice I got so when we started the company I Just called Peter Fenton who I've worked with twice before he's the only person I talked to and you know that that was our first board member and with our subsequent round similarly way how long was that conversation uh yeah I don't want

to disclose private details but Peter and I worked together a lot before it probably could have been even shorter than it was but I'm not there to I'm I want to talk to Peter about what we're doing and why And get his advice so it was the right conversation because I wasn't there in a transactional capacity and I think that the best relationship between you know investors and entrepreneurs um is one where you really like they're your first phone call on a strategic issue and and thankfully I've known Peter for you know almost 20 years

so it was pretty clear to me like the first person I was going to call I have a man crush on Peter's brain so it's totally Fine I remember when I had him on the show first I was like wow he is the most articulate orator I think I've ever had on this show um listen I want to do a quick firearm brat so I say a short statement you give me your immediate thoughts does that sound okay yeah so what have you changed your mind on most in the last 12 months how quickly the

cost of AI will go down largely thanks to the emergence of distillation and open source models like llama what is The biggest misconception of the next 10 years of AI the focus on hardware and models and not enough focus on the applications of AI uh I think many of the defining companies in AI will be delivering consumer and Business Solutions that happen to be powered by AI not just the models themselves who's the best board member you sat on a board with and why them I'll skip Peter since we just spoke about him Uh I

don't stack rank these board members but a board member that I've worked with twice is Fiji Simo so she's the COO of instacart I work with her at Shopify and she's also in the board of open Ai and one of those folks who's an operator who knows also to Be an Effective board member and a remarkable intellect which VC is the single best picker do you think and why then it can't be Peter I don't know I don't follow it Enough to know this episode is brought to you by Peter fanton I actually honestly don't

follow that much not because I don't care but I I I follow the companies more than the the investors I don't I just don't know can I ask your advice you sat on some of the best boards I sit on boards now I am a young board member I want to be the best board member that I can be is there any advice that you give me having seen many different types of boards and types Of entrepreneurs you know I think the the art form as a board member is how to be involved enough without

jumping into the operations of a company and knowing how to give advice in a way that the CEO and the management team actually hears um so you know I think the finding that balance of creating the Cadence with the companies you work with to get the information you need so that you know where you can to add value when you know until like you know uh call the Proverbial bat foam because something's wrong um is the biggest art form so I would say you know board members who treat every engagement the same are probably not

doing it right because different executive teams different cosos have will hear device advice in different ways and the businesses are very different so I think really treating it very uniquely and finding an operating Cadence you can get the information you need to actually provide Good advice what yes that you got was the most important or significant yes probably the most impactful unexpected point in my career um was Mark Zuckerberg making me a chief technology officer of Facebook I'm not sure I was qualified to do that job um but he saw something in me and and

I obviously saw of myself as well I would say that moment kind of changed my own conception of myself uh from being sort of an engineer to you know being able to Lead larger teams and it was largely because of Mark's faith in me what's your favorite story from Facebook when the movie The Social Network came out we rented a movie theater and all watched it together and it was you know it's a fine movie but there was this funny scene where they order Apple teis which was like a kind of a lame drink let's

be honest like no one you know orders an Appletini and you know maintains their their reputation on the other side of it So we go out to a bar in pout afterwards and I walk up to get a beer and the bartender like what the [ __ ] is it with you guys and apple teis people have been ordering it all night so after the movie like everyone just orders apple teis and the guy at the Old Pro was like I ran out of what of that toxic looking green Lor is and he was like

what is it with appletinis today so that's a do you know how I first I first heard about Venture when I was 13 because I was sitting in a Cinemar in London and I saw the scene with Peter teal and clarim where he invests in the young zck and I was like oh my God I I want to be a venture investor the ironic part of that movie is whatever the director was trying to achieve I've met a lot of entrepreneurs who um view it as a source of inspiration which I'm not sure was the

director's goal with I know I I think the exact same and also like I think everyone took like Entrepreneurship away from it and I was like VC but I I literally don't think anyone has the the view of leaders that you've had working alongside Zach Benny off bought a shop with Toby uh Board of open AI with Sam this is the greatest leaders of a generation what do they have that is non-obvious that makes them great leaders one of the things that I've admired the most about the leaders you mentioned whether it's Larry and Sergey

Mark benof Mark Zuckerberg uh Marissa whom I work for at at Google um is this sort of Relentless Drive every time you might uh get comfortable with a situation they're always looking out towards the horizon I always found Mark Zuckerberg particularly remarkable at this uh every time I thought I was thinking long term whatever Mark was thinking was about 2x farther in the future than I was thinking and you know it was so uh disconcerting and Motivating for me when I was there I think when I became Chief technology officer of Facebook after they had

acquired my social network I was 29 if I'm remembering correctly I think it was uh 2009 um and see how his brain worked definitely changed my perspective on what bold leadership meant and taking bets that could have been unpopular or complex in the short term to achieve a long-term goal and I think you really see with some of the great entrepreneurs This ability to think extremely long term and make decisions uh that you know especially if you're nowadays if if you're a public company it's such a challenging uh you know Cadence to to uh parade

yourself out in front of investors every three months and you know while investors claim to be longterm very few have the patience that they extol on their website you know and it really requires um this uh Relentless focus on the future and the other thing That I would say that all all of them have in very different styles is the ability to communicate Vision to employees and stakeholders employees probably being the most meaningful when you're running a company and motivating the team to work forward but you really have to tell people what the future will

look like why it will be important and why it's an important thing to pursue and why people need to sort of overcome these short-term Challenges you both have to have the vision and you have to bring uh you know bring the team along with you and all of them have it in very different styles but in ways that are incredibly inspiring dude rock and roll you're a star thank you so much thank you really apprciate it