SPEAKER_00: so i go to a pcp they say alex you need to go talk to a nephrologist and then what happens SPEAKER_03: right at that moment and how does it break so so the it's like a you kind of have to think about it as like a funnel right if um if you clicked on an instagram ad for the incredible you know shirt that you have on there right that funnel is super super tight all your data is going to neatly get passed on over to the store that's trying to sell you that shirt and you know you're going to enter some information and man if you don't buy that shirt right then and there they are going to hound you and they're going to find you on every inch of the internet until you buy because what they really care about is capturing you as a lead right so most people think about SPEAKER_05: patients as patients and not enough actually as a lead that really needs to go be serviced and worked SPEAKER_06: to go and actually get their attention this week in startups is brought to you by squarespace turn SPEAKER_07: your idea into a beautiful 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 northwest registered agent starting your business should be simple with northwest registered agent you can form your entire business identity in just 10 clicks and 10 minutes from llc's to trademarks domains to custom websites they've got you covered get more privacy more options and more done visit northwestregisteredagent.com twist today and aws activate aws activate helps startups bring their ideas to life as you build and scale your business activate credits grow with you to support your changing needs apply to aws activate today and receive up to one hundred thousand dollars in credits visit aws.amazon.com startups credits hey everybody and welcome back to this week in startups my name is SPEAKER_00: alex and we have a special episode for you today we are once again going to go talk to some of the SPEAKER_09: founders who are building the companies of the future if you're not familiar with our twist 500 project we are going out into the world to find the 500 startups that have the potential to have the largest financial impact which is a good corollary for how much disruption they're going to bring to the world of business and technology we're having a lot of fun we have about 400 names on the list so far and are racing to close but also right now we are going through and talking to people as often as we can so today we are going to talk to the founders from tenor and extropic and beehive so we have applied ai next generation chips and then a software company that we've talked to before and we know and love here at twist so first up we're going to talk to tenor what are they and why do we care well it's important to keep in mind that medical care is one of the largest markets in the world today period the us spends around 18 of gdp on healthcare just to pick an example now inside those trillions of dollars that we spend on medical care each year are billions of dollars worth of technology spend and a lot of that goes to software in fact software for the medical practice management and administrative automation spaces alone are worth about five or six billion dollars this year and even better healthcare spend is rising faster than gdp so that means startups like tenor are chasing large expanding markets that are often pretty much recession proof it's really not hard to see why tenor recently raised over a hundred million dollars in one round venture investors are simply betting that the medical world will spend on software to help control costs and also to ensure better patient care given how much spin is up for grams it's not a hard wager to understand let's talk to the company SPEAKER_00: here's tenor all right here on twist we talk a lot about technology companies of all shapes and sizes from drones to robots to ai models to people that are trying to reinvent business software yet again one space we don't spend enough time really looking at is our health caring for ourselves it's an enormous part of the local economy tens of percentage points of gdp and it's pretty inefficient and it's pretty slow and it's often not that great for patients some companies are finding real success though attacking certain areas of the current healthcare market bringing a little bit of that technology magic dust to helping us all get care faster easier and with less disruption one of those companies is a firm called tenor that i've been tracking for a little bit now and after they raised an enormous series c just last month i thought hey let's get them on the show let's talk to them and figure out what they're doing so i'm going to bring on a guy named trey holterman here in just a second and oddly enough of all the ceos i've spoken to the last 12 18 24 months he's the only one who has SPEAKER_12: a strong ai background who wants to focus more on who he's helping than how he's using ai inside SPEAKER_13: of his business trey welcome to the show hey alex great great to be here great to you didn't use the word luddite i was expecting it but i appreciate it uh i appreciate the intro nonetheless SPEAKER_14: uh before we started i gave trey a joking intro and called him a luddite just because of the ai SPEAKER_13: thing i thought that was going to be the real intro but either way no no i uh i try to not SPEAKER_00: flame guests until we're at minute two or three into the into the chat and then you know loosen them SPEAKER_17: up and then go for it well i'm fully clenched so uh i'll stay that way for a couple more minutes then SPEAKER_09: i knew this was going to be a fun chat the moment you got on uh your energy is fantastic all right SPEAKER_00: uh trey seriously though tenor looking at the medical referral market and its problems if people listening this haven't had a medical issue that required a specialist they may not know what that means so can you tell me why you built the company and the problem inside of healthcare today that you SPEAKER_13: guys are attacking so super simply basically if you want to go to a variety of specialists um you SPEAKER_03: really just can't and why is the reason that you can't you can't because uh you are not the one paying right there is an insurance company or the government is actually paying for your service so what do they do they say look you've got to go to a gatekeeper a front line uh a primary care physician um urgent care hospital and these people are allowed to refer out into these specialists and it turns out right when they refer out to these specialists one of the big problems in the us healthcare system is you refer a patient out to us health uh out to a specialist to do uh you know a drug a device um or of course a more specialized consult and the patient never gets contacted never actually gets there or shows up and doesn't have the paperwork necessary to uh you know get the work done effectively um and that's a big problem it's a huge problem in fact over 50 of patients do not get captured along that process so they just go um you know on with their lives and oftentimes disease get done go untreated um patients get unseen that's the problem in a nutshell i want to know what counts SPEAKER_00: as a specialist because to me the doctor is the doctor and um sometimes they have different job titles but i kind of go into a room there's a white coat they chat to me whatever so what is the difference SPEAKER_13: between a specialist and a pcp for example so typically right um uh when you're going to medical school right you're focusing you're specializing in one of many areas and the the you know some of SPEAKER_03: the most incredible doctors are uh the front line and oftentimes they are generalists uh in doing family medicine they're treating a whole host of things and you go to them as really that first line of defense saying what's going on but listen they're not the ones that are going to give you you know knee surgery um or diagnose a complex issue with your stomach or heart um you know they're not the ones that are going to go and do your imaging um for you they're going to refer out and so those specialists are they're all doctors are all providers the way we would refer to them um but we SPEAKER_05: really only focus on the providers uh and the businesses really that are getting sent patients SPEAKER_00: all right so i go to a pcp they say alex you need to go talk to a nephrologist and then what happens right at that moment and how does it break so so the it's like a you kind of SPEAKER_03: have to think about it as like a funnel right if if um if you clicked on an instagram ad for the incredible you know shirt that you have on there right that funnel is super super tight all your data is going to neatly get passed on over to the store that's trying to sell you that shirt and you know you're gonna enter some information and man if you don't buy that shirt right then and there they are going to hound you and they're going to find you on every inch of the internet until you buy because what they really care about is capturing you as a lead right so most people think about SPEAKER_05: patients as patients and not enough actually as a lead that really needs to go be serviced and worked SPEAKER_03: to go and actually get their attention and the problem is when that provider sends you alex as a patient they don't just send um you know a nice clean data blob of data oftentimes they're sending all your chart history bunch of documentation labs studies um their notes their determination of what they think is going on and so you end up sitting on a backlog and that backlog is heinous and what we help people do is get through that backlog while engaging the patient every step of the way so they know what they're going to pay if they're going to you'll be denied for medical necessity reasons and really what the roadblocks are to actually getting in and it turns out basic human psychology if you're able to contact you alex within five minutes saying look this is what it's going to cost you we're missing this one piece of documentation if you can go back or go get imaging done for this one thing you're going to be able to get seen and serviced it's just tremendous like the impact that it has SPEAKER_17: on actually converting patients into real visits so we talk a lot about in like the e-commerce world SPEAKER_00: about reducing friction in the checkout flow like every time you can remove a step your overall conversion rate improves by x percentage points it sounds like the current referral system is just like a 50 fail funnel to getting people from you need this to them actually getting it so using tenor system as it exists today uh how much better is the successful rate from referral to care well SPEAKER_03: you're going to hate this answer but the the reality is it totally varies by specialty right 50 50 50 for gastro where somebody's going to stick something you know where the sun don't shine is actually an incredible conversion rate right so you're trying to get more towards is that because SPEAKER_29: people don't want to actually go get those appointments yeah there's certain right there's SPEAKER_03: certain care pieces of care that people do not want to go and get um there's other care right where you're going to get that care it's just a matter of whether or not you go to the first place that you were actually sent and so in that place you as a patient you're going to get service one way or another it's just a matter of if you have to go and hound down the door yourself um and so you as a patient may convert personally at like an 80 rate but the provider that received you you know for us we're dealing with a lot of folks in the 50 to 70 range trying to get into the you know 70 to 90 numbers i mean it's really astounding actually the sort of impact and that you can do on a per SPEAKER_31: provider basis your website is the face of your company people judge a book by its cover it's how you make a powerful first impression we all know that and let's be honest you might be a little embarrassed by your current website well don't worry squarespace is going to help you build a new beautiful professional attention grabbing website in just a few simple steps let's say you've got products to sell or a gallery of your work that you want to showcase maybe you got some services you want to promote you're a consultant you're a developer well squarespace is going to give you all the tools you need to grow and prosper we're talking stunning world-class design plus templates to fit every possible business or purpose start an online course schedule appointments even generate invoices for clients with just a few clicks their mobile blog editor makes it extremely simple for you to create and update posts on your favorite 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linkage between primary doctors and specialists yeah so it's it's in the tens of SPEAKER_03: millions uh from an individual's basis in the united states but what's interesting about that is that um you know unfortunately a lot of the folks it's not like it'll happen to one person one time for a lot of these people they're seeing different specialists every month and and even for a single sort of patient journey um you know where this gets really quite a bummer to be honest is oftentimes you'll have sort of six six links in the chain to the point that you're actually getting treated and at every single point you're dealing with this insane friction and the same sort of uh you know paperwork obstacle it going from really point a to the time that a patient's actually getting treated it can feel like you're trying to get like a you know an expensive rare packaged good through like multiple adversarial countries through different domestic ports um and honestly from timing delays sometimes i i actually think that you're ryan peterson over at flexport uh you know would do a better job at getting some of these patients into like uh you know i don't know congo or something so um it's uh it it can be months uh for a whole patient journey but we see oftentimes patients that are not getting contacted by a single provider on the order of five days to SPEAKER_00: two to three weeks so we we joke about delays and timelines and you know working with uh our friends over at flexport to speed things up but on a non-joking side of this this is bad for health right these delays are not just administrative issues they're not just you know paperwork headaches you could die if you don't get the care you need at times yeah i mean what really ends up happening right SPEAKER_03: as you go to the hospital you have uh you know something that's really wrong they say hey you got to go to the specialist they send you the specialist specialist doesn't contact you so you think hey this must not actually be that serious or maybe the specialist contacts you you're freaked out about how much it costs right number one reason people don't convert is time number two reason people don't confirm is price and really just not having financial transparency to what it's going to cost and then where do they end up they end up back in the hospital so it's one of these problems that's it's bad for the patients it's bad for the system it's bad for the payers it's also bad for the providers getting sent these patients so it's just like a problem you know it's a clean SPEAKER_01: definitional problem that should not exist all right now let's tilt this towards what you're SPEAKER_00: building because tenor didn't just raise a nine figure series c on the back of wanting to help people strictly only out of the goodness of your hearts there's a business here and so what you guys have done as far as i understand it is train a in-house ai model which i believe you were working on before the chat gpt explosion so you're kind of an ai og if you will and you took essentially the documents from doctors and referrals and kind of created your own data set to then teach a model to not only find out the right information but also to just decipher the famously convoluted um doctor scrawl that we've all had to deal with at least once yeah so this SPEAKER_03: where i think a lot of people kind of end up um slightly misunderstanding kind of the reason it's like tricky it's not about really reading the document um as much as actually interpreting it against these complex sort of payer guidelines right everybody knows that you know these astounding rates of denials from commercial payers um they actually publish these guidelines so they say look we are not going to cover that visit for you alex unless this this and this is true about your history right if you got a back surgery 11 months ago we're not going to give you another back surgery we're not going to pay for it at least and so somebody has to go in to the clinical history of alex and determine hey have you had a back surgery in the last 11 months and so we have to go through insane amounts of uh of uh documentation on you now when people see documentation yes there's an insane amount of this documentation that literally travels via facts and we do a bunch of fun marketing around the fact that like you know the primary means that most patients are getting sent over is the facts but the reality is actually there's a massive volume of patients that we process that are actually just like they're in emrs they exist there as notes you know sometimes even ambient listener notes but it's complex documentation that um you know if you if if you don't have the payer guidelines if you don't have a model that can really interpret them against those guidelines and you don't feel really really com confident in what you're determining you cannot SPEAKER_00: triage patients okay so just just to help people that are listening along emr is electronic medical record uh systems like epic essentially the it's the cms of the healthcare world more or less it kind of keeps track of each person and what's happened um if you need an analogy okay so that helps a lot where do you get all the information that you need from the insurance companies to know for a particular uh let's say back surgery you need to have these four things is that all accessible and then therefore ingestible by you guys or do you have to go out there and kind of like beat down the door and say please give me the secret recipe to approvals i mean this is where like you know part of SPEAKER_03: the reason i'm always happy to talk about this problem is like it is such a schlet problem um these guidelines the mainstream ones get posted to websites every six months that um and they change and so we have a massive massive massive operational overhead of converting these different guidelines into language model uh interpretable formats for ourselves and then guess what codes get reprinted all the time with different guidelines that update before they even publish online so you have to be calling so we are basically this like massive supply chain of inter bringing these guidelines in and then converting them into a a workflow software that can take a patient match it to the guidelines and basically convert if they're good or not we also of course though like stand on the backs of giants we've got a great partnership um with a couple of folks in that specific specifically focus on the policy game but we also have to do quite a bit of work ourselves to keep them up to date so they're changing constantly and you know there's thousands of different plans in this country so it's SPEAKER_17: uh it's a bundle of fun it's a bundle of fun to do this uh yeah it does sound like a particularly SPEAKER_00: thorny and naughty problem just given like my insurance plan and my spouse's is different than the one we had a year or two ago which had different guidelines for different things different pay points honestly i don't even know who my insurance provider is right now you got to get SPEAKER_01: that checked out i mean uh well no i'm on her insurance and it's good that's all perfect yeah yeah SPEAKER_00: as long as you can take care of okay so when i said that you guys train an ai model to ingest the data from individual records i was missing the backstory on all the work you have to do to interpret that information but when this works the way you guys want it to um the patient who goes to get the back surgery referral to keep with that example um when the doctor sends out the referral how does tenors step in and then what from the patient's side is the lived process yes so um that's actually part of SPEAKER_03: the sort of big product that we released called the network product but um i was working my way towards that yeah sorry i'll get to the patient experience side then in a little bit but we we really primarily our customer is the receiving provider and that receiving provider today people obviously they love to talk about us as an automations platform because we do automate a lot of work but it's really um it's it's work that's so laborious on the receiving side where you're taking in a patient reading through their chart and trying to interpret all this information trying to figure out where to triage them try to figure out if oh man they're already in our system we got to update them we're going to create a new one we got to contact them what do you do so we are a a sas platform that lives right before their emr so like you give a good example it's like their cms or their crm right um for or their billing platform what have you so we exist by interpreting all the patient flow SPEAKER_17: right before them and then we get them in to that system at the end of the day and that's where they SPEAKER_00: live to go and um be billed and stuff like that so your customer is the specialist provider who wants to have an easier onboarding and ingestion of incoming patients that previously would have SPEAKER_05: arrived with a binder full of faxes yeah and i'll be slightly a little bit of a pain uh the specialist SPEAKER_03: wants you know one of three things they want to convert more patients they want to reduce denials and they want to have better fte efficiency um you know a lot of people get super excited like oh this like crazy technology we get to automate a bunch of work like well what's the point of automating work because sometimes you see some of the most insane behaviors where people are like oh we automated this thing and our conversion rate went down eight percent you should have thrown more humans if you were going to lower your conversion rate this is ridiculous it turns out though of course they're like automation is a key piece of con of increasing conversions um and so you want to automate certain things but it's it's always a fraction of the story founders if you've got a SPEAKER_61: product maybe you've got some customers or even just a little bit of traction guess what you've got Chamath Palihapitiya: yourself a startup and it's time to make things legit you want to be official tighten it up investors don't want to wire money to a gmail account with a p.o box no they want to know you're a serious person and that your company is incorporated in 10 clicks in 10 minutes you can follow your llc get an actual domain name launch your official website claim your business email and even start fast tracking your trademark application that's right you need northwest registered agent the service that's going to do all of that for you with nwra's privacy by default option they're going to use their address for all your public documents not yours so you're not going to get a ton of spam or junk mail and you can also get a legit address and working phone number with their virtual office setup so get more than just an llc get your entire business identity go to northwestregisteredagent.com twist and show the SPEAKER_65: world you're in business all right so now let's let's get to the new product which is the tenor SPEAKER_00: network which as far as i can tell because this is the first time you and i are talking so i didn't have the uh the advantage of running this by you before but it appears like it's a visibility network on top of the mechanics of tenor so you guys do all this work and then you've essentially made like a like a lens into it that both providers and patients can use yeah no i'm kind of laughing at SPEAKER_03: hearing you describe it not because you're doing a bad job you're doing a great job but actually because it's like the uh you know so much of sort of our mantra is to keep things dead simple uh i'm not maybe i'm not so much a a tech luddite is maybe like a tech marketing luddite and uh you know yet i yet i hear myself using um enough jargon i could uh you know tie a rope with but anyways um the simple way to think about it is you're a sender of a patient and tenor can be doing all the great work in the world but you still have no clue what the hell happened to that patient they exist in a black box as a patient you could have no clue where you are in that process so we built this incredible patient experience and this incredible referral source experience so that everybody knows what's going on so you as a patient have this like really sort of lovely experience um where you know what it's going to cost you know what the gaps are you know what services you're eligible for and things like that and so it is cool because it's like uh the first sort of foray for us into the actual SPEAKER_70: direct patient experience and how has reaction been what do people think so it was rolled out across SPEAKER_03: uh you know a number of beta customers and it's been the number it's been the biggest this is why we talk about like there was no there's no automation in that right like that's just it's just software right it's just an experience um but it's been you know one of the best things we've seen for conversion lifts right it turns out if you give patients like a an experience that is digital and friendly and logical as all hell even if their records are moving back and forth on the fax who cares they're getting this incredible experience they're going to show up to the doctor at much SPEAKER_02: much greater clips trey do you eat pizza uh i do yeah yeah do you ever seen like domino those pizza tracker that's like the 95 of the inspiration just give people a domino's pizza SPEAKER_03: tracker we don't need to reinvent the wheel here you know the the the problem i guess for us was really just um to create the domino's pizza tracker experience everybody it's like you know ronnie coleman everybody wants to be a bodybuilder nobody wants to live anybody heavy ass weights like like everybody wants a pizza tractor everybody wants a pizza tracker but nobody wants to build you know the integration into the 100 plus effects systems you know the 50 different email inboxes that are going to come in and that was really like why it was easy for us relatively speaking SPEAKER_00: to get to a point that we could offer visibility to both sides yeah no you're i do not want your job because it's a lot of work everyone that i've talked to who deals with anything in the insurance space deals with a a huge plague of complexity as far as i can tell so i'm glad you're doing it so what's next what can tenor do next after you fix referrals what's the next thing you can go do with a similar uh mindset and bent if you will to make this system work a little bit better and suck a SPEAKER_03: little bit less yeah i just you know i like i'm so allergic to kind of like the the oversell or the overhyping or anything like this but if you look at like where very medically specialized models are going and where this stuff is going to get super super interesting is when a doctor refers you for one service you often actually have like a a ton of sort of other issues potentially going on now what prevents you from actually going and getting treated for those those services is that it's a pain you don't know what much it's going to cost and what's cool about this patient experience is in the very sort of alpha stages we're seeing that like if i'm getting sent over for something like a cgm there are on average two or three other services that i am as a patient am eligible for um and actually can go and be receiving my the insurance company is happy to pay for it because they know it's a good return on investment and yet i'm not taking advantage of as a patient so the big thing for us is actually creating like net new experiences for patients um uh well it sounded uh sort of airbnb-esque but not not quite as sexy you know more like net new service is for um you know patients that are getting sent over for thing a they they are qualified and eligible for thing b and c and making it dead simple SPEAKER_17: for them to go and get referred for thing b and c when relevant i just really dispute your uh your SPEAKER_00: framing of constant glucose monitors as not sexy because if you need one i bet you there's nothing more beautiful in the world than that exact piece of modern technology which we didn't have not that long ago so i i like all that and i appreciate you not overselling it but i do think that if you've done all the work to learn this element of the internals of how healthcare actually works you've already done so much of the intellectual lift to figure it out i hope in time no pressure that it can expand all right before i let you go i'm curious about building in your market one thing that i've heard from founders in venture capitalists over the years is don't sell in the government don't sell into highly regulated industries because sales cycles are longer there's just more stuff to take care of it's tough in other words your company uh you guys had tripled between series b and series c which is incredibly quick and i'm really happy to hear that so do you think more founders should should dive into your side of the market or do you have words of warning um you know when we were when SPEAKER_03: it was like 2022 and nothing worked and everything was you know completely hellish um you know we had a bunch of vcs trying to convince us to go into crypto and it's nothing against crypto but i basically at that phrase i don't know where i learned it but buffett uh talked about how like uh you know in the 1960s everybody was talking about the efficient market theory and so all of his competition thought it was worthless to try investing because the markets were already efficient um and i guess the the learning for myself there was if everybody is uh saying that you shouldn't be doing something it's like okay like that's actually that actually gets me quite excited um and conversely if everybody's saying you should do something um you know that's that's kind of lame and maybe that's the reason we never said ai as a company we don't say agents even though like vcs will say to our face that we are the only like agentic ai thing that's actually working um and we just don't do that because it's like i would just uh i'd rather just talk about the problem rather focus on the problem did we solve the problem better today or tomorrow and actually like you know if there were some crazy SPEAKER_17: technology that came out tomorrow that helped us solve the problem better we would we would do that to solve we would use it to solve the problem in in two seconds well what i like about your company SPEAKER_79: is that when people think about ai in the healthcare space they mostly think about you know medical SPEAKER_00: imaging and finding more tumors and that sort of thing as opposed to you know automating document flow but if that's the real issue that needs that's broken i mean i'm glad we're using everything we can to smooth things out you give me a modicum of hope trey because if you guys can make this better there must be other things that we can improve and probably quickly you know i mean you guys are moving fast the company was only founded four years ago and you're already as big as you are now i think fortune said you're in the eight figures of revenue so clearly you can build a relatively sizable company and attack a big problem here quickly so i hope other founders listen to this and ignore the part where you said hellish and only talked about the good bits and are encouraged SPEAKER_02: to to follow up well yeah the only the i guess the last soapbox you know being on the soapbox a little SPEAKER_03: bit the last soapbox for me is like the cool thing is if the scorecard is a problem that's that you're trying to solve and you can solve it for one after customer after another you almost get to a point where you talk to a customer like just let me solve the damn problem for you because i know you have it i see that you have it and i'm not trying to sell you software i don't care about selling you software i want to solve the problem for you um if you don't have the problem i'll run away faster faster from you um you know then you can chase me that makes life easy because you're just not selling anything you wouldn't buy and uh you either get really good at solving a problem or you don't don't exist um and that's made my life a lot less stressful because i don't SPEAKER_17: have to uh you know i don't have to think about everything i could possibly sell somebody you know SPEAKER_26: i i'm really excited about it i want you to come back on the show uh in a couple months when you've SPEAKER_00: had a little bit more time to spend the money to let me know how fast growth is going and i want to learn more about what you guys are going to do in terms of how to use the money but you just raised it so i'll let you alone trey uh where can people find the company on the internet and also what is SPEAKER_17: a job that you're having a hard time hiring for oh great question so first of all that'd be that'd SPEAKER_13: be awesome uh hopefully i have something to say um uh the uh linked oh god i can't believe linkedin is probably the best place uh you know listen we are always one of the reasons we're in new york SPEAKER_03: is uh you know we think there's a there's a great more number of great software eng talent that wants to be out in new york that doesn't have great opportunities to be out in new york that is always universally in a world where the sort of the efficient market theory of today is everybody thinking you don't need engineers i hope desperately for any competition to believe that you don't need engineers because engineers are still um you know that's our stable of of incredible talent here and uh you know we keep obsessing over it so it'll always be hard so if SPEAKER_12: you're an engineer and you want to work in the chelsea neighborhood of manhattan uh trey holdman look him up go talk to him in the meantime we appreciate it and we'll talk to you in a couple months SPEAKER_31: talk to you guys soon thank you so much for having me we're all familiar with aws amazon web services that's the cloud platform that powers so many of your favorite brands but do you know about aws activate that's their program for startups where they provide up to a hundred thousand dollars in aws credits for all startups whether you're backed by an investor or you're bootstrapping money is time to keep innovating time to delight customers and time for you to keep gaining traction you need runway and aws's activate is going to help you with that runway we hear this story from so many of our founding university companies they're finding product market fit the words getting out about their product just a little boost finding some savings here or there to get a little extra time can be the difference between getting traction and bringing in revenue or hey let's call it what it is running out of money okay and shutting down aws knows this that's why they've created the ultimate toolkit for early stage startups looking to boost growth with aws activate you're going to get up to a hundred thousand dollars in aws credits hands-on support and training plus exclusive discounts with some of our favorite companies and tools so start getting the support you need at every stage of your startup journey to learn more visit aws.amazon.com startups credits that's right aws.amazon.com startups credits the most valuable company in the world today is not a software SPEAKER_07: company uh instead nvidia's four trillion dollar market cap puts a hardware company at the absolute top of the corporate world why well because building and selling chips to power compute is simply an enormous business for perspective nvidia generated revenue of about 44 billion dollars in its most recent quarter and that was growth of 69 percent on a year-over-year basis naturally startups are circling service systems and grok are building chips to handle inference at scale while companies like rebellions are reducing power demand for ai compute the list goes on but there's a startup called extropic that is not simply trying to build a faster or more efficient gpu using known principles instead the startup has an entirely new approach to crunching ai numbers that could consume far less power and potentially topple the most viable corporation in the world that's why we're excited about extropic and put it onto our twist 500 list the startup is gunning for the richest vein in the modern economy with hundreds of billions of dollars worth of potential yearly revenue up for grabs so please join me in welcoming gill verdant the founder and ceo of extropic gill how you doing man doing David Friedberg: good doing good thanks for having me happy to be here my absolute pleasure uh and if folks don't SPEAKER_07: know you're also uh based buff jesus over on twitter people might know your twitter account and not have made that connection great to have you on the show i want to start with what the problem is a lot of folks out there have seen ai models improve we keep hearing stories about bigger and bigger data centers it seems that to some degree the current model of gpus and llms works so gill what are we running up SPEAKER_88: against and why does extropic want to fix that yeah i mean um you know it's been it's been a highly SPEAKER_90: successful sort of um scaling of ai in the past years but i i feel like we uh i think every hyperscaler is feeling the pain of uh trying to keep up with the demand uh i think the the thesis is that you know as you have more compute you have more intelligence and if you have more intelligence it has more value in the market you get more revenue and so the pull of the market is nearly infinite for more intelligence and that sort of transduces to the pull for more compute and and we've clearly seen that uh and a few years ago we would warn you know i used to warn that uh intelligence will scale and we're going to run out of power and everybody would laugh uh three years ago uh why are you working on a paradigm of computing that's far more energy efficient and now no one's laughing because they have to build five uh they have orders to build uh several data centers with five nuclear reactors per data center and they're they're pulling their hair out and so essentially um you know what we've seen is that uh you know over the past few years there was uh scaling the training worked really well you got to gpt one two three you know one two three four four point five and then they went back to 4.1 that's SPEAKER_91: kind of the the the top end of of that sort of scaling and now what we're what we're seeing is um SPEAKER_90: test time compute they call it or reasoning right the the models reason for a very long time um and and you use the same model instead of a bigger model with more parameters you use the same model kind of recurrently you you make it think for a while and then and then you you optimize that sort of the thinking trace with uh with reinforcement learning uh often on for example at the moment it's mostly on math problems because we can check uh whether it it it was right or wrong and really that's kind of the the future scaling law is at least our thesis and i think the thesis of opening i and of uh of google is that uh uh scaling reasoning scaling test time compute more generally is the way to go to have uh smarter models uh without having to keep scaling uh the training uh compute by you know 10x to get sort of diminishing returns in terms of the the the performance then again the the test time compute scaling law tells you that the more uh compute uh both the test time and and when you're training the this reasoning system uh you get more performance you get i think it's about SPEAKER_91: like quadratically more performance it's like it's like i think you you if you put in 10x more compute SPEAKER_90: you get uh about at reasoning you get about 100x the equivalent of 100x more compute at training and SPEAKER_07: the old sort of old school method if uh inputs go quadratically uh when we compare training versus test time compute and just doing more inference work what you're saying is your method will SPEAKER_89: be more efficient inherently because you're focusing on the more efficient area of ai improvement today SPEAKER_91: yeah so what we're seeing is that uh if you make your ai algorithm more probabilistic so instead of having just a single forward pass that's deterministic and you may it starts looking like a monte carlo algorithm you're kind of probabilistically thinking probabilistically searching over responses uh then then you get more performance and that was the thesis of the company from the get-go is that the algorithms will become more probabilistic but then and and you know we're uh catering to that because we are building probabilistic computers but also if you look on the hardware side from from the bottom up uh as you try to make your transistor smaller you try to use less current less power the transistors become probabilistic as well so then we saw an opportunity well hey most workloads are going to be probabilistic the hardware naturally wants to be probabilistic why don't we just cut the gordian knot here and run probabilistic algorithms on probabilistic computers right and that sounds like heresy you know we've been doing things a certain way for many decades you know a lot of people rooting us on a lot of people are skeptical totally natural it's very disruptive it's a very fundamental change in how we do computing from the ground up but what we've demonstrated really SPEAKER_90: uh is that we can build these new probabilistic primitives in silicon using uh mass scale manufacturable techniques so using one of the large fabs and uh that these are these are very real they're here they're in the lab uh we submitted a bunch of papers to peer review and now we're going to put uh this this SPEAKER_91: chip and this product this is our our test board with our our first uh extropic silicon chip we're SPEAKER_90: going to put it in customers hands similarly customers for people to try out what we call thermodynamic SPEAKER_52: computing i don't think everyone is familiar with deterministic versus probabilistic computing so SPEAKER_89: if you could just break that down for the the layman i think that'll help people understand the rest of SPEAKER_91: our conversation absolutely absolutely so so computers they're in a deterministic state you know you have a bunch of transistors there's zeros and ones and they're they're definitely not uh in a state that you don't know because if if you don't know the state of your computer it crashes in in current architectures essentially you get a blue screen it's over and then you know i came from a different world originally from from quantum computing where there we're using quantum physics which is like super positions and you have any noise there it crashes same thing right so it seemed to me like okay well to scale quantum or scale deterministic computers the bane of our existence is noise so randomness just from the jitter of matter of electrons of radiation whatever it is sources of SPEAKER_90: noise come in seep into your system and add entropy they add uncertainty as to the state of the the computer and that's usually a problem but if you if you use the uncertainty and you shape it that's actually the algorithm we're trying to run in machine learning you're just trying to shape uncertainty uh into a blob that is the same shape as the data set blob and and that is machine learning and so uh that's what we've been doing using essentially the natural jitter of electrons that occurs at very uh low current because if you have very few electrons then whether a handful of them are are oscillating does matter to the population average right so you could think of it as a SPEAKER_91: a mosh bit of electrons and we're kind of steering it right and and and that's that's kind of the art that's the that's the very real challenge there and uh you know we're creating software and compilers to compile well-known textbook algorithms onto onto the physics of this device onto the physics of this SPEAKER_97: mosh pit of electrons okay so determinants compute everyone knows is what we use today quantum computing everyone knows that we're working on it yeah all the majors are you worked on this at alphabet i know SPEAKER_07: microsoft amazon everyone's working on quantum super low temperatures and an entirely different set of problems but in between those is where you guys seem to exist and so i think it might be time to bring up um energy-based models and how those tie to the underlying uh structure of of neural nets and other ai techniques that matter so talk to us about that and then i want to get from there into uh SPEAKER_91: production yeah for sure so energy-based models are both very old and cutting edge at the same time there's kind of uh some founding fathers of of of deep learning and ai they're big fans of them uh yan lecure uh has an active working group and uh working on energy-based models at meta uh but originally their you know back propagation uh algorithm we use to train neural networks came from jeffrey hinton who was working on how to train networks of these energy-based models and if you look at averages of energy-based models averages of their input inputs and outputs because naturally they're they're more of a distribution their probability distribution over outputs but if you just look at the average then that's how we actually got neural networks and then if we looked at how to train you know deep networks of of these energy-based models using the averages that that's how back SPEAKER_90: propagation came about so in a way we're going back to the ancestors of deep neural networks and running them natively in hardware right and and and that that that's that's pretty awesome from a theory standpoint but uh at the same time uh you know the energy-based models have been known to be far more parameter efficient again because you you kind of have to uh use more test time compute to use them uh traditionally sometimes people didn't want to throw more compute at test time to actually use them um but um if you do then you theoretically uh have the most parameter efficient model and hence data efficient because the more parameters that you have the more you got to chisel away uh using gradient descent so you need more hits of the chisel which is data points every time right so unlocking the ability to run energy-based models scalably and tractably uh is is is what we're working on and and that's going to unlock these models that are more data efficient more parameter efficient they use far more compute but if compute is 10 000x cheaper for us in terms of why do we care SPEAKER_91: why not exactly 100 000x you know exactly exactly right and so so we've been not only working on the hardware but we've also been working on on the algorithms in order to to you know uh uh get people to use more energy-based models right so how to uh modify diffusion models uh to use more SPEAKER_90: energy-based models is some research we've been doing for example yeah so i want to get to software SPEAKER_97: in a second but i want to go back to um the underlying work that you're doing here to make chips more efficient because you guys talk a little bit about brains and how they are incredibly efficient but also deal with noise in an efficient way so does the brain provide a bit of a uh map SPEAKER_89: for the company or is it more of an analogy for how you guys are approaching dealing with noise inside SPEAKER_91: a signal inside a computer i mean these energy-based models were kind of a physicist model of how the brain works that's why they were then called neural nets right but again it's like a loose inspiration SPEAKER_90: um but uh you know we're not obsessed with sort of biomimicry this is not a normorphic processor SPEAKER_91: um but for us you know unlike quantum computing there is a proof of existence of a large-scale thermodynamic computer out there that is very performant for ai and runs on 20 watts and we're using it to converse right now it's our brains exactly right so so that's very encouraging uh and again the brain to us instead of how you know we we build it with uh electrons sloshing around in a mosh pit the brain is really a mosh bit of of neurotransmitters right which are bigger chemicals SPEAKER_90: they're heavier and slower so to some extent you could imagine someday we we might exceed the brain in terms of energy efficiency because we're using kind of particles that are lighter and they're they're uh less energy they're less costly energetically to slosh around but uh you know i i don't think we're at brain energy efficiency yet or in the near future the manufacturing process is gonna have to improve but we want to end up in the 10x 10x oh you know away from the brain so if you were to scale um if you were to scale this this chip this tiny tiny chip right here to a whole wafer it would run on 20 watts and have uh about 1.5 billion p bits and um 17 or 20 billion parameters per layer and then you SPEAKER_91: could do multi-layered programs so you get a 100 billion parameter model and because these models are 10 to 100 x more parameter efficient that's effectively should be the intelligence of a trillion parameter model and that's what we're getting for right and so if you have a trillion parameter model for 20 watts that seems pretty valuable that's insane you can run that on on the edge i mean you could run that on on a smartwatch so obviously we have to scale our system right we're aiming to scale a thousand x year over year which is you know really crazy we started with three now we have SPEAKER_106: you know nearly nearly a thousand degrees of freedom in the in the devices we're going to hand customers and then and then next year it's going to be on the order of a million right and then we we SPEAKER_07: keep scaling so people are definitely familiar with qubits in the quantum case um explain for people what a p-bit is and how it might relate um intellectually to a qubit yeah i mean you you have SPEAKER_90: a classical bit it's it's definitely zero or definitely one and then you have a quantum bit it's actually SPEAKER_91: people used to say zero and one zero or one it's not it's not and or or it's it's a complex valued superposition right so they have a phase they have a complex number and and the value of that phase matters because the you know uh zero plus one and zero minus one are completely different states a p-bit for example you can have it be 20 percent of the time sitting in the state one and it's dancing between zero and one and eighty percent uh time in the other state and then you could flip that you could go from twenty percent zero eighty percent one to eighty percent zero twenty percent one and that's sort of a fractional bit flip so we can do fractional operations and that's how we save power right SPEAKER_90: because there's fundamental limits for any operation you do of in terms of your edit distance how much are you editing how much compute you're actually doing uh but because we maintain the computer in this uncertain state we can technically do fractional bit operations so this is really useful for for low SPEAKER_91: precision uh neural networks right and and sort of any sort of probabilistic algorithms it's not SPEAKER_90: necessarily the best for uh you know super high precision scientific computing no no god no but it's SPEAKER_101: great for ai which is inherently probabilistic versus deterministic exactly and we're seeing that uh you SPEAKER_90: know low low bit quantization uh works pretty well right in practice and that's what uh that's what the SPEAKER_91: labs do to scale their product right otherwise they couldn't afford the inference and so um yeah that's that's what that's what we're targeting you know from the ground up so it's it's a herculean effort to i mean reimagine understand the physics of the transistor and silicon reimagine the whole architecture from ground up for ai which is which is needed because we're investing i mean we're at the point of investing trillions of dollars into building out nuclear reactors and gpu-based data centers i think SPEAKER_90: we can afford to have uh some startups with tens of millions of dollars taking a different bet in order to SPEAKER_07: save the planet right i mean yeah so that's actually a great segue into what i want to get to next which is just growth of the company as a commercial entity so you guys put out this uh this slide here which shows essentially your first superconducting prototype back in 24 this year the test chip that you've been holding up and showing us thank you for bringing that and then next year first production chip so much more capacity on that thing um as far as i can tell from public uh information you guys have only raised 15 16 million dollars this all looks to me incredibly expensive i'm used to as you said you know gpu spends being in the budgets of billions tens of billions and so forth so yeah how much more capital will extropic need to get um out into the world at commercial scale and is that capital hard to access vcs have been known historically to be a little bit skeptical of SPEAKER_88: hardware companies yeah yeah no i i totally understand that i think uh vcs have been burned by uh you know SPEAKER_91: hardware plays because if you're if you're not ambitious enough you're in the nvidia kill zone right if you're trying to make a better gpu and competing with nvidia you're in for a world of pain but if you create something that's entirely alien to them they're going to dismiss it at first and you're going to keep scaling it and then and then when you're at scale it's going to be it's going to be too late so you have far less market risk uh there uh yeah in our case i mean you know we've raised actually 38 million dollars uh so far we go we haven't uh we haven't burned it all obviously we're we're in a very good position we've burned only about 20 20 million so far but we have a very uh very very high talent density team a lot of physicists a lot of ply mathematicians electrical engineers and we've been building the whole stack from from the algorithms compilers to to to to the hardware itself and we've done several tape outs uh we have done all these experiments in superconductors we took our learnings brought that to semiconductors and now we're we're taping out our our much bigger chip and it it's we're aiming to make it available next year uh but but this chip turning it into a product a dev kit is what we're working on right now and in the coming weeks we're going to be able to SPEAKER_118: ship it to the very first uh enterprise customers so we're pretty stoked about that yeah summer 2025 is SPEAKER_07: the time this stuff actually reaches the customer yeah and that's what something i'm very curious about because you can take nvidia gpus and put them into many different data centers because they kind of have some compatibility i have no idea what bringing extropics trips into an existing data center might look like maybe the right question gills can you do that or will people have to build SPEAKER_91: oh okay so talk about yeah yeah so so people people you know saw our first experiment so so the thing with thermodynamic computers is as you make them smaller they can run hotter and we started with you know the the chip was small but the the p bits were macroscopic you could almost see them with the naked eye they were pretty they're pretty large but to to have that operate in a thermodynamic regime we had to super cool it so it was in a big fridge we put out this movie and everybody was like ah that's never going to scale it's like we're just learning here this is our experimental platform SPEAKER_113: and this is the 2024 um superconducting prototype you were working at quantum temperatures uh quantum SPEAKER_88: and then a bit above we're we're going we're going hotter right so uh essentially we cracked how to do SPEAKER_91: it at room temperature so originally we thought we were going to have to cryo cool it with some uh you know liquid cooling or some some crazy like uh pro gamer overclocking set up i see you've seen my gaming rig all right yeah yeah but uh but we figured out how to do it room temperature uh in silicon right using the right process and uh and so now i mean it's just like this you know you could have a card you could slap it in uh into your server and that's what we're gonna that's we're gonna sell SPEAKER_90: in the early days uh but over time you could imagine you want to have it as integrated as possible with regular forms of computing and so uh i think i think people you know what people should plan is you know with uh for their build outs that they're there there will be heterogeneous compute you're gonna have some gpus or you're gonna have some some groc some cerebra some etched or SPEAKER_91: whatever and you're gonna integrate some thermodynamic computers and then they're gonna work together right so just like a diffusion model is like a big neural net and then it proposes a jump a probabilistic jump for how to denoise the image you're gonna collaborate between a thermodynamic computer for that proposal and a big neural net running on a traditional processor but that that sort of um collaborative algorithm you get about a hundred x less compute on the classical side needed and of course that's most of the energy consumption the thermodynamic computer consumes very very little but if you were to figure out how to run a whole algorithm on the thermodynamic computer again it's gonna look like a different architecture so far what we've been able to do cfar you know kind of benchmarks that are kind of 2012 again we're going back to the drawing board in terms of the architectures so so we have to redo you know 10 years of deep learning from scratch hopefully the community helps us with that as we release it but you know with cfar we were able to get 10 to the 8 times greater energy efficiency 10 to the 8 that's uh pretty significant that's 10 million times uh greater energy efficiency than diffusion models running on gpus right and so or hope there's something between 100x and 10 million x right where uh you know some architectures that run really well either mostly on a thermodynamic computer and partially on a classical one or or fully on a thermodynamic computer sit somewhere in SPEAKER_90: the middle and anywhere in that middle is awesome because that means you know we have a hundred to thousand to ten thousand acts less nuclear reactors to build to get the same intelligence and performance and to us frankly i think i i don't think robotics and embodied ai will be tractable unless you have a paradigm like this that is at scale right because right now you have a whole cloud being the SPEAKER_91: brains of these robots and even with the the biggest clusters you know running these video models these video world models they're extremely expensive they're not even close to being at the edge and ideally we want them at the edge and so so you need that many orders of magnitude for us to unlock SPEAKER_07: robotics and you know america are you saying that eventually robotics will not be essentially tethered to remote data centers to handle compute but it'll be literally on device thanks to lower David Friedberg: cost lower uh power demand ai chips i mean that's the goal right like to have a fully autonomous robot SPEAKER_88: that's not necessarily tied to the fleet um but i would imagine the manufacturers were always gonna SPEAKER_91: have have some connections for all sorts of other reasons but you know in practice you could have a brain that runs on the on the robot's battery and doesn't take all the power uh and and is very highly performant and can help uh do motor control and reasoning in a 3d environment and and that's the goal it's also very important for ar and vr right in ar and vr they're kind of you know apple vision i have SPEAKER_90: an apple vision it's pretty heavy right like apple have their own silicon they have some of the best team in the world but it's it's it's too heavy so it needs to miniaturize it needs to have way more compute uh with less power right and so that's the sort of uh stuff we can unlock with much denser intelligence SPEAKER_52: uh in thermodynamic silicon so really briefly before before we go is your target customer the hyperscalers is it the foundation ai model companies is it companies that just want to run their own SPEAKER_07: inference in-house i'm just trying to figure out who you're going to sell to to start yeah i mean SPEAKER_88: you could look at who buys gpus right you have companies that put them in devices at the edge you SPEAKER_91: have companies that put them in their clouds you have uh developers that slap them in their computer at home and and i mean that's that's that's what we're we're going for right we're going to sell cards and and dev kits so the dev kits you're going to be able to have on your desk and and you can have one or two chips and then the cards are going to have more chips than that and then you could build servers and so uh it's it's it's a bit of everyone but uh frankly everyone needs to migrate because there's a sort of ecosystem uh effect when everyone's using the same software tools and and the same researchers can go from a robotics lab to to uh an ml lab in the cloud you know for for for for um open ai or whatever uh and and the same researchers their skills carry over because they are using the same chips and the same tools so ideally we kind of spread to to all these SPEAKER_07: verticals but uh you know are you referring to kind of like a nvidia cuda system but for extropic SPEAKER_91: processors yeah yeah absolutely so so we have our our own compiler uh and everything like that um and and for some background you know co-founder and i trevor cto uh we built uh originally we built tensorflow for quantum computers right how to how to integrate quantum computers into deep learning compute graphs and how to compile to them and so that's what we worked on at google as basically kids like uh eight years ago and uh and so we have experience basically creating compiler from scratch for a new type of weird alien computer that we don't know how to program right that that was kind of our our you know we've done that and now now we're doing it for an entirely new form of computing that you know there was basically no community that was pre-existent um you know i think um really there was some darpa research on like hey you know neuromorphic is kind of dead we should think more like thermodynamic uh yeah one of our advisors todd hilton uh worked 20 years at darpa on neuromorphics and and he's kind of the godfather who coined the term thermodynamic computing so we met up and i was like hey i'm leaving google x i'm gonna do this uh i'm gonna build the paradigm and and he was just over the moon and and and we've done it now and and we have the components so of course uh you know as we scale it it's going to have more impact in the world but right now it's going to be the early adopters the early believers and also kind of the the companies that can't afford to be disrupted by this next year SPEAKER_90: you could think of a hedge fund a defense company uh or or even this big ai labs now they're they're in such a tight race it's almost like hedge fund they're looking they're looking for alpha they're trading researchers for 100 million dollars a pop it's getting crazy out there so any sort of edge they can get they'll be interested right so i think if your guys's technology risk goes all the way to SPEAKER_07: zero your market cap's going to scale to essentially infinity and that's why i i was really excited to SPEAKER_97: have you on because i really do think that we're going to have to really go in a different direction SPEAKER_23: to get to what we need to go uh gill an absolute pleasure i could keep you here for two hours and you have to let it go here uh when you do get the dev kits out let us know um and oh what is going to SPEAKER_91: that's what i heard something like that well we'll see all right well thank you so much for having me Chamath Palihapitiya: on i really appreciate it cheers okay everybody your pitch is the face of your company right what does everybody say when you ask them for money or they're going to join your company they say send me your deck and some founders no offense you're walking around with a little schmutz you got the schmutz on your face right it's messy and people judge a book by its cover so you need a clean easy to follow a beautiful pitch deck and not just to let investors know about your company it's also to show them you're capable of making a beautiful deck right it's just kind of table stakes let's call it what it is that's why we've joined forces with our friends at gamma g-a-m-m-a for a twist pitch deck competition why am i doing this i want to see better decks so go to gamma.app g-a-m-m-a.app these decks come out so beautiful because you use their ai power platform to create stunning stunning two to three minute pitch presentations and you can import your existing deck from whatever incompetent ugly disgusting platform you built your deck on and you can get started from scratch with just simple text prompts right ai first it makes sense and gamma is working with 20 of the top ai models that means you're going to be able to use one of their hundred pre-made themes and templates to help you elevate your ideas and your script and your designs so here's what i want you to do i want you to submit your finished pitch deck at gamma twist.com gamma twist.com go to gamma twist.com we set up that special domain and you submit it there 10 finals will pitch me right here on this week in startups and i'm going to give the winning company 25 000 in cash or i'll even make it an investment if you want my name on your cap table you choose if you take the 25 000 a surprise it may have a certain tax treatment if you take it as an investment it may have a different one so talk to your accountants make your deck today at gamma.app and then go to gammatwist.com to submit it and hey get the schmutz SPEAKER_07: off your face all right clean it up a little bit all right so last week on twist we dug into substack's massive 100 million dollar series c it was a big event for the newsletter and online creator space the investment pushed the value of substack up north of a billion dollars and was i believe the largest round in its space since beehive raised 33 million dollars last year our question after chewing on substack's latest fundraise was pretty simple what's the 10x case for both substack and beehive over the next 10 years venture investors backing the two companies really do expect material upside but can that be achieved when media economics are in tatters now we've had the founders of both companies on the show before but with new capital flowing in and new revenue milestones being announced talk about that in just a second it's time to look to the future so please welcome back to the show it's beehives David Friedberg: co-founder and ceo tyler dank tyler how you doing man it's great to be back alex thanks for having me SPEAKER_52: it's been it's been almost three whole months so it's about time we got back together and since uh we last spoke you dropped some news that in early july i believe beehive scaled to 20 million in arr but SPEAKER_07: that's not the full revenue story tell me about uh where behind us today yeah so 20 million arr as of SPEAKER_140: a few weeks ago and then we also have an ad network and a tertiary monetary of revenue stream called boost which is like a co-registration network and the combination of the ad network and boost accounts for another 10 million in revenue so altogether about 30 million revenue run rate as of SPEAKER_14: today but just to be clear this gorgeous chart that you shared i believe it was in your newsletter big SPEAKER_07: desk energy this chart is not inclusive of boosts and the ad network this is just the software SPEAKER_140: revenue here yeah if you if you multiply that by 12 that would get you the 20 million arr and yes that SPEAKER_07: that's just the sas revenue i wanted to put this chart up because it's uh it's very very yeah i was gonna work of art beautiful impressive um it's pretty much rock solid and i want to talk a little bit about how this chart came to be because one thing i have seen is that beehive has incredibly quick product velocity you guys are always launching new stuff so can you just for folks out there SPEAKER_89: who are building um try to connect for me product velocity and shipping things and uh mrr growth or SPEAKER_140: arr growth yeah so the product velocity i think is kind of like it sounds cheesy to say built into our dna but we entered a very competitive industry back in 2021 where there was mailchimp who just been acquired for 12 billion there's tons of email 1.0 platforms substack has been around for four or five years there's other platforms in the space and we entered with an mvp prototype type product where we knew that it was very rudimentary relative to the competition and so the only way we can possibly catch up or the philosophy we took is let's just ship as many valuable features as quickly as possible and what that does is one catches up to the market that we entered very late relatively speaking but it also creates this narrative that we can ship quality product quickly that addresses our users needs and so that gives users or potential users the perception that yes they don't have what i have what i want today but because they ship so quickly maybe they will solve my use case next month or in a few months SPEAKER_151: um and that buys you a lot of patience with these early adopters of the platform and we really just SPEAKER_07: haven't taken our foot off the gas since so i was thinking about beehive and substack and people like to talk about uber and lyft and kind of other traditional well-known technology rivalries but i think the best analogy or perhaps analog for what beehive is building is ramp because when ramp came out they were targeting a similar ish market to what brex was doing they had a particular angle on it they were focused on saving you money versus kind of corporate cards for startups and since then they managed to go from what was immediately or initially dismissed as an also ran into being one of the most valuable companies in in silicon valley so i guess the beehive story saga if you will is that you can start with something basic and then iterate incredibly quickly and catch up to any incumbent or SPEAKER_89: just one that was only a couple years in the market like substack i mean substack is a formidable SPEAKER_140: competitor for sure i think the market's massive right and like we like i just said mailchimp got acquired for 12 billion there's dozens and dozens of other email platforms as of two weeks ago we just launched a website builder as well so you could argue that we are going deeper into the creator or just builder space competing with a wordpress web flow framer as well and so i guess we're going to make the pitch of where we can 10x from here i think there's a lot of opportunity both in email but also in the website space which is growing very competitive but i think the wedge of being vertically integrated with a website builder that has a full cms and newsletter and the growth and monetization of your audience is a really compelling offer that other website builders don't offer also i'd say your analogy of brecks versus ramp is interesting i think the way that i typically look at it is i think us versus substack is pretty analogous to amazon versus shopify where amazon has millions of third-party sellers but to access their products you have to go through the amazon website or the amazon app the product shows up in an amazon box and amazon owns the customer relationship very similar to how substack owns the distribution and reader relationship with its users whereas shopify is more similar to beehive in the sense of it's the infrastructure and tools that kind of sit behind the scenes to empower the success of our users and we don't take a cut of revenue unlike substack so i think the SPEAKER_143: the shopify and amazon analogy is is pretty interesting so just pulling up the numbers here shopify SPEAKER_52: currently valued at about 161 billion uh amazon at 2.41 trillion stretching out the time horizons here SPEAKER_07: do you think that in time shopify's model will generate a larger company than amazon just based on market value i'm trying to understand why you're taking this side of the bet when amazon has done so well with SPEAKER_159: its centralized model and frankly owning the customer relationship as you said yeah but you could also SPEAKER_140: probably make your and granted i'm not an analyst like a financial analyst viewing both you're not but that's why i had you on tyler but but you could also argue that amazon benefits from aws and they own twitch not that that's a massive revenue stream but they have a diversified product suite outside of the pure e-commerce play where shopify has really owned like if you want to build your own brand and your own product they are the storefront they're the infrastructure they will facilitate payments um so i think that is kind of what we are trying to do we don't want to be we don't say sign up for my beehive right it doesn't sound great and like that's not the purpose of what we're building we want you to create your blog your website your newsletter your storefront whatever that looks like we want to sit in the background and empower our users i think substack has very intentionally created the alternative or taking the alternative approach of sign up for my substack download the substack app if you want content created by our users on our platform you get that SPEAKER_143: by substack.com and find different content that suits you um so i think it's like a philosophical difference in how we're approaching the business so as i was thinking about the future SPEAKER_07: of beehive actually one of the questions i wrote down was central application question mark and it sounds like you're saying that that's not something that beehive would want to build because you're not trying to aggregate demand but notably in the case of shopify they have put out an app uh just sticking to your analogy there that does centralize um shopping demand uh for shoppers sorry for sellers on the shopify network so i does the analogy to shopify fall apart when it comes to centralized mobile applications in the case of beehive or am i just taking that analogy too far um i mean it's a great SPEAKER_140: point right i think what we've seen time and time again is when platforms get in between their users and their audiences it usually doesn't end up so great for the users and so in 2018 when facebook revamped their or overhauled their news feed much to the detriment of publishers and brands on the platform in 2022 twitter deprioritized external links in the news feed which hurt traffic to publishers and then just recently as of a few weeks ago you've seen publishers claiming 40 to 50 decrease in traffic due to google's ai summaries and so i think that there's something around aggregators and trusting a large platform that has historically always come to the detriment of users and publishers and i think one of the the winning narratives for substack is distribution and algorithms that can boost quality content and just know when that distribution works in your favor at times it also can work against you just like facebook used to give tons of free traffic as they googled all of these publishers and users until it didn't um and so i think actually it's like a cheap dopamine hit to get that type of traction early but i think the more sustainable businesses have their own foundation and can stand alone on their own and that's what we're trying to empower our users to do yeah i mean in one sense SPEAKER_07: i think that the the dopamine hit the short-term sugar rush is is the right analogy because it never feels bad back in the days of google being a great traffic source to have google send you five million people but if it's going to send you zero the next day it's just simply not sustainable as a model so that brings us all the way back to kind of the core behind product which is email newsletters um you and i both write one on a regular basis so we're in the trenches here i also write the um twister 100 newsletter which is on beehive and i'm curious about how much that market can grow because i think you and substack have done a good job of getting all the folks like myself and yourself who want to write for a regular audience on our own terms ish uh onto these platforms but what i'm not clear about tyler is just how many more folks out there in the market who might want to sign up for beehive launch a SPEAKER_52: newsletter either use the ad network or sell subscriptions and just kind of join the party if you will are we halfway there are we a third of the way through the market how much is luck yeah it's SPEAKER_167: interesting because when i raised our seed around three and a half years ago that was the number one point of feedback that investors would give me they're like how big is the market because everyone SPEAKER_140: kind of looks at oh newsletters are at the time morning brew the hustle axios the skim and they're like how many more how can you build a business like how many more of those exist and i think the narrative you just gave is like yes there are writers there are people who want to build their who write content and build their audience but how many of those like journalists and and like written word first creators exist and i think the one the answer is a lot more than people give it credit which i think we've proven over the past three and a half years two i think you're seeing that content creators that are youtube native instagram tick tock or just businesses are seeing the value in communicating with their audience directly via email whether that is a customer comms email that you send weekly whether that is an investor update i think we've all come around to like email is not going anywhere it's actually it has a ton of staying power um and so i think that there's more opportunities to bring these types of net new creators on board but i also think there's a lot of markets that are not email first yet but can diversify and leverage email as an additional channel to engage with their audience and i still think we're pretty early on that email is the form SPEAKER_07: but the content can be variable you and i write a lot you also do a lot of graphics and illustrations your newsletter is in the uh what is like windows 3.1 historical style or something yeah windows 98. oh that's much dated myself there a little bit um but one thing i i'm curious about is emails and newsletters as essentially a way to send stuff that isn't words uh videos or podcast transcripts or audio or whatever so how does beehive think about expanding support for other types of content inside of email to hopefully get those tick tock first creators possibly on to your kind of economic SPEAKER_140: engine as you call it yeah and so what you're pushing up against is like the limitations of email where like native video is just not supported which is like one of the downsides of email right it's antiquated and it has staying power but it isn't as dynamic as a web page what i think we are hinting at is where i see a lot of opportunity in the business and so because i know that the preface for the conversation is like how does beehive 10 100x from here and so i'll paint i'll paint the picture of what i think what we're building is so interesting and like the three pillars that overlap like a multi-billion dollar opportunity one is email two is website and three is monetization and i don't think there's a platform that exists that does all three of those as well as what we're trying to build in a way that's a truly one-of-one opportunity so focusing on email we own the newsletter space now so newsletters are bread and butter i would argue that email and and content based email is actually the smallest segment of emails uh e-commerce and marketing emails that you get for 20 off black friday like there's a reason why mailchimp sold for 12 billion and why clavio is a public company so i think not saying we are definitely going into marketing emails but that is an expansion opportunity if we are great at email what would be stopping us from expanding there and another type of emails like transactional emails so whether it's send grid mail gun basically if you are creating a mobile app or a website that needs to fire forgot password or login like transactional emails is a whole different segment of emails that we could potentially explore not tipping our hat that we're going into either one of those but i think there is a wide range of email type companies beyond just content which we are suited to be able to expand as opportunities present themselves so let me let me explain the two other pillars so the website builder we acquired a website builder company a year ago called type dream we've been building in beta for the past six months we launched it two weeks ago the website as a key differentiator that's vertically integrated with the email is like a great selling point right so you can have a website on wordpress but if you have an email newsletter you're copying pasting into mailchimp or to beehive two different systems two different logins two different uh pieces of infrastructure that you have to manage we've just gone vertical with the website builder and where website leads to is kind of like the classic creator play of link in bio community courses digital products and so i think there's a whole roadmap that can be built and will be built on the website side that allows us to onboard coaches who want to sell their time and they have a storefront of booking time with them directly and rather than paying a 10 fee on a lot of these other platforms that do booking you can have all of your booking is done on our website product that is fully integrated with the email product so you can communicate with your users so i think website as something that we made a big bet on is bearing fruit already and i think there's a huge opportunity and roadmap to be had on the website front and then the last pillar is monetization right and so we offer paid subscriptions just like substack patreon and other platforms we're the only platform in the space that doesn't take a cut of revenue so you can charge your readers 10 20 30 a month and you keep the 10 minus the stripe fees you keep what you charge we have an ad network which has brands like nike netflix hubspot ag1 and so as a publisher and focusing on the icp of publishers you receive ad opportunities every week you see that ag1 wants to sponsor your newsletter for five dollars cpm you don't have to run it if you want to it's a high quality ad and you've never spoken to anyone at ag1 yet they're paying you 150 250 up to a few thousand dollars for running the ad in your newsletter and i think we're very early on the ad network front and in a way you could argue we could maintain our user base we have now scale the ad network and that is zero marginal cost and additional revenue as long as we're filling ad rates in these different newsletters so i guess going back to your initial question like why not jump into marketing yet i think we we have owned this icp of like content first email newsletters and if we can help them grow faster build a website build products on top of their website and monetize i think that's a really compelling offer and i think there's a lot SPEAKER_07: of room to run with that so you know we used to think about companies get into a hundred million in revenue and then going public i know that's a 1997 perspective on things but i still think about a hundred million in revenue is like here is a company that will last for a very long time it has reached essentially uh unkillability in some way it sounds like tyler that with the addition of websites which i believe will unlock uh incremental software or arr for your software revenues uh and growth on the advertising side you have enough components just there to grow the business from a 30 million dollar run rate today to 100 million in some amount of time that answers the question of how do you 10x because i you know if you can get to that scale your last valuation is going to appear tiny in comparison to what you're doing now so maybe the right question then is to ask what could go wrong what could disrupt you because you know i've seen the revenue charts i use the product SPEAKER_149: i've seen the releases things seem to be going pretty well what's potential turbulence on your horizons SPEAKER_140: yeah i mean it's worth calling out for all the revenue projections too we we just launched three and a half years ago so i think we are just getting warmed up and really just beginning to hit stride up until two months ago we had a team that was manually provisioning ads in the ad network to our publishers now we have a machine learning model that's using data and like optimizing both campaigns for advertisers and for publishers so it's very nascent it's successful but very nascent and the new the website builder has been live for two weeks so i'd say like these are big bets that we've been making and investing in for years but we're three and a half years old and i think like just starting to see a lot of these things go live the what could go wrong is i just pitch you eight different business models and eight different icps of we could do transactional we could do marketing we could diversify here and i think it is very hard what i have learned to build a single startup that does one single thing very well that customers will come back to and pay we are trying to build almost like three companies in one with the website builder with the email newsletter and core email platform and then an ad network that is globally scaled with thousands of advertisers across all of these different publishers and each one of those is a almost like a startup in itself and very difficult so can we thread the needle and do all three equally well and have them compound where one plus one plus one equals 10 is like the bet that we're making but each of those has tons of complications and i could see ourselves and if there was an area of concern it's that they all need to SPEAKER_175: work well together in lockstep and it's very hard to do all three at once but it does seem like you SPEAKER_07: have a pretty clear conception of your icp or ideal customer profile if people don't know we're not talking about the insane clown posse and if you stick to knowing what your icp is it seems like you're going to have the right direction to follow to make sure that you do thread the three parts together into kind of one cohesive whole maybe i'm underselling how hard this is tyler but to me it sounds like what you're describing is doable with your team just given what i've seen you put together before you don't need to be modest we're on a podcast you can you know you can beat your chest a little bit okay yeah SPEAKER_140: i mean again it's because we've been here for three and a half years i remember like yesterday the days that we had ten thousand dollars of revenue and everything feels so fragile right so we're in a hyper competitive space a competitor just raised a hundred million dollars we like the valuation though that's good um and yeah it's great it's great for you guys to have that comp and they're SPEAKER_52: jumping into advertising which is something that you guys really kind of showed a new way forward for SPEAKER_07: for folks who don't know you usually don't get a five dollar cpm from an advertiser you're often selling banner ad space at a very low effective cost per thousand or cpm rate um which is why i started off this little chat with the media economies and tatters um because the old models of advertising don't work and yours seems to work at least for newsletters so i don't know i'm pretty bullish tyler but uh just to kind of close things up for today tyler why is beehive and subsec doing so well when traditional media is is in such an absolute dire situation because to me the split screen between beehives growing newsletters are doing so well and also you know my old home of tech crunch has cut SPEAKER_52: huge chunk of its staff it's now down to the absolute bones so what's driving that and is that a long-term opportunity uh for beehive yeah i think the underlying thing there is the owning your audience and SPEAKER_140: distribution so grouping media as a whole as struggling i think is partially incorrect morning brew had an amazing exit and post exit continued to crush it axios had a great exit politico had a great exit the thing all three of those have in common is they were newsletter first and they own their audience distribution where if you flip it to the other side of the equation you see a lot of publishers who outsource traffic to facebook twitter google they monetize with a few pennies on a page view on banner ads and google adsense and when twitter facebook stops prioritizing external links and google now is leaning into ai summaries your traffic dries up as does your revenue so the underlying business model i think struggled you're seeing new business models like puck and other publishers kind of lean into subscription first and they're having a lot of success as well so i think it was again going back to like that easy dopamine high that you can get from like network effects and distribution i think it feels good but those who can own their own distribution build their own moat have their own brand and product and have distribution directly with their audience i think those are like the tried SPEAKER_151: and true media companies and individual content creators that stand to benefit from this all right so SPEAKER_07: the 10x wager from beehive is email is not going away building websites and vertical integration inside your service is going to have a big effect on helping people do more the advertising system can scale well SPEAKER_52: you're going to have lots of software revenues and as media falls apart well the people are going to be building and wanting to own their own audience i can see that being a 10x wager so tyler when you do raise more money you call me and i have the first five five dollars ready to go into the next beehive round so watch out world we'd love to have you i'm going to tell you thank you so much as always for your time i love hearing you explain this stuff and uh when you do hit the next arr milestone call me SPEAKER_163: yeah or subscribe to my newsletter it's the first place where you'll find any of the milestones that we SPEAKER_07: had actually true i had to go back through your newsletters to pull stats for today's chat uh for folks who want to find big desk energy where can they just mail that big desk energy.com it's not SPEAKER_143: a podcast appearance if i don't promote the newsletter i i worked it into the first like SPEAKER_52: two minutes of our chat i know i respect the game i appreciate it of course all right SPEAKER_65: tyler thanks a lot man we'll talk to you soon cool thank you