A promising technology is not a company until the hard parts reinforce one another. Product, distribution, evidence, data and timing all have to spin together; if one link keeps breaking, the founder spends eternity pushing the wheel uphill.

Jamie Wood invited the teardown, so in part four we do it properly. We pressure-test AUTONOMIC's product experience, data advantage, wearable strategy, sales motion and scientific proof—then ask what has to be true for all of it to become a compounding brain-data flywheel.

Transcript

Jamie: What's the hard part? That's literally what I was just about to ask you. Great. Now blow this apart and tell me what I'm not seeing around a corner or where this is not gonna work.

Pablos: I think the first order things that scare me: I wanna know that those users wanna use this product. I've listened to your spiel. I haven't seen the product. I'm probably not really the target market because I don't believe in stress anyway. I don't use anything else.

Jamie: You may be interested in memory enhancement in 10 years from now.

Pablos: That might be true. Memory enhancement might be something that would win me over. I know people who claim to have problems, so somebody's gonna want this.

Jamie: Let's presume there's a customer who needs this and wants it. I'd wanna be convinced that you figured out how to make a sticky product, or at least one that's sticky enough.

Pablos: You may have all the data, and I don't know it. To me, that would be a really important mission for the company to focus on. We need to show that we attract a user, get 'em to try it, get 'em to stick with it, improve them in some way, shape, or form, and get paid. If you can get that flywheel going, you're on track. Without that, or if some part of that chain is broken, you're gonna fight all the forces in the universe forever. You need to get the flywheel working.

Jamie: Let me ask you a question. If we think about how you're looking at this, correct me if I'm wrong, but it's more of a traditional SaaS model.

Pablos: Traditional SaaS is great to emulate, right? There's a lot that might be different here, but most of what's going on in this podcast is me making fun of SaaS holes because I think they're not doing important stuff. That is not what's going on here. You are doing important stuff. What's good about SaaS is they have systematized a lot about startups, investing in startups, and all these milestones you've had beaten into your brain: MVP, product market fit, all that stuff. That's applicable to you.

There's no point reinventing any of that because that's been worked out. All the kinks have been worked out. If you read or watched YouTube videos on how Y Combinator startups work, all that is applicable to you. I think, almost no exceptions, that's the model you should have in your head of how this company should be built and run. You essentially are building a SaaS product. You're trying to affect the brain, and there's neuroscience involved, but most investors won't care about that stuff. They're important ones to win over 'cause you need to probably raise money to build this and grow this, so the investor view is gonna wanna see this flywheel working. There's lots you can do to improve every bit of it over time. If the chain is broken, then there's a problem. Once you got the flywheel working, you can say, "Here's how we're improving this part and this part and this part. This is how we're reducing our customer acquisition cost. This is how we're improving long-term value."

This is how we're working on churning retention, and all the other buzzwordy bullshit they use. All of those things matter to you. I'm making fun of them—that's what I like to do. But that's a great rubric for you—quite venture compatible. Once you've adapted to making it palatable to investors, other things get easier. Your customers get easier 'cause you can back out from there. They're not totally finance driven.

They're partially and they don't give a shit as much as you give a shit, but they kinda give a shit. Customers are kind of in between. You can win people over who are like you.

Jamie: They're like, "Wow, this is amazing. I'm gonna fix brains and save the world, and this is gonna be awesome." Those people are already in your camp. You don't have to worry about them. Finance people are probably the other end of the spectrum from where you are, meaning investors. They're looking: put in $1, and I get $10.

Pablos: You need to be compatible with their vernacular on how they talk about that, so you communicate with them by using spreadsheets, right? You don't send decks to VCs. You send them spreadsheets. Everything I'm saying is a little bit hyperbolic.

Jamie: But also true. Sadly.

Pablos: If you can show your story in a spreadsheet, then you're gonna be in a much better position to make it palatable. They need to be able to understand how this flywheel works: the little money goes in, and a lot of money flies. That's the game. If you're saving lives or keeping people from committing suicide or helping them keep from dropping out of college or all this wonderful stuff?

Jamie: That doesn't really matter.

Pablos: Right? If the spreadsheet works, you can sort of say, "Oh, by the way, you got kids in college? This could be really helpful for them." Oh, great. Then you can start looking for that human connection. But it is impossible to get with any meaningful investors. The story about the money: that's kind of how I would think about it right now. The rest of it is believable. App to build? You don't have that hard of an app. Again, you inherit everything that Y Combinator startups ever did. You have relatively easy software development. Hardest part of it is not the machine learning stuff; it's gonna be integrating all this hardware—monitors.

Jamie: Exactly. I completely agree.

Pablos: One of the biggest problems there is that most of those companies all have a fantasy of building their own platform, their own walled garden, and everybody else is gonna come play with them. They're all gonna fail at that. You will too. Nobody wants to give up the data.

Jamie: If they went through all the work of building—if you think of Muse or Oura or any of those guys—

Pablos: Of the story they sold to their investors is, "We're gonna get the data, and the data is the new oil." They're gonna end up fighting for this position where they get the data and keep it, and invite you into their app store. You're gonna pay them 30% every time you make a buck. That's their vision. It's not gonna work. Almost nobody ever succeeds at that. Apple controls the universe. Apple's gonna win. On any day between now and the heat death of the universe, they can decide, "All your data belong to us." Boom. We're the platform.

You all pay to play in our playground." 'Cause ultimately, Apple has a platform. They own the user. They own the user interface. They own the user experience. They're the only ones who can tie data together between all these apps.

Jamie: But with you and your hacker mind, how do you hack that inconvenient reality that we are up against?

Pablos: I think the truth for a lot of these situations is that once the cat gets out of the bag with the data, it seems like if you are a Muse or Emotiv or somebody who has a lot of brain scanning data, you have this highly proprietary goldmine. You've probably seen how the conversation around AI has come to a consensus recently: we're hitting the ceiling on adding data to an LLM, making it better. Right?

We're at five hundred billion parameters or something. At some point, adding more data isn't helping. It turns out that we loaded up the entire internet in training the LLM. A lot on the internet was dumb shits reposting dumb shit. It didn't end up making the LLMs better to add more of that. Right. The guys who are gonna win in AI chat crap are gonna be the ones who have proprietary data that's mostly real-time. X AI is gonna win because they have the Twitter feed.

The Twitter feed is a very unique, highly valuable source of real-time data; it's hard to replicate. Maybe Facebook has their way, but Twitter's feed is extremely good. That's an example of how real-time data mattered. You don't have a real-time data issue. What's gonna end up happening in your case is you're gonna find that we need data from a thousand EEGs, ten thousand, or maybe a hundred thousand, but at some point more isn't better. You're gonna be the ones to get that because you're gonna be the one who can go to Oura or Muse or someone and say, "Hey, we're gonna give you ten thousand students." You keep all the data from all your customers. You're only sharing data from 10,000 students with us, right? We're gonna take your devices, get schools to pay for them, put them on those students, give you the data back, and keep a copy for ourselves. Sound good? Love it, guys. Sign here. Now you're getting the data that you need.

You're not getting all the data. You don't need all the data. You just need enough data to make your thing, right? That's probably how that could go—some version of that.

Jamie: Let me ask you a question. Using the Twitter/X example real-time data: if we think about, at scale, individuals in different demographics providing their real-time data subjectively, can that translate? Let's think this through. The reason real-time data from Twitter is useful is because it's showing consumer sentiment, what's gonna happen in the stock market, where the wildfire's starting and stopping—that stuff.

Pablos: Who's gonna win an election—this kind of stuff gets valuable economically. It's useless tomorrow. Data: that's what matters. What people thought yesterday doesn't fucking matter. I need to know today. Google probably has it 'cause they have so many search queries. Twitter has a version. Facebook has a version. Very few companies have a meaningful competitor to that data feed. That's why freshness matters: there's a perpetual business. You just need enough data to train this model, maybe update it every couple of years. You don't need fresh data. That's on your data consumption side. On the flip side: are you gonna make money selling data? Are you gonna end up with a valuable data source? You could imagine variations of this where you have dialed in your app, made it very accessible; lots of people love to use it.

Jamie: And it works. That's the most important thing.

Pablos: The most important thing. Even if it didn't work on the therapeutic side, if you're collecting data about how people are stressed, you could imagine certain markets for that. Certainly research, but that's probably not a big market to worry about. If you could make the case that you have a high-value customer base—executives, people who are traders—that would be one where you could say, "Traders are fucking stressed out right now." That's a signal somebody would pay for.

Politicians working on foreign policy are stressed out right now. Everybody at the Pentagon is stressed out right now. I'd have to think about it some more to find some conniving way of making a valuable data set out of what you got. Maybe someone listening will have a better idea.

Jamie: Let's crowdsource this—crowdsource ideas. I'm the first one to want there to be a data marketplace that's efficient. I have worked on companies to do that. We have one company.

Pablos: Working in that space: Data.World. They're doing amazing stuff, but a little bit orthogonal from making the marketplace. I think it's very important. There could be good partnerships. If you get the revenue model working properly, you could imagine a partnership with an Oura Ring: "Look, upsell the users." I assume there's a subscription model.

Everybody wants a recurring revenue model. Probably there's a subscription. You could go to them and say, "Look, upsell your customers. Charge them 20 bucks. Charge them an extra 10 bucks a month, and we'll add our product: a stress reliever, a focus thing, or a memory booster, whatever it is. They're like digital supplements."

Jamie: I was just like, that's fucking great. Take that. Trademark application goes, and then we launch podcast episode. Perfect.

Pablos: Perfect.

Jamie: Opportunities like that where they already have the customer base.

Pablos: They need to upsell. You could be a good upsell for those things—for Apple Watch. It's really hard to sell things through Apple, but it's possible.

Jamie: What you're tapping into is really important in terms of our strategy because a lot of people want to get a product to market really fast and show revenue to show value, but they skip over efficacy 'cause efficacy takes time. Doing it well opens up a huge amount of opportunities. It's a different risk strategy. I believe you. I think putting it back in consumer SaaS: efficacy is a really hard thing to sell to people initially.

I agree. I think efficacy sells through testimonial and word of mouth. Once you have users saying, "This fucking worked for me," that's when you get the multiplier, right?

Network effect. You get customers: "Oh, shit, you're not using Autonomic?" You want every podcast guest on every other podcast to be saying, "Oh, my God, you gotta try—" I had that first moment happen a couple months ago. Somebody I knew sent me a screenshot saying, "I was just on a call with this AI guy from New York, this other guy from Toronto." He was on a team call with a company, and one person on the call was sharing a story about how they weren't doing well and were having a hard time focusing. Then the other guy said, "Oh, I just started using Autonomic. You should try it." I was like, "What? It's working." Oh, great. Oh, my gosh. There you go. People can come to the platform and just use it. We're going after schools—B2B—but you can absolutely sign up, try it for two weeks and get going. We do have people dribbling in from all over. Of course, then you're like, "Well, how'd they find out?"

Everybody, find the most stressed-out person. Send them to the website: GetAutonomic.com.

Pablos: We'll get you some beta users

Jamie: Let's go. I know stress is real. Maybe you just really wanna learn about your brain.

Pablos: Training.

Learn about neuroscience.

Jamie: Start.

Pablos: With yourself. The things you're experiencing—learn about them.

Jamie: Learn the science of why behind it all. Build the habits. Away you go.

Pablos: I'll try

Jamie: Yes, you will.

Pablos: I'm the worst customer.

Jamie: You can't cut it out now. Then we could have a product review.

I'm sure. I might need a glass of wine or something.

You may be aware that I was stressed out. I was thriving in denial until I tried— If you'd like to be blissfully unaware, don't use Autonomic.

Pablos: I can find you some nerds to help build it and some investors to help back it. It'll be cool.

Jamie: Wouldn't that be the dream?

Pablos: Wouldn't that be the dream? It is the dream.

Jamie: Difficult dream to realize sometimes. But you have a lot of the bones of a good run here, so get it going. The reality: you get capital to move faster. If you don't get it, you just move slower. But if you're used to bootstrapping, you're gonna get it done. You're gonna be scrappy. You're gonna take that penny, turn it into a dollar.

That's how it works. Then, of course, you need the hardworking piece. You need to wanna work hard, wear a lot of hats, and basically eat shit for a year. It's so much more rewarding.

Pablos: A lot of the problems that your users probably have is they're just not working enough. That's what I think. I'm so politically incorrect about it, though. Think about the history of humans on Earth: free time is a pretty modern invention. We have these romantic fantasies of hunter-gatherers: just waking up in the morning under the sunshine. Go look for some dewy berries, pick them, eat them.

Jamie: That's not how it was, guys. Everybody was fucking dying all the time. Suffering.

Pablos: Suffering and dying all the time. Short, nasty, and brutish. If you start there and work your way towards 2025, how long have people actually had a significant amount of free time?

Jamie: You're probably gonna get an answer: a century or less. If you look back, basically all of your ancestors had to work their asses off, and you just have to watch Netflix.

Pablos: That's a pretty high contrast. It's no wonder your brain can't handle it.

Jamie: Why does the world need you if all you do is watch and think about the overconsumption of information? You watch Netflix and then read TikTok.

I actually wanna jump in on something you've said, which is really interesting. It ties to a creative friend that we share—Franz. He gave me this exercise last year: "What's the voice of the coach?" He's used the platform. He was like, "Listen, I like it, but it feels too scientific." Sterile. Exactly. "What's the voice?"

He sent me away with this homework. I'm right there with you. We're not here to hold your hand and sing Kumbaya: "It's okay you're having a hard time." No, you're missing a toolkit. You're missing important information about your own brain. Learn it, apply it, go kick ass. That is what we've built. Super cool. He was like, "When I talk to you, I get what you're trying to do."

Pablos: This is the wrong direction. Have you ever watched the TV show The Wire?

Jamie: Pick one of the union bosses in Baltimore who's gritty and fucking working his ass off and basically suffering 'cause they don't make enough money.

Pablos: Get one of those guys.

Jamie: You rule with an iron fist. They're all no-bullshit guys. That's a really important piece: let's cut the crap. Here's the science of what you need to learn. Go apply it. We'll help you train that behavior, 'cause guess what? It's gonna work. You're gonna feel better to continue doing cool shit. You don't need to find all this time or have this "I have to go back to the office" thing. Whatever your suffering is, you can do so much more.

But if you're gonna skip over some real fundamentals of how the nervous system and the brain works in terms of behaviors you can have to support them, and even just understanding of it, you're caught on your back foot.

Pablos: Is one of the recommendations that the Autonomic app might make to me, get off your ass and go to work?

Jamie: Might make for me: get off your ass and go to work? If there's research on the positive effects of telling people to just suck it up and go to work? I think part of that translates to how I was brought up. You need to work hard. You need to try. Nothing is gonna be handed to you. I learned that right away when I thought, "Oh, this is great—"

I get to work in my parents' office, and, "Oh, wait. They treat me terribly."

Pablos: Genius parents. I should've done that. Too late now.

Jamie: My kid thinks she wants to go to college. I'm a failure. That's a hacker's worst nightmare. That's a doctor's nightmare. She can use Autonomic.

Pablos: I think she's got a good head on her shoulders. I wonder if it would help. She's got some friends who need it though.

Jamie: The biggest thing for us that's valuable right now is feedback. Where can we be better? Where can we iterate? We've got an objective we're trying to reach, so use it, try to break it. Give us the hard, direct truth. Try to make me cry. Tell me your opinions. You seem good for that. I tried to make you cry; it hasn't worked. It seems like you're doing really well. You're gonna be a great founder.

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Recorded on January 16, 2025