The Exchanges

Every argument clarity score on this site is built from rows on this page. Each question and answer was assessed with names hidden, the host's own answers included, on four things from 1 to 5: directness (does it answer the question asked), coherence (do the ideas follow), precision (concrete details and clear references), compression (says a lot per word). The weighted mix (30/30/25/15) is the exchange score. A person's published score averages their exchange scores on raw tape only, at least 8 of them, shrunk toward the cohort mean. Full method →

Qasar Younis no published score: only 6 usable exchanges on raw tape, and a fair score needs 8+ · coarse estimate ≈4.5/5 from 6 raw tape exchanges record → ← everyone

Every exchange below was scored with names hidden, four dimensions each from 1 to 5. An exchange's score is 0.30·directness + 0.30·coherence + 0.25·precision + 0.15·compression. The published score averages the raw tape exchange scores and shrinks small samples toward the cohort mean, so five great answers can't beat twenty good ones. Produced feed rows count only toward coarse estimates, never toward a full score.

clear all ✕
6exchanges match
6on raw tape
0redirected or not addressed
Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q At some point in the future, when there's a, a, a book that's written about you and applied intuition, what do you think the, the big idea that somebody might take away or like the thing you would hope that they put it down and the take-home value is what?

A Probably, I mean, on the product side, it is like this concept of intelligent vehicles and the broad category of vehicle intelligence, which is, you know, a category we're in many ways creating and we, we occupy, which is the intersection of things that move and, and AI. So people sometimes say that's autonomy. Autonomy is definitely a big part of it, but there's like in cabin experiences, the engineering tools that you use to build these intelligent systems. I think, you know, we called that, I think, before a lot of people. I, I think we, we saw that A long time ago, and that's one. I think number two, like building up actual business. Like we, and what I mean by that is like, we are a profitable company. We've been for many years. We've grown, you know, we've raised, you know, hundreds of millions in the company's history, close to a billion. We have all of that in the bank. Like that is a functioning business. And so I think like building a high growth company in a way that's sustainable, I think that that's probably the second thing. And then the third thing is, just the way we operate inside in the company is, I, is typically, we, we have folks from every autonomy company, every AI company, every software, big software company, we're about a thousand folks in the company, and consistently people say the companies just run very, very differently. And so we use software to …

AI assessment note: “Probably, I mean, on the product side, it is like this concept of intelligent vehicles”

Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q Does it make you think that, that the, the sort of broad topic of domain experiences is somewhat undervalued in Silicon Valley, that there actually is goodness that comes if you know a space backwards and forwards?

A Today it is because there's, again, the, the Valley is different today in 20, 25 than it is ever before, because now there's no idea. I mean, you can go to an individual YC demo day and you'll see the same company, you know, three, Companies doing the same idea. So, it's a true advantage, because no one can, like, get that fast to get to that, you know, get, get that knowledge. I think broadly, like, if you worked in a hospital group, and you worked on software in a hospital, you're going to know more if you're selling software to hospitals. Now, let's say you did that for seven years. I was in the automotive engineer for seven years, like, before I ever came to the valley. You just learn a lot. You just learn a lot about the innards of this company. We could do a five hour podcast on automotive. I mean, there are thousands of YouTube channels on automotive. I mean, it is its own universe and that's not, you know, trucking and defense and construction mining. We play in all of those in a real way. And so what do we, what do we do? Then we pattern match. We're like, we're going to get into defense. We got to find people who are like us in defense. Who's dad and grandfather words and we're in the military and we work at the DOD. Then we do trucking. Same thing. It's like you start pattern matching to what worked in automotive. And today that's how we built a diversified business.…

AI assessment note: “Today it is because there's, again, the, the Valley is different today”

Answered raw tape D 5 · C 5 · P 4 · Cm 4 4.60

Q In the early days, did you, did that just translate to cash comp was much lower than most other companies and thus burn was much lower?

A That's a part of it for sure. And just like we didn't waste money. Look, also compensation is only a part of the formula. It's, you know, on the low end it's maybe 50%, high end it's maybe 70% depending on software, hardware, mix of, mix of company, et cetera. But it's not the only thing. How you do business trips, how you pay for office. I mean, we, we in this office pay an X amount for rent per square foot. There's a very well funded high growth company across the street that pays two X. Literally two, two times the per square foot. I know the founder. It's a late stage company. I called him and I said, dude, you're screwing up the local real estate market by not negotiating here. It's like, it's actually way cheaper because the landlords are talking to each other. And he said, ah, this is well below the top 100 things I care about. Who cares if I pay a little extra on a building in Mountain View? And so it's just like, that's just a prioritization as well, right? It's a, it's, it's not a simple silver bullet, but we did, we are cheap. It's one of our core values. Be cost conscious. It's one of our core values. Remember business, revenue, expenses, profits. We talked about the revenues. We minus the, you know, we took, we keep an eye on the expenses and we've got profits on the other, other end. A lot of, I think a lot of companies just don't, they don't look, they don't real…

AI assessment note: “That's a part of it for sure. And just like we didn't waste money.”

Answered raw tape D 5 · C 4 · P 5 · Cm 4 4.55

Q Were you worried that, you know, you'd have five customers? Like the TAM is maybe they could all pay five hundred million or a billion a year.

A I worked at Bosch, the large tier one automotive supplier that does, just an automotive, they do like, sixty-five billion in revenue a year. I mean, companies that are at scale that are just even hard to imagine, um, that, you know, in a hundred plus countries globally. So we knew the market existed. Even, I think, a misunderstanding that people have who are not in the car businesses, they think, well, there's like, 40 or 50 brands globally, and that's the whole market. And it's like, Well, individual brands, like individual companies, like a Stellantis of 12 brands, individual brands within, or 14, within them will have lots of product lines, and then each of them might have their own self-driving team, and, you know, it's just such a, you know, a company like Volkswagen has 600,000 employees. That's 600,000, you know, different views of that company. It's not just one company. And so, you have to understand, like, how can we sell, and again, it's getting really into the weeds. I could do an hour on how Automotive is different than, than other businesses, but we knew, we know those things, and so I think we, we organize our go-to-market motion, and we organize our, our products to fit into that, and, and so first, you know, bootstrap with the Silicon Valley companies, and then ultimately springboard into the traditional OEMs, and then use them as kind of your long-term, and th…

AI assessment note: “So we knew the market existed... So it's not just, you gotta get three car companies.”

Answered raw tape D 5 · C 4 · P 4 · Cm 4 4.30

Q So maybe expand on it a little bit. Um, what, what is a founder to do with that perspective?

A Yeah, I think the, the, the mistake you can make is taking, taking advice from uncalibrated people who don't, you know, who haven't done the thing themselves. Like if I ask, you know, Somebody who's in the suburb of, you know, Tulsa who works, you know, as an accountant at a tool and dye shop, should I start applied intuition? They're not the right person to ask. But if you ask a partner at, you know, first round, and they're like, this is not a good idea, then that's an issue. Now, the reality is the partner at first round or wherever is not going to tell you this is not a good idea because they also don't know. All they can say is I'm going to invest or I'm not going to invest. But there's signal there. If you get five, eight, 10 funds that say, we're going to sit this one out, for whatever reason, you should think about that. I think a lot of founders just don't think about it. Now, if you get three people to invest and, you know, 25 to say no, you got three people to invest. That's fine. But I would be really listening to advice. I mean, one of our strengths as a company, when you talk about writing books, we take, feedback is a big part. Not only giving and taking feedback, but as a company in our strategy. I mean, literally right before this podcast, you know, all hands with the whole company, and we talk about very openly, like, these are the faults in the company. These…

AI assessment note: “the mistake you can make is taking, taking advice from uncalibrated people”

Answered raw tape D 4 · C 3 · P 4 · Cm 3 3.55

Q So how long after the company was started did you get your first big account?

A Depends on what big is. I mean, a year in, we, we thought we were getting some big accounts, which would be like a million dollar, you know, account or something like that over, over a couple of years. Now, like that, that doesn't move the needle. So, uh, But yeah, it's, it's, it's all relative, right? It's like, even today, it's like, what big is today might not be big three years from now. But it was true. I mean, from fairly early on in the company, we got traction. Like it wasn't this, you know, it was like, we were like, whoa, is this going to work? Is this not going to work? It's, it's worked pretty well. I mean, we've, we've preserved all the capital we've ever raised, like in the company's history, which is an evidence that the company is an efficient cash generating entity, as in the products we build our Wanted by the market. The market's willingness to pay us more than it costs to build the products. And then we just save all that money for, you know, an eventual war, which is like maybe as a competitor that comes or something, you know, where we can deploy hundreds of millions of dollars, maybe billions of dollars into a specific fight. So, but yeah, we're not, you know, luckily we haven't had to do that.

AI assessment note: “a year in, we, we thought we were getting some big accounts”

page 1
Made with StarZero

Turn any episode into a week of clips.

This entire site, about 80 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.