book / uses
Road Less Traveled
“Road Less Traveled, I've read more than once. I mean, it's just one of the classic human psychology book.”
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Published podcast speaker
Books, apps, and tools
book / uses
“Road Less Traveled, I've read more than once. I mean, it's just one of the classic human psychology book.”
book / recommends
“I would also recommend Thinking Slow and Fast, that's the... Yes.”
Claim ledger
19 transcript-backed records
01 / recommendation
“I would also recommend Thinking Slow and Fast, that's the... Yes.”
02 / recommendation
“Road Less Traveled, I've read more than once. I mean, it's just one of the classic human psychology book.”
03 / belief
“I mean, I think the really important, the reason why I'm doing this, the reason why want to spend time here outside of wanting to be on the show for a while and being a long-term listener is, our long-time listener, excuse me, is there's a lot of amazing work going on at Scale.”
04 / belief
“Am I going to make money tomorrow? So the urgency, I think the biggest thing people miss when they're building new products is the urgency of the buyer part of it.”
05 / belief
“Despite my original story, it's the family treat in the house. I would say that that's probably the top thing that we order.”
06 / belief
“Yeah, I think that's the story he would be referencing. And then, the onboarding of it was crazy because we basically went global with them in six months, and at this point the business was less than two years old.”
07 / belief
“We have the AGI, everything is just going to become AGI, and then there's the skeptics, which is like, "Hey, this is all bunk, this is a bubble, et cetera." And of course, my view is most things are kind of like there's truth in between and some of the extreme parts of the extreme probably correct, but the reality is is that it's very hard to get machine critical use cases in agentic systems where agents are talking to agents to a level of accuracy that is necessary to accomplish a goal.”
08 / belief
“I mean, that sounds like almost daft to say at this point in the market, but if you were to go back three years and think about that from a technological standpoint, a lot of things that we think are trivial now are very sophisticated, and it's a combination of, I mean, the real answer is it's a combination of computational power, model improvement, and data, and all three are getting better at once.”
09 / commitment
“I mean, more practically we will order mixed greens or tender greens or something like that on a day-to-day basis, but I think that the more notable, surprising thing is is that despite my initial aversion to working with a global chain, it's a good treat once in a while.”
10 / recommendation
“Look, if you want to give yourself the best chance, and this isn't always how it works, but if you're in my position 25 plus years in their career, if you want to give yourself the best chance, I think there's two ways that companies end up working out.”
11 / prediction
“To make this tool better and better, you get to a certain limit with the models off the shelf, and actually the people inside of this healthcare system have to do their own labeling. So we talk about labeling for model builders, but we are starting to see the labeling move into enterprises and into governments because you can only get so far with off the shelf plus rag plus some fine-tuning based on recorded data.”
12 / recommendation
“You see this with researchers, because the market's moving so fast, you don't have time to train up some people, so you actually have to go find people either who have the right relationships with customers that you want to get or you have to, who might not check other boxes but are awesome at that, might not check the classic boxes that I think you're referencing of they're a problem solver, they can grow with the company, they have a high trajectory, et cetera.”
13 / evaluation
“You might have a 70% gross margin now because the next question is why can't someone else do this? And if you have an answer of like, "Well, they can now, but they can't in two years, if we run really fast.”
14 / preference
“I think the way that I look at it that might be additive to the discussion is I look at the underlying incentives of the customer.”
15 / evaluation
“And so, what I did is I'm like, I was a golfer and frankly, there was nothing to do in tech. So I started selling golf clubs on the internet and I was making real money and I might've learned more from this business than any other because I started on eBay and I was 22, and I didn't really understand that my margins would come down because anyone can do this, but I was one of the first ones to do it, so I was making a ton of money and then I built this business and then I just failed to recognize I had a lot of hubris.”
16 / preference
“And so, I keep a very, very wide aperture on ideas for as long as I can until I'm like, okay, everything is coalescing. And I think there's a bunch of reasons why you have to keep an open aperture on considering ideas that might seem bad at the start, but you just keep digging and see if you're right that they're bad or you're wrong.”
17 / recommendation
“And then, I think in business, I think Good to Great. It's not the read that you're going to be most excited to enjoy on a vacation, but it's pretty much right, and I think we should take advice from people who have analyzed these business problems before because not a lot's changed, but we keep acting like everything's changed.”
18 / prediction
“You can go from being a dog to being a hero in a very short period of time, but you're on this very, very long journey, but you have to survive for that condition to be met. And so, then the question is is when you're in a hype cycle, I would argue that we are right now, everyone wants to go for it and then go for it more and then go for it more and go for it more and you don't realize, guys, all of our customers are going to be around in five years.”
19 / prediction
“And then you're like, "Oh, okay." And sometimes it's like, we'll just make it up with volume and then the gross margin will go negative for a while and you're like, "Wait, this doesn't work.”