Latent Space / episode intelligence
Speakers in the public record
Claim mix
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
26 published records
01 / belief
“I can’t say th because it, this is like, I don’t, you know, my wife is also Canadian, um, and I think.”
02 / commitment
“Do, do you operate, like if there’s one cha there must have at least one champion who’s like, yes, I will put my career on, on, on the line for this.”
03 / uncertainty
“Um, like Turbo Puffer hired, like, I don’t know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.”
04 / belief
“You know, like, um, I would say so someone needs to like, have both fists up and be like, I’d fight.”
05 / uncertainty
“Uh, people are 10 x saying, everyone’s saying, you know, uh, maybe engineers are out of a job. I don’t know.”
06 / commitment
“Look like we’re all in, like we will just do what we’ll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics.”
07 / belief
“Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.”
08 / belief
“You know, I think sometimes it’s like, well, these are the tradeoffs, but the three nines, it’s like, actually it’s not a real trade off because we can make something that nobody has ever made before and actually make it work.”
09 / belief
“I think another trait is that, uh, the P 99 spends a lot of time looking at maps.”
10 / belief
“You know, Uhhuh like, it’s like the way I think about, it’s like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that.”
11 / belief
“I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.”
12 / uncertainty
“I don’t know if we were the first, like it was very much, it was, I mean, I, I hadn’t, I just looked at the napkin math and was like, this seems really obvious.”
13 / belief
“Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long.”
14 / uncertainty
“We’re just gonna be honest with everyone. Like when I don’t know how to play a game, I just play with open cards.”
15 / commitment
“Usually when you buy fiber, you buy like multiple lines. And we’re like, we can only afford one, but we will just test it that when it goes over the public internet, it’s like super smooth.”
16 / belief
“I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid.”
17 / preference
“I love the guy and we just, um, we just last, like last week we just went on X live and just sat and like shut the shit for like an hour and I think we’ll probably do that again.”
18 / recommendation
“I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data.”
19 / evaluation
“What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I’ve seen some teams that weren’t talent dense and like seemed a counterfactual run, which if you’ve run in been in a large company, you will just see that like it’s just logically will happen at a large company.”
20 / prediction
“I was just sitting down, I was like, why hasn’t anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you’re, if you’re querying it alive, it’s just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it’s really all upside, right?”
21 / evaluation
“The way that I generally think about this is like, there’s a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.”
22 / evaluation
“From a workload perspective, you’re thinking this is gonna be like a read heavy thing because they’re doing recommend.”
23 / commitment
“before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this? And because if I take the money, I really have to do it right.”
24 / evaluation
“Like Notion does a ridiculous amount of queries in every round trip just because they can’t. And I’m also now, when I use the cursor agent, I also see them doing more concurrency than I’ve ever seen before.”
25 / evaluation
“There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.”
26 / preference
“I don’t know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I’m just sitting down and writing a teal code, that’s how I think.”