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
41 published records
01 / belief
“Sometimes it's not even just that the ideas are not worth anything. It's almost just the persistence and execution that I think you do very well.”
02 / belief
“I've had the joy of watching you build this company a little bit, and I think you're one of the top founders I've ever met, so it's just great to sit down with you and learn a little bit.”
03 / belief
“I think serverless is probably one of the most important unlocks for us because it sort of allows us to bound failure into something that doesn't require restarting servers or restarting Linux processes.”
04 / belief
“Exactly, as a load balancing mechanism to have that same user experience with more complicated deployments. But I think that in some ways, maybe a small fish in that pond, but I think that the ease of actually a single endpoint is, it sounds obvious or whatever, but it's not.”
05 / belief
“There's one where it doesn't seem hard for a founder, and I think in those scenarios, it ends up being much harder for everyone else.”
06 / belief
“At Impira, I think our primary technical advantage was the fact that if you were extracting data from PDF documents, which ended up being the flavor of unstructured data that we focused on, back then you had to assemble thousands of examples of a particular type of document to get a deep neural network to learn how to extract data from it accurately.”
07 / uncertainty
“You want to sprinkle LLMs into a database. Because we know how to scale systems, we don't know how to scale agents that are quite hard to be reliable.”
08 / belief
“I think there are a lot of caveats, especially around access to the newest models.”
09 / belief
“The space is very competitive. And so I think I'm hoping, although I'm not 100% sure about this, but I'm hoping we didn't leave anyone totally out to pasture.”
10 / belief
“You can also do evals and all the other stuff. So there's a lot of tooling, and I think you saw something or you just had the self-belief where I didn't, or you saw something that was missing still, even in that space from DIY no-code Google Sheets to custom tool, they were first movers.”
11 / belief
“Not to be too cheeky about it, I would say almost all of the products in the space are spreadsheet plus plus.”
12 / commitment
“I will mention one thing that I'm trying to figure out. We obliquely mentioned the GPU inference market.”
13 / belief
“The thing I would say is not debatable is whether or not fine-tuning is a business outcome or not.”
14 / belief
“I was saying, I think while in the short term there may be opportunities to scale agents by doing silly things, it feels super clear to me that in the long term, anything you might do to work around that limitation of an LLM will be pushed into the LLM.”
15 / uncertainty
“I don't know if it's quotable, but you said you had something from Vercel, from Malte.”
16 / belief
“I think no one knows how durable that revenue is, but all else equal, if a company has some traction and they have the opportunity to build relationships with customers, I think independent of whether their margins erode for one particular product offering, they have the opportunity to build higher margin products.”
17 / belief
“I think the market is very dynamic and it's interesting because almost every company cares.”
18 / belief
“My personal perspective on this, which almost everyone, at least hardcore engineers, disagree with me about, but I'm okay with that, I think DSPy, I think there's two elements to it.”
19 / belief
“One other part of the triangle that I drew that you disagree with, and I thought that was very insightful, was fine-tuning. So I had all these overlapping circles, and I think you agreed with most of them, and I was like, at the center of it all, because you need logging from Ops, and then you need a gateway, and then you need a database with a framework, or whatever, was fine-tuning.”
20 / belief
“While we're in the name-dropping and doing shout-outs, I think a lot of people in the San Francisco startup scene know Alana, and most people won't.”
21 / belief
“I think there's a lot of marketing from SingleStore that makes sense, but there's a lot of doubt in people's minds.”
22 / belief
“Are you competitive? And what I think is like, cursor is taking AI and making traditional software engineering insanely good with AI.”
23 / belief
“I think there's a lot of value in being the chosen tool for an industry because then you just get a lot of community patience for figuring stuff out.”
24 / belief
“I think, to me, it seems very unlikely that you and me sort of like sipping an espresso and thinking about how different personified roles of people should interact with each other and stuff.”
25 / belief
“At Impira, while we were having an existential revelation, if you will, we realized that the debates we were having about what model and this and that were really hard to actually prove anything with.”
26 / disagreement
“Where I disagree is that something that feels like an overpriced toy, I mean, I viscerally remember playing with GPT-3 and it was very silly at the time, which is kind of annoying if you're doing document extraction.”
27 / belief
“I think that you are very perceptive in your mental modeling of me, because I do disagree 15-25%.”
28 / belief
“I'm open to debate, and I might be totally wrong, but I think one of the things that felt obvious to me and somewhat vindicated by O1 is that there's a lot of code and paths that people went down with GPT-4.”
29 / belief
“Bear in mind that I'm now eight years removed from SingleStore, so they've done a lot of stuff since I left, but maybe the meta thing, I would say, or the meta learning for me is that, even if you build the most sophisticated or advanced technology in a particular space, it doesn't mean that it's something that everyone can use.”
30 / belief
“I think being so early in single store also taught you, among all these engineering lessons, you also learned a lot of business lessons that you took with you into Impira.”
31 / belief
“I have a question on this market because I think after Impera, there's a cohort of new Imperas coming out.”
32 / prediction
“Then I'd say probably the remaining 25% are what I would say are advanced agents, which are things that you can maybe run for a long period of time or have a loop or do something more than that simple but effective paradigm.”
33 / evaluation
“I think I with databases and just in general, I've always taken pride in being able to work on the most leading version of things and maybe it's a little bit too personal, but one of the things I struggled with post-single store is there are a lot of data tooling companies that have been very successful that I looked at and was like, oh my god, this is stupid.”
34 / recommendation
“One is that it's very important to have a history of the evals that you've run and make it easy to share them and publish in Slack channel, stuff like that, because that becomes a reference point for you to have discussions among a team.”
35 / evaluation
“Ultimately, we built it in a way that just supports Node, which I think Vercel has sort of embraced as well.”
36 / evaluation
“There's a lot of people, it should be fairly obvious if you look at our customer list, who they are, but I won't call them out specifically, that are doing CodeGen and running the code that's generated in arbitrary environments, but they have also morphed their code into this dumb pattern that I'm talking about, which is like, I'm going to write some code that calls an LLM, it's going to write some code, I might show it to a user or whatever, and then I might just run it.”
37 / preference
“I think practically speaking, I am very passionate about this variant-type issue that we've talked about because I now work in observability, where that is a cornerstone to the problem.”
38 / disagreement
“But really the goal is automatic optimization. And I think automatic optimization is a really valid goal, but I don't think fine-tuning is the only way to achieve it.”
39 / commitment
“There are a lot of things that I took for granted that I later learned at Impira that I had taken for granted, and the most exciting thing is I got to run the engineering team, which was a great opportunity to learn about tech on a larger stage, recruit a lot of great people, and I think, for me personally, set me up to do a lot of interesting things after.”
40 / preference
“As someone who works in observability, I dearly miss the variant type that I used to use in Snowflake. It is, without any question, at least in my experience, the best implementation of semi-structured data and sort of solves the problem of storing it very, very efficiently and querying it efficiently, almost as efficiently as if you specified the schema exactly, but giving you total flexibility.”
41 / evaluation
“There were a few strategic bets that we made early on at Braintrust that I think helped us a lot.”