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
20 published records
01 / preference
“No, we love Temporal. There's some edges that are a bit rough, surprisingly rough.”
02 / prediction
“I think the focal point of that disagreement was the fact that we started working on the API and wanted to make those models available through an API.”
03 / preference
“Well, the reality is that if you're building a product, you're going to be doing a lot of JavaScript, right? And Next, we're using Next as an example.”
04 / evaluation
“Yeah. So technically we were open source and we still are open source, but I think that doesn't really matter.”
05 / commitment
“We're using the models that exist, and we try to push the product boundary as far as possible with the existing models.”
06 / evaluation
“When you have the firehose of information, you can do a ton of stuff with models that are just not accelerating people, but giving them superhuman capability, even with the current model capability because you can just sift through much more information.”
07 / belief
“I think there's nothing too magical in their approach, even if it hasn't been published.”
08 / observation
“When you have discussion with users and there's a bug or a feature missing, you can just point to the issue, show the pull request, show the, show the, exactly, oh, PR welcome. That doesn't happen that much, but you can show the progress if the person that you're chatting with is a little bit technical, they really enjoy seeing the pull request advancing and seeing all the way to deploy.”
09 / evaluation
“At times, it's the Anthropic models that is the best. Our take on that is that we are agnostic and we let our users pick their model.”
10 / belief
“I think we care most for function calling because you want to... There's nothing worse than a function call, including incorrect parameters or being a bit off because it just drives the whole interaction off.”
11 / belief
“I think for most of the ICP companies, the companies that ICP for us, the scale ups that are between 500 and 5,000 people, tech companies, most of the SaaS they use have APIs.”
12 / belief
“I think he's really focused on building the vision and communicating the vision within the company, which was extremely useful.”
13 / prediction
“I'm talking about building AI on top of Salesforce and Zendesk, basically, if I understand correctly. And all of a sudden, your product surface becomes much smaller because you're interacting with an AI system that will take some actions.”
14 / belief
“I think having that capability of changing the scale of your attention in the company, because most of the time you operate at a very high level, but being able to go deep down and being in the known of what's happening on the ground is something that I feel is really enlightening.”
15 / evaluation
“that are starting to provide integrations as a service, right? I used to work in an integrations company.”
16 / evaluation
“There's all these other companies that are like, we will do the integrations for you.”
17 / preference
“Anyway, but like you want creators who are empowered by a bunch of agents, Dust agents to do all this stuff because then ultimately it's just the brand, the curation.”
18 / evaluation
“It's funny because in some ways, the model labs are competing for you, right? You don't have to do any effort.”
19 / commitment
“We build our brand in one specific niche. And in future, if we want to choose to spin off platforms for other things, we can because we have that brand.”
20 / evaluation
“I've written a post called Maximum Enterprise Utilization, kind of like you have MFU for GPUs, but it's basically like so many people are focused on, oh, it's going to like displace jobs and whatnot. But I'm like, there's so much work that people don't do because they don't have the people.”