Public evidence record
Published podcast speaker
Claim ledger
20 transcript-backed records
01 / observation
“Yeah. So the customers we've seen have most success with AI I think are still fairly conservative about some of the ways in which they use this stuff.”
02 / belief
“I think that there are ways to build in inertia and traditional moats, but I think by and large, we're in a space where it is incumbent on us to continue to try to build the best thing, and everyone in this industry.”
03 / belief
“I think that vibe coding right now describes exactly this state of creation that is pretty controversial, where you're generating a lot of coding, you aren't really understanding the details.”
04 / belief
“I think another thing that's tricky about this domain is, it's kind of a new form of product building, where it's very interdisciplinary in that we are something in between a normal software company and then a foundation model company, in that we're developing a product for millions of people, and that side of things has to be excellent, but then also one important dimension of product quality is doing more and more on the science, and doing more and more on the model side of things in places where it makes sense.”
05 / belief
“I think you'll want the ability to move between all of these things fairly effortlessly, and sometimes I think you will want to have the thing kind of go spin off on its own for a while, and then I think you'll want the ability to pull in the AI's work, and then work with it very, very, very quickly, and then maybe have it go spin off again.”
06 / belief
“Many people you hear hire too fast, I think we actually hired too slow to begin with.”
07 / prediction
“The way we netted out is, you need to actually develop your own models from the get-go. And the way we did that was tricky, and there's not a lot of data on the internet of 3D models of different tools and parts, and the steps that I expect to build up to those 3D models, and then getting them from the sources that have them is also a tricky process too.”
08 / belief
“I think to start with, maybe we actually biased a little bit too much towards looking for people who fit the archetype of well-known school, very young, had done the things that were high credential in those well-known school environments.”
09 / belief
“I think one of the things that has been most surprising too is that the growth has been fairly just consistent on an exponential, of just consistent month-over-month growth, accelerated at times by launches on our part and other things.”
10 / belief
“I think less than the UI side of things, maybe taste is a little bit of a misnomer, but just about having the right idea for what should be built.”
11 / belief
“I think the important thing to note is, if you're in a space where you run out of useful things to do very quickly, then that's not a great situation to be in.”
12 / belief
“For the past few years, it hasn't been as big as I think the first experience people have had with some of these big models.”
13 / prediction
“our goal with Cursor is to invent a new type of programming, a very different way to build software. So a world kind of after code, I think that more and more being an engineer will start to feel like being a logic designer, and really, it will be about specifying your intent for how exactly you want everything to work.”
14 / prediction
“I think one thing that's been counterintuitive for us, [inaudible 00:32:14] added a little bit before, but is, we definitely didn't expect to be doing any of our own model development when we started.”
15 / evaluation
“We sort of did this whole grand exercise, and we decided to work on an area of knowledge work that we thought would be relatively uncompetitive, and sleepy, and boring, and no one would be looking at it, because we thought, "Oh, coding's great, coding's totally going to change with this AI, but people are already doing that.”
16 / prediction
“" In a text box, removed from the whole thing. And then the version of the world where nothing changes we think is wrong, because we think the technology is going to get much, much, much better.”
17 / prediction
“I think one aspect of software engineering, and we're very far from this right now, and there are lots of funny memes going around the internet about some of the trials and tribulations people can run into if they trust AI for too many things that comes to engineering, around building apps that have glaring deficiencies, and problems, and functionality issues. But I think we will get to a place where you'll be able to be less careful as a software engineer, which, right now, is an incredibly, incredibly important skill.”
18 / observation
“One of the ways these tools are adopted is, there's developer experience teams within companies, often those are staffed by incredibly senior people, because often, those are people who are building tools to make the rest of the engineers within an organization more productive.”
19 / evaluation
“There's also this cost component of, we're running tons, and tons, and tons of molecules, every keystroke, we need to be changing our prediction for what you're going to do next.”
20 / evaluation
“Because a lot of the time, we run into people who haven't given the AI yet a fair shake, and are underestimating its abilities.”