High Signal Podcasts Evidence ledger
Method
Browse
← Back to evidence

Evidence receipt / preference

Published · transcript-backed

Dan Shipper: preference

24 May 2026 Lenny's Podcast The AI paradox: More automation, more humans, more work | Dan Shipper

“I'm very curious and I'm super all-in on AI." And what that does, I think, is it creates this little pocket of the future where we're all living in it together and we get to be a little bit further ahead because at any other company, there's a mix of people.”

— Dan Shipper

Source trail

Everything needed to verify it.

Speaker
Dan Shipper
Attribution
Verified speaker
Claim type
preference
Recorded
24 May 2026
Publisher
Lenny's Podcast

Transcript context

…The last time you were on this podcast, you had this, it was almost like an offhand hot take that people were sleeping on Claude Code and in particular Claude Code for non-engineering work, for just fixing files, sorting your hard drive, just all these things that people hadn't thought about. Nobody was talking about this. This was a year ago. You were so unbelievably right about this. It's just unreal what has happened since then. They built Cowork, which built on this very specific idea using Claude Code for non-technical work. Codex is getting into this now. I imagine you've been seeing this. They're like leaning into this non-technical use of basically coding agents. I feel like this has also been a big part of Anthropic's success over the past year, just like how do non-technical people use this stuff. So you were just so ahead on this stuff. I even wrote a newsletter post building on this idea. I'm like, "Hey, this is interesting. I should dig into this." I asked people, "How do you use Claude Code for non-engineering work?" And I just had so many examples and it's like my second most popular post. So clearly, you have a unique glimpse into where things are heading. So the premise of this episode is we're going to go through what else you predict will happen in the future, how things will change for people building products. And I think it would be helpful to start with giving people a brief glimpse into just how you operate and how your team operates. That gives you this unique lens into where things are going. So just give us a sense of how you work. Thank you. I really appreciate the introduction. And yeah, I think one of the things about predicting the future or the way that we think about predicting the future at Every is that what you don't want to do is prognosticate. What you want to do instead is just live in it together. So everybody at Every is an AI early adopter. We're almost 30 people now. I think when we did our interview, we were 15, so we've doubled in size in the last year. We're all early adopters and we have engineers, we have designers, we have writers, we have editors, we have salespeople, we have customer service people and everybody has a little bit of that, whatever that thing is where you're just like, "Oh, I like to explore. I like to experiment. I'm very curious and I'm super all-in on AI." And what that does, I think, is it creates this little pocket of the future where we're all living in it together and we get to be a little bit further ahead because at any other company, there's a mix of people. There's early adopters. There's the middle of the pack people and there's people who are very anti. And another thing that happens, which is really cool is we get to, because of our role reviewing models and being a little bit of a pacemaker in AI, we get access to stuff before it comes out. So we get to beta test and alpha test and help steer the direction of where things are going a little bit, which is very, very cool. And so when I think about predicting the future, it's actually, when you create an environment like that, it's actually just about noticing what's going on. I think a core part of it too is writing about it. I think articulating what you're noticing, articulating the future brings it about in this way that makes it real for you and your team and then anybody else who's like on the internet who's reading it. And so the Claude Code thing, it's this very organic thing where, for us, we tried Claude Code when it came out. That's our job. We tried all the new stuff from the model companies and at the time, it was like a little bit early, but right around I think like Sonnet 3.5 or Sonnet 3.7, we were testing that to do our vibe check on it and we were like, "Holy shit, this is crazy." They got rid of the code editor. And so from that point on, we just basically, at this point now we run like six software products internally. At that time we ran maybe two or three. And from that point on, we just started shifting to a world where no one was looking at the code. Everybody was talking to their computer in English, using Claude Code in the terminal. And so I was able to see like, "Ooh, this is starting to happen." And then because my job is a little bit to just push and play with stuff, I was like, "I wonder if I could use this for my writing. How could I do that?" And then it just starts to unfold and you're like, "Okay, this is not ready yet, but it's obviously useful for me." uff, I was like, "I wonder if I could use this for my writing. How could I do that?" And then it just starts to unfold and you're like, "Okay, this is not ready yet, but it's obviously useful for me." One of the things that we talk about internally is what I call the reach test, which is like, when you wake up in the morning, do you reach for it organically?…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.

Search evidence