Lenny's Podcast / 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
22 published records
01 / evaluation
“10 X the goal that you thought you had and what would it take and it worked really well for Airbnb. So I love that you're doubling down on the same idea.”
02 / evaluation
“I love that. So the idea here is make it very okay to be wrong, but make it not okay to be confused and not clear about here's what we're doing, here's why we're doing it.”
03 / evaluation
“" So those became really powerful. That's on the clarity of thought, clarity of execution is even more important because many organizations actually reach a decision, they don't act on it, which it's one of those shocking things.”
04 / belief
“When I think about the future of AI in the sense of belief, that relationship is going to be sacred, the relationship between AI and the human is going to be [inaudible 01:07:10].”
05 / uncertainty
“If you are thinking about, I don't know, a title or that did not, once I did the change into my excitement around impact, that's been at least my yardstick.”
06 / belief
“I think we're in for AI-nophobia at that point, where you're going to get to a point where AI is going to feel so intimate, so personal that it would actually feel concerning to you to be away from it.”
07 / uncertainty
“Oh man, there reminds me of Friend.com, which just launched in a really fun, I don't know if you saw Friend.”
08 / uncertainty
“Also, why Tomer's most repeated mantra is, "We might be wrong, but we are not confused.”
09 / belief
“Yeah, because I think people get, there is just inertia, people get into their, it's human behavior, people get into their lanes, they start to feel really comfortable within the lanes, and then they don't know that there's a different way to do things and you have to almost externally invoke that or trigger that.”
10 / observation
“In fact, you should go all the way to infrastructure. You can have massive lifts in your product outcomes and goals if you probably enhance your infrastructure.”
11 / belief
“Here's an example that I think sometimes to bring it to people in a more visceral way if you've been building products, product leaders are used to very much dictate the experience they're building.”
12 / belief
“If we think about just your career arc, I'm zooming out a little bit. You helped create the mobile experience on LinkedIn.”
13 / evaluation
“I think when you do minus one to one, it's really hard unless the CEO says I don't care about how the company performs for the next two years, we're going to go for it.”
14 / commitment
“I think the lesson would be, for me that was the biggest learning going into AI first that gave me the why is AI so core and why I got to make it a priority all the way to my role today to make sure the rest of the organization thinks AI first.”
15 / preference
“Most of my traffic to my newsletter comes from LinkedIn, not Twitter where people think, it's absurdly underappreciated and it's I think underappreciated what it took to make this happen.”
16 / recommendation
“I believe knowledge sharing and knowledge exchange is the most amazing way to grow your career and to grow your business.”
17 / prediction
“Actually there's a lot, when I think about our LinkedIn feed and thinking about when you started off, it was hard to imagine what that product could be because it was more of a promotional in nature product and I was like, no, is going to be a place where millions of people and not just tens of millions will come daily.”
18 / commitment
“I have strong conviction about what I could do there. And I asked to do this role and we assembled the team around it and one of the main things we've done was to really set the new purpose for it, which was this is not a springboard for other products, this is not a traffic jumpstart for, it's not an app self feed, it's really about people that matter talking about things that I care about professionally.”
19 / preference
“I don't know if this is a recommendation for everybody, but for me it's worked really, really well.”
20 / evaluation
“I think that's much more important. That's why I think when I say I don't mind being wrong, it really comes from a humble place.”
21 / prediction
“I think if we take a step back, there's so much conversation about zero to one products or scaling products, but you don't have much conversations about minus one to one products, like turnaround products.”
22 / evaluation
“We don't compete for volume, we're not in the same category of Meta in terms of the skill there, but we will compete all day long for the right people seeing your content.”