This Week in Startups
00:39:51 · Lon Harris
[00:39:51] S0: Yes. I mean, I... This is... I'm writing these daily Substack tactical and practical posts. You could check them out, twistartups.substack.com if you're curious. And and this variations on this topic have come up so frequently throughout not just this week in start ups history, but any other tech founder start up podcast that you watch. The idea that a lot of people think that when you come up with an idea for a business, the very first thing you do is make a product. Like, I've figured out a product that people need, and I'm going to build it. And today, this is so especially true because you can literally just tell your agent or Claude, like, here's the tool I have an idea for. Let's build it together. And and what this and so many other founders, come back to is really when you come up with a with a business idea, you've figured out there's a problem. Like, here is a problem people have. It needs solving. I wanna be the person that can facilitate the solution to this. But without getting your hands dirty, building things, talking to your future customers, learning everything you can, you probably don't know the exact right solution. You... It's probably going to take iterations and education and research to really crack how do you solve the problem in the way that the people who are gonna use your solution are going to come back to and repeat use over and over again. So, like, I think that's kind of what a lot of this gets to is that you're you're not ready to build your finish like, let's build Stripe today because I figured out there's a need for Stripe. It's like, okay, now you've got to do a lot of what Patrick talks about in this clip. Now you've got to, like, talk to all of the people who run banks and financial institutions who understand what's missing now. And then in the future, you will know what you need to build that actually solves the real contextual problems that exist.
00:41:45 · Alex Wilhelm
[00:41:45] S3: Yeah. Whenever I hear a story like this from a founder, I'm always, one, impressed at their ability to just work on things that are nonobvious, nonconsensus, and and difficult because that's kinda like you're out in the field by yourself digging a hole. Like, it's not exactly a fun place to be. Yeah. But, also, the willingness to have patience. I mean, if you think about the current startup world today, Lawn, every time you see one of those revenue charts, everyone's trying to be the fastest to a 100,000,000 ARR, the fastest to a billion in recurring revenue, whatever, whatever, whatever. Everyone's obsessed with what have you done in the last thirty days how can I measure it, and how can I instrument, and how can I put that against other things to benchmark it? This seems like a slower process, a bigger problem. Yes. It did take a while, but think about the result they got out of this. I mean, this is a billion dollar company now, but they had to go out there and ask questions. I I I just... I I hope that there's still room for founders like the Collisons who do things that take time to get launched, get rolling, and become unstoppable to build up that inertia versus the companies today that are just kinda going from zero to hero overnight, and I worry that they're gonna go back from hero to zero in the same time frame in some cases.
00:42:50 · Lon Harris, Alex Wilhelm
[00:42:50] S0: Yeah. I feel like it's it's probably like a pendulum swing. Like, right now, things are just in this incredibly... Like, we figured out what a few of the key AI bottlenecks are, and everybody is just pouring into those niches. Like, okay, we need, like, faster, more efficient inference. Like, everybody try to do that. We know that's a problem. You know? So I think we'll probably wait a little while, and then we'll get back to, like, we have to do a little bit more legwork to figure out exactly what these bottlenecks and obstacles are to the next iteration of our AI agents because I'm assuming it's all gonna be AI from now on. [00:43:25] S3: I do just wanna add a caveat, though. I'm not trying to say that today's companies that are growing quickly are not valuable, aren't doing something cool. Of course. I just appreciate that there was a time when you could do the equivalent of messing about in the garage longer. And I think that's something that that we don't want to lose in the broader startup conversation.
00:43:25 · Alex Wilhelm, Lon Harris
[00:43:25] S3: I do just wanna add a caveat, though. I'm not trying to say that today's companies that are growing quickly are not valuable, aren't doing something cool. Of course. I just appreciate that there was a time when you could do the equivalent of messing about in the garage longer. And I think that's something that that we don't want to lose in the broader startup conversation. [00:43:42] S0: I'm reminded of, Clue, q l o o, who've been on This Week in AI a few times recently. Alex, Elias, a great founder. They predated AI. They were already trying to figure out recommendation engines and algorithms, and then AI came along and it's like, oh, this technology is even better. Like, let's just adopt that. And, like, that's been a fascinating process to sort of follow is, like, becoming this AI company because, obviously, AI is good at recommendation engines and put in a lot of data about what you like, and it spits out. Here's what you'll... Else you'll like. And, you know, it just reinvented that business, but he's been building that business all along. [00:44:20] S3: Yeah. No. I love it. Now my last clip from this interview comes when we're talking about the darkest moment in Stripe's history, and the story is not gonna go the way you think it is. So listen closely to what Patrick has to say here.
00:44:20 · Alex Wilhelm, Jason Calacanis
[00:44:20] S3: Yeah. No. I love it. Now my last clip from this interview comes when we're talking about the darkest moment in Stripe's history, and the story is not gonna go the way you think it is. So listen closely to what Patrick has to say here. [00:44:35] S2: Here's a common founder scenario. You're looking over your sales numbers at the end of the quarter, and, hey, your team, they're at risk of meeting their quota. This kind of thing happens all the time. You can't figure out what the specific problem is without taking a closer look at all of the data. Not long ago, that meant pulling it all in from across the entire organization, a time consuming ordeal. But now today, there's Rippling AI. Rippling is already built on your real time people and business data. That means Rippling AI pulls metrics from both their data and your CRM into one dashboard, and then you get to see how close you are to hitting quota. And you can figure out the root of the problem of why you're not getting there. Maybe it's the marketing. Maybe it's the targets they're going after. You can break down all of that revenue by region, by customer size. All of that important information is gonna be at your fingertips in seconds with Rippling AI. When you're running a company, you have important questions that need immediate answers. That means ASAP, as in right now, as in yesterday. So if you're ready to rule your business, head to rippling.ai/twist to get the only AI built to give you full visibility and take complex actions across your startup. What was the darkest moment?
00:44:35 · Jason Calacanis, Patrick Collison
[00:44:35] S2: Here's a common founder scenario. You're looking over your sales numbers at the end of the quarter, and, hey, your team, they're at risk of meeting their quota. This kind of thing happens all the time. You can't figure out what the specific problem is without taking a closer look at all of the data. Not long ago, that meant pulling it all in from across the entire organization, a time consuming ordeal. But now today, there's Rippling AI. Rippling is already built on your real time people and business data. That means Rippling AI pulls metrics from both their data and your CRM into one dashboard, and then you get to see how close you are to hitting quota. And you can figure out the root of the problem of why you're not getting there. Maybe it's the marketing. Maybe it's the targets they're going after. You can break down all of that revenue by region, by customer size. All of that important information is gonna be at your fingertips in seconds with Rippling AI. When you're running a company, you have important questions that need immediate answers. That means ASAP, as in right now, as in yesterday. So if you're ready to rule your business, head to rippling.ai/twist to get the only AI built to give you full visibility and take complex actions across your startup. What was the darkest moment? [00:45:48] S4: The moment where you're like, [00:45:50] S2: this is