Parallel

“Like an example right now at parallel, we have so much, the market is coming towards us so intensely. That the team is overwhelmed. There's like not enough people to respond to the demand that we have.”

“One of the things I used to say at Windsurf, and we haven't had to do this yet at Parallel, But I would say I don't ever want a debate or a conflict between my directs to come to me, because if it does, I will intentionally make a decision that's designed to a…”

“40% of first meetings convert into use case evaluation. For us, qualified pipeline QP is starting at scope. So once you get to scope, We expect the close rate to be 60% or greater. So we know 50% of use case evaluation conversations move into scope. We know th…”

“We believe that AIs will use the web a thousand X, a million X, more than humans ever have. And as a result, The web will need to transform.”

“In fact, like the products we've shipped recently are the only APIs that hit human and even higher than human level performance on a variety of deep research benchmarks.”

“Twitter was famously remote friendly. Parallel, we're all in person, in one office, five days a week.”

“People need everything with AI. So that's almost obvious. And now all you really have to zoom into what works and what can work. And where is it going? And you have to look sort of a step ahead and build towards that. And it's a very different art. Like, every…”

“One thing we did early on was we took the counter approach of saying our customer is an AI. And one of the things that led us down was we are going to design an API that is excruciatingly slow.”

“I think that's the same ethos we're taking at parallel, which is like, I think we want the web to be open, and we want it to be permissionless, and we want it to be a free market, and we want everyone to have access to everything, including AIs. We want AIs to…”

“And then we realized that AI performance, when you have repetitive, well-specified work, Improves. Human performance, when you have to train 50 people to do repetitive work, declines.”

“We now serve, like, millions and millions of requests a day, and it's our cheapest, cheapest requests on our system cost under half a cent. The most expensive requests to our system today can cost 10 dollars.”

“Turns out ground truth is never ground truth, right? So one of the things we sort of totally changed in our worldview was ground truth is never ground truth. And that we actually have to do comparative analysis of quality and really reframe every customer conv…”

“I think like hyperscalers Can't move fast enough to capture the opportunity. Can't build fast enough. Right? The labs are amazing. They move really, really fast. But they're also slow relative to how fast we can move.”

“One of the pieces of advice I got as I was starting this company, I spoke with Patrick Collins at Stripe. On building an API business, he said, like, your first API design will be wrong. Just know that.”

“And I had one very simple rubric. People, it's for me just the people I would spend time with. And if they said something to me, and I dramatically disagreed with them, will I feel sleepless that night to try to reconcile why? And people who I feel that way wi…”

“To me, building the company is binary. Either we are successful or we're not. There's just like nothing in the middle, right? So I asked myself the question, I should raise the amount where I can argue up till that amount that I have a reason for believing tha…”

“The second thing that's really important, if you embrace this sort of bet, take risk on hiring, is you have to be somewhat like, the system only works if you also embrace being decent at firing.”

“We don't talk about roles. We don't have teams. We don't have hierarchy. We're very chaotic.”

“I think it's a learned skill to be productive with AI in a real production system. And I've personally, I know my team sees this like vibe coded stuff without deep, full understanding of what I was doing. And my team has had to clean up behind me.”

“The second thing we do really well is really good attribution down to specific sources from which web research was done in a very fine grained granular way. And that allows us to build a differentiator, which is confidence scoring for all of our output element…”

“Part of the reason we do so much attribution down to sources is to be able to do that math. To be able to understand feasibility. We really want to create open solutions where everyone has incentive to remain open”