How Palantir built the ultimate founder factory | Nabeel S. Qureshi (founder, writer, ex-Palantir)

Lenny Rachitsky:Thirty percent of PMs that leave Palantir start a company. Just give us a picture of what what the people are like.

Nabil Qureshi:I feel like they screened really hard for a few traits in particular. One is like very independent minded people who weren't afraid to push back. Two is people with broader intellectual interests.

Lenny Rachitsky:What's the difference between say a PM at Palantir versus a traditional PM?

Nabil Qureshi:They were extremely careful about only making people PMs who had first proven themselves out as forward deployed engineers. You basically could not become a PM any other way. There's two types of engineer at Palantir. So there's one that works on the core products and they're a traditional software engineer. There was a different type of engineer which you sent into the field, right? You would spend maybe Monday to Thursday and you would actually go into the building where the customer worked and you would work alongside them. You would literally get a desk bath and so that engineer became known as a forward deployed engineer.

Lenny Rachitsky:What's something that you believe that most other people don't?

Nabil Qureshi:I think this is a somewhat contrarian view within tech.

Lenny Rachitsky:Today my guest is Nabil Qureshi. Nabil is a founder, a writer, a researcher, and an engineer. He was recently a visiting scholar researching AI policy at the Mercado Center alongside Tyler Cohen. At one point, he worked with the National Institute of Health and major clinical centers to create the largest medical dataset in the world. He worked at the Bank of England for a bit. He was founding member and VP of business development at GoCardless, one of Europe's biggest financial technology unicorns. And most related to the topic of this conversation, Nabil spent almost eight years at Palantir as a forward deployed engineer working on public health projects with US federal agencies including public health services during the COVID-19 response and applied AI in drug discovery. Whether you are a fan of Palantir or hate everything that they do, they are an important and fast growing company that is pumping out incredible product leaders as you'll hear more than any other company in the world, so it is worth studying and understanding. I've never heard an in-depth conversation digging into how they operate, build product, hire, and were able to scale from a primarily services business to a software business, so I am very excited to bring you this inside look. In our conversation, we go deep into what the heck does Palantir even do, why getting good at managing lots of data is an underappreciated secret to their success, they look at the unique forward deployed engineer role that they innovated and what other companies can borrow from their insights here, also how they hire and how they build amazing product leaders, plus a ton of advice on talking to customers, building products, and starting companies. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a bunch of amazing products for free for a year including Superhuman, Notion, Linear, Perplexity, Granola, and more. Check it out at Lenny'sNewsletter.com and click bundle. With that, I bring you Nabil Qureshi. This episode is brought to you by WorkOS. If you're building a SaaS app, at some point your customers will start asking for enterprise features like SAML authentication and SCIM provisioning. That's where WorkOS comes in, making it fast and painless to add enterprise features to your app. Their APIs are easy to understand so that you can ship quickly and get back to building other features. Today, hundreds of companies are already powered by WorkOS including ones you probably know like Vercel, Webflow, and Loom. WorkOS also recently acquired Warrant, the fine grain authorization service. Warrant's product is based on a groundbreaking authorization system called Zanzibar which was originally designed for Google to power Google Docs and YouTube. This enables fast authorization checks at enormous scale while maintaining a flexible model that can be adapted to even the most complex use cases. If you're currently looking to build role based access control or other enterprise features like single sign on, SCIM, or user management, you should consider WorkOS. It's a drop in replacement for Auth0 and supports up to 1,000,000 monthly active users for free. Check it out at WorkOS.com to learn more. That's WorkOS.com. This episode is brought to you by Ateo, the AI native CRM. Ateo is built to scale with your business from day one. Connect your email and calendar and Ateo instantly builds a CRM that matches your business model with all of your company's contacts and interactions enriched with actionable insights. Sync in your product's usage, billing info, or any other data sources and Ateo's flexible data model will handle it all without any rigid templates or workarounds. With Ateo, AI isn't just a feature, it's the foundation. You can do things like instantly prospect and route leads with research agents, get real time insights from AI using customer conversations, and build powerful AI automations for your most complex workflows. Industry leaders like Flatfile, Replicate, and Modal are already experiencing what's next for CRM. Go to Ateo.com/Lenny to get 15% off your first year. That's Ateo.com/Lenny.

Lenny Rachitsky:Nabil, thank you so much for being here. Welcome to the podcast.

Nabil Qureshi:Thanks, Lenny. Glad to be here.

Lenny Rachitsky:In our chat today, I wanna zero in on a post that you recently wrote where you shared your reflections on your time at Palantir. You spent something maybe just under eight years there. The reason I'm really interested in Palantir is I've been doing a bunch of research recently looking into which companies hire the best product managers and create the best product managers and Palantir just keeps coming up over and over in the work that I'm doing. So I'll share a few stats real quick. So I looked at which companies produce the most founders especially out of their PM team and Palantir is by far number one. 30% of PMs that leave Palantir start a company and that's like and number two is number is 18% and that's Intercom. So that's that stat. I looked at which companies PMs that leave get immediately promoted in their next role. Palantir is number one of all companies in the world. I looked at which company's PMs become the first PM at another startup that they join. Palantir is number two in the world. And then I looked at which company's alumni PMs become head of heads of product down debt later in their career. Palantir is number three in the world. Also just the company is doing extremely well. It's worth I think something like $200,000,000,000 these days. So there's a lot to learn from Palantir. I actually wanna start with a question that I imagine every employee at Palantir constantly gets that and I still don't think people totally have an answer in their head. What does what does Palantir do?

Nabil Qureshi:That's a great question. You started off with an easy one, Lenny. So Palantir is the way I describe it is they achieve outcomes for their customers very tactically. The way they do that tends to be through a data platform. So they have what I consider to be the world's best data platform and I can go into what that means in a second. And then there's a couple different versions of this. So there's one that's optimized for intelligence and defense use cases. That one is called Gotham. And then there's one that's more optimized for commercial use cases. That one's called Foundry. And that's kind of the classic explanation of what they do. So they sell a data platform. They typically work with very large customers is the other thing. It's going to be Fortune 50. It's going to be governments around the world. It's going to be those kinds of. So that's the kind of capsule answer but there's lots to unpack in there.

Lenny Rachitsky:Awesome. Okay, and we're gonna touch on a lot of this stuff including the data piece. I wanna start with talking about just kind of the people and the culture of Palantir. You shared a bunch of really funny stories of what it's like to come to work and even even interview at Palantir. There's a story you shared where because maybe the cofounder you're walking by and he's chewing ice and you're and that's like some benefits of cognition. Just give us a picture of what what the people are like especially early days Palantir and the culture and how unique it might seem.

Nabil Qureshi:Yeah, it's definitely it's an No One company. I don't know how else you would stop stop this company if you were not somebody like Peter Thiel. And so far as it it seems like you know there was a point at which they owned a silly fraction of the office space in Palo Alto. So you'd walk around Palo Alto and it would just be you know pounds of hoodies pounds of buildings everywhere and so on. And so I feel like what happened at some point is they raised a lot of money and they resorted to all these really interesting ways of just getting top talent out of places like Stanford and other you know other top schools and just people who knew the founders who tended to be very interesting people. And I feel like they screened really hard for a few traits in particular right so I would say one is very independent minded people people who weren't afraid to push back who questioned frame of everything and thought for themselves and had sort of strong convictions. Two is just like people with broader intellectual interests you know Kop Kop just released a new book and you know he's quoting Habermas and all these European intellectuals and just things you don't typically see a tech CEO do. And so I think there's that intellectual strand in the company and then yeah I think three is just people who are very intensely competitive there's there's a sort of win at all costs mentality to the company and so I think those were the kind of set of traits that were like this gravity well in California at a certain time and so you just had a lot of really fascinating people joining the company at that time. The way they screened for this was interesting too right so for the longest time they had everyone does this now I think but it's like at the time it was a little bit rarer as a founder had to interview you in order for you to receive an offer and so a founder it it could have been Alex Karp it could have been Stefan Cohen earlier on it might have been somebody like Joe Lansdale but it was always like one of these people and the interviews were pretty strange so you know with with Stefan it would be you'd be chatting about philosophy for an hour and a half and it would very much just be like he would pick a topic out of thin air it was impossible to prepare for and then he would just go very very deep and try and test the limits of your understanding but it would really just be a fun conversation and then you know if you pass the vibe check you'd be in and so there was that strong selection mechanism. There was also the question of you know I think it's it might have been Thiel who mentioned this but he thinks that a lot of the best recruiters in the world or like companies that attract talent they put out this kind of distinctive bat signal and it has to turn some people off that's kind of the key of a good bat signal right so I think in the present day OpenAI Anthropic they're both sucking up like some of the best talent that you and I know and I think one way they do do that and they are sincere in this but they do really attract people who are almost messianic about the potential of artificial superintelligence right and who really believe this is the only thing that matters and it is gonna be the biggest thing in the world. I think Palantir's version of that was that you know they were quite focused on things like preserving the west there was a slogan of save the shire right so they were talking about military and defense and intelligence and the importance of that well before everybody else. Bear in mind this was during the era when it was social mobile local apps right social media was on the rise you had you know the hot companies were like Facebook and Pinterest and things like that and so this was at the time a very strange thing and so I think to be drawn to that you had to look at the other options and say well this is fine but what am I really doing in life right whereas you had this other place that was like hey come solve the hardest messiest problems in the world with us and I think just at that time that really drew some really good people.

Lenny Rachitsky:We're gonna talk about the thing the reasons people don't necessarily like Palantir and kind of the moral question of what they do but when people look at a company that is like like I guess OpenAI's to your point is a good example where they're just like so turned off by maybe their approach you're what you're missing is that's potentially intentional because that actually draws in the people they really want. It makes me think about I was involved in the creating the core values at Airbnb and something that we learned at going through that process is when you define the values for your company it's really important to clarify who this is not for exactly as you described which is feels unnatural like oh we wanna be inclusive we don't wanna make people feel like they don't belong but the whole idea is to be clear on here's who will thrive here and here's who's aligned with our mission and I and what I'm hearing is Palantir and these companies take it to the extreme.

Nabil Qureshi:100%. Yeah on my team at Palantir one process that we followed I could talk about this more if it's interesting is you had to when you started a new project you basically had to organize what they called a murder board for it. I think this is originally an army turf right so the idea is basically you write up kind of a two page plan for the project you invite three or four smart folks you know who don't know anything about the project and their job is just to tear apart your plan right and so you have to write like here's the vision for this here are the goals there are the like tactics over the next three months and one section was principles that you're following for this project and I remember giving this advice a lot was just like when people joined they would they would write principles such as you know move fast and I would always be like everyone likes move fast so I guess not a good principle actually because nobody can really disagree with this reasonably right you need something that actually a lot of people are gonna go like why are you why are you taking this principle this seems wrong to me so you need something that people can disagree with.

Lenny Rachitsky:I wanna come back to this the beginning of what you described of what Palantir looks for in people you talked about independent minded a lot of interest broad interest and competitive first of all I think a lot of people hearing that especially the last part be like I don't wanna work there why does this work because this isn't naturally what you would think of as how you build the most amazing productive team

Nabil Qureshi:Yeah I think it it just draws people who wanna win right I think that's what was really important there the other piece of it I think is that there's actually and this was much truer ten years ago right is there was a lot of talent that was a little bit outside of the tech ecosystem but could easily have been very successful within it so you know people who got out of the military or one of the intelligence agencies and they were doing let's say an MBA somewhere to transition into the corporate world and I think typically they would have taken a position at a kind of classic Fortune 500 corporation and actually Palantir managed to get a bunch of that talent and at the time that was very undervalued you know the the people who succeed the most in the marines or the special forces or whatever it is tend to be pretty smart people they tend to have accomplished very difficult goals in very hostile environments and it turns out that when you're starting a somewhat chaotic tech company that's actually a very useful skill to have again I think more companies are doing this now so scale AI Android etcetera at the time that was a very differentiated talent pool so I think having those values as opposed to maybe the values that were more in fashion then so talking about you know how inclusive you are or you know the sushi that you serve at lunch or whatever it is it just drew a very different crowd and I think I think the game that was being played there was one it's it's mission alignment right like you're doing a defense company that's the kind of person you wanna attract but I think there's also two which is just what is the talent that maybe is a little bit undervalued now and how do you actually draw those people to you and I think that game is always shifting

Lenny Rachitsky:This this is definitely starting to explain why so many Palantir alumni go on to start companies and become leaders at other companies like this is a these are leaders that you're hiring so it feels like a lot of it is just the talent you hire people that are naturally leaders

Nabil Qureshi:I think you're right and we can get more into it but I think there's also there was also a very concrete set of ways where that place was a training ground for founders I even think it turned a lot of people who might not have become founders into good founders because of just because of the way it works so I think there was a selection effect there but there is also some sort of training effect too but it's kind of unique to the way the company works

Lenny Rachitsky:And is that along the lines of the forward to play engineer stuff or is that something else

Nabil Qureshi:It is that okay

Lenny Rachitsky:Cool we're gonna get to that I love it okay amazing before we do that one last thing is something I've seen is that you guys at Palantir don't have really have titles everyone's kind of the same level and just like generic titles for everyone talk about that why do you think that was important why why was that useful

Nabil Qureshi:I don't know this for sure but I do I do know that Thiel writes about this in zero to one and his take is just that as soon as you have these titles you have a thing that people are competing for and then you get these very unproductive conflicts you get people optimizing to game the system you get Goodhart's law everywhere right so it's like you have a metric and then people basically manage to the metrics there's a lot of interesting I don't want to pick on any one company but if you take Google for example there's a lot of interesting posts by people who left Google and they cite this as a reason why they got a little bit disgruntled is that there's a way to get promoted rather than like let's say improving an existing product what you do is like you start a completely new and that has your name attached to it and then when it comes to promotion season you can say hey like I did this new thing and then boom you have a new Google product that is is is maybe confusing to the end user so I think they wanted to avoid all of these kinds of dynamics right and so the way that they did that was they said well titles are not gonna be this sort of mimetic totem that everybody competes for instead everyone's just gonna have the same slightly meaningless title which is for an engineer and the only people who did have titles were the CEO and then there were six directors and that was it and and now I think you know it's a little bit more nuanced there are different teams there are some people with titles but honestly it was almost like we used to joke about it right it's like people would leave the company and then you'd see them update their LinkedIn and they would be like oh yeah I was totally the SVP of you know x y z and it's like no you weren't you just you know but then it's like I I totally understand it too because when you leave the company you have to make your experience legible to the next person and and so guess what things like SVP actually do matter right and so yeah I think they didn't they they wanted to avoid this kind of intel competition there are downsides to doing this right so maybe the competition isn't as explicit around a specific title but instead what it becomes about is you know there's a particular exec or something and you want to gain that favor and so it becomes more like who can get in the inner circle of this person or whatever it is and there were those dynamics too I actually am a big fan of this philosophy though the no titles one I think what it did do is that it basically said you if you are in let's say you're in a role of you're leading a very important project right which would happen what it said was this is always fluid so you are in this role because you're very good and so it's a meritocratic thing but if if you stop performing well it's actually very easy to shift that because there is no explicit like I am the GM of this this project kind of title and so you always had to kind of earn your place in the company you always had to earn the right to work on what you were working on and I think that was a good side effect

Lenny Rachitsky:Let's start talking about forward deployed engineers what is a forward deployed engineer

Nabil Qureshi:Yeah so the way this originated was basically you can think of it as there's two types of engineer at Palantir right so there's one that works on the core products so they don't necessarily leave the building in Alto or New York where the offices they're very much working on the core products and they're a traditional software engineer because of the way the company works where you had these very large engagements with these large entities there was a different type of engineer which you sent into the field right so what that meant was you would spend maybe Monday to Thursday and you would actually go into the building where the customer worked and you would work alongside them you would literally get a desk there and so that engineer became known as a forward deployed engineer so within the company that function is known business development or BD and then PD is product development so it's where the product is made and so within BD you had forward deployed engineers there are actually two types so there is one that is sort of a more technical software engineer so you have to pass a software engineering interview and prove your chops there and you would typically have a CS degree but there was actually a type of forward deployed engineer that didn't have that so you would still get sort of a technical interview but it would be less about you know do you know the specifics of this C plus plus algorithm it would be more about just like can you reason about data and we we kind of didn't have that division originally but it turns out that there's a lot of people who are you know technical adjacent shall we say who you really need in the room when you're working with these large organizations or these large companies because translating what you're doing into language that would resonate with an executive or being able to kind of navigate the social dynamics in a room all of these are very valuable skills and so the hiring criteria there were a little different right it was a bit more about like are you savvy as a human but you know all of that was given the title of flawed deployed engineer and it's just an engineer who works with customers

Lenny Rachitsky:Okay so just to make this crystal clear for people because a lot of people hear this idea of Palantir having forward deployed engineers a few other companies have done this it's pretty radical so as you described you basically have a desk at a company so you work with Airbus and we'll talk about that so I'll just make it real so you have a desk and a computer and login access and all these things at Airbus at you work you go to their office four times a week you're sitting there with their employees working like side by side building a product for them versus what most people do where they just talk to customers in quotes where they do an interview once in a while they do a zoom they share mocks things like that this is like that on steroids is that roughly the the way to think about it

Nabil Qureshi:It is yeah and and so we would we would really be there a lot of the time and so the the side effect of that was one you learn to live and breathe the customer's problems and you learn to speak their language right and eventually they saw you sort of as one of them and so you develop these really close bonds with the customers so at Airbus I would be at the factory where the planes were produced or I'd be sitting next to you know people diagnosing issues with aircraft or whatever it was similarly later on I worked with the NIH which is part of the US government and I actually had a batch there and I would work with civil servants and biologists and clinicians and people who are working there and so it's this it's this pretty radical thing as you suggest I think the key thing there from a business point of view right is the average kind of deal that Palantir had was very large it's in the many many millions of dollars which means that you could kind of pay for this as part of the thing that the customer got and then it was sort of priced according to the value that the customer got right so as a simple example like if you're Airbus and you're let's say that you have an issue with one of your planes and you need to fix it and fixing that is worth you know a $100,000,000 or something to you that's how it would be priced it would not be priced as hey you're buying data infrastructure and it's similar to Snowflake or Databricks or one of these other providers it's much more anchored to here is the outcome but then the job of the forward deployed engineer is not just to deploy software it is not just to sell software it is to actually solve the problem and so you would have to be there you would have to meet the key stakeholders who are actually in charge of reporting to the CEO about this specific issue you would have to become their friend you would have to gain that trust and you would have to in some cases create new software such that it could actually solve the novel problem that was in front of you so I would have friends who worked with one of our energy company customers and they would have to learn the ins and outs of how oil wells work and then out of that it turns out that having streaming data is actually very valuable for this use case and so boom suddenly there's a product that can handle streaming data that becomes part of the core platform but that would be the motion is you learn about the problem you figure out what software would best address it you build that software you use it to accomplish the goal and then eventually that kind of gets folded into the broader broader product suite and so you can start to see why this would be a good forge for founders right and this was actually part of my thesis going in and joining was I said well say I got five reps of this which I got more than that right but say you get five reps of doing this in five disparate contexts you actually become very good at this cycle of like okay go into the building gain the trust of the person meet the people that are going to become your users talk to them about their problems make sure you're building something that actually solves them and you know isn't just a boondoggle get really fast feedback and iteration loops right so every week you would have like a cadence where it's like Monday you go and you do your meetings Monday night you build something Tuesday you show it to somebody Tuesday you get the feedback Tuesday night you iterate on it Wednesday you show it to somebody Wednesday night you iterate on it so you you get like four of these five of these cycles every single week and you're moving incredibly fast so six weeks in you've suddenly gotten to wow this is really valuable and somebody's willing to pay you whatever 20,000,000 for it and boom I think this is why you get so many founders coming out of this same process

Lenny Rachitsky:It's becoming very clear why so many founders emerged out of Palantir okay so an important element of this as you described is that the idea here is build this as a one off solution to solve a real problem at say Airbus or some government organization and then the idea is you create something out of that that then Palantir can sell to other companies what's extra cool about that is you they pay you to solve this problem for them and then that is funding this other product that Palantir can now sell to everyone what a cool what a cool business however early days Palantir everyone thought it was just the services business or just consultants building software for companies like Airbus there's no way they can make this a platform that works for a lot of people clearly that's what's happening and it worked out this is kinda like the holy grail solve one customer's problem and then sell it to everyone else every every SaaS business basically would love to do this what what do you think allowed them to actually achieve this and be good at this what are some principles that that worked

Nabil Qureshi:Yeah that's a great question and and it's true I think that from when I joined until maybe till IPO and a little bit after you know I was told hey isn't this basically like a Sparkling extension right isn't it a consulting business kind of lopping as a product company and eventually it became undeniable one because you know I always laugh when people are like what does Palantir do it's like you can go onto YouTube and just search Palantir demo and you'll get plenty of demos of how the software looks not many people know about this but you can go and sign up with a credit card right now and start using it

Lenny Rachitsky:Have a Palantir account?

Nabil Qureshi:You actually can, yeah.

Lenny Rachitsky:Not know that that's...

Nabil Qureshi:Cool. I think it's called AIP now, so it's not actually that mystical and there is a product. And if you look at the margins they show that, right? So they have like 80% plus margins which is not really what you would get if you were actually a consulting company, would be closer to 20 or 30%. So then your question was, well how did they actually achieve this? I think there was just incredible talent in the product development organization, like really top tier incredible talent. And it took somebody, it took some really really smart people to take the set of internal tools that we were using at the time to create value of customers and then go, what is a unified version of this? What is the thing that, what would this look like if this were a product? And out of that process that I saw came Foundry. I assume there was a similar process with Gotham a while back, but basically it's like the motion was that you would go in and early on you were basically armed with Jupyter notebooks and some kind of data integration stuff but it was very primitive and you had to create value that way. But we kept building tooling that was useful for forward deployed engineers so we were our own first customers. And at some point there was this concept of wait, what if we take our internal tools and we let our customers use them? And I remember at the time this is a really radical idea. And then Shyam Sankar is one of his, I think he's the CTO or maybe he's the president now, he just mandated like okay every customer deployment you have to have a customer using this within, you know, three months or whatever it is. And so it was horrible at the time because these had been built for these, you know, nerdy Silicon Valley engineers and so they weren't particularly usable. They would crash all the time, you'd have to debug, you know, spark errors or whatever it was. But basically that process brought a lot more rigor to our thinking about the product and out of that kind of I would say three or four year process came the Foundry product. And then there was a lot of focus around, you know, things like performance and reliability and so on. That was all really painful. And so yeah, I think the answer was just talent. And then there was this recognition that we do know things that most people do not know about how data works in large organizations. That was the other thing we discovered a lot of, you know, quote unquote secrets in this process of living with customers for so long. The basic one was just data integration is massively painful inside organizations. Organisations, this is very hard to understand unless you've worked in a large organisation, but it's actually impossible to even now to get access to a lot of your own internal data that you need to do your job. So you'll hear stories of people being like I'm trying to calculate our sales this quarter, I had to wait six weeks for some other analytics team to get me this deliverable. And so just the knowing problems like that and being able to focus our product efforts around those problems meant that we were able to build something generalizable there.

Lenny Rachitsky:Okay, there's a lot here. First of all, you talk about Gotham and Foundry. I know that we'll link to videos of people checking these out, but just what's the simplest way to understand what these two products do?

Nabil Qureshi:Yep, so Gotham is optimized for military and defense use cases and intel as well. I would say they both have some things in common, right? So they both have, I would describe this almost as a pyramid where the bottom layer is data ingestion, the middle layer is data mapping, and then the top layer is anything that's user facing, so any UI component. And then if you think of Foundry for a second, there's different tools that allow you to ingest data to it, there's different tools that allow you to easily build data pipelines and clean up data which everybody has to do, and then there's a bunch of tooling that allows you to build compelling UIs on top, point and click analytics, do notebook style workflows, whichever kind, however you are. And so that's what I mean when it's a platform, it's a suite of things that has kind of a common data backing but contains a bunch of different applications. And so I think that is somewhat true of Gotham as well, but you kind of when you log in you see this unified interface, right? So what is the actual difference then? I would say with Gotham you're looking much more at workflows that involve maps, for example, right? So when you're doing a military operation a lot of the time you are going to be looking at a map and you are going to be monitoring, you know, the movement of troops or tanks or whatever it is. Another big difference is the idea of graph based analysis. So Gotham, one of the kind of early use cases, right, was finding, combing through networks of terrorists and basically finding the bad guys. And so being able to do queries that are sort of graph based was important, right? So it's like who is everybody that Lenny called in the last week, imagine like all the nodes kind of fanning out from there, and then it's like okay, well this one looks interesting, let's zoom in on that, what is this person's location, right? And so it's just like very graph based way of thinking that also applies to things like fraud. And so Gotham has been deployed against fraud, but if you look at Foundry it doesn't actually emphasize that component so much because it turns out, you know, let's say you're a B to B SaaS company, you're probably not doing that much graph based analysis, you're doing things that look a lot more like classic SQL queries, tables, that kind of stuff. And so Foundry's a lot more kind of traditional in that way.

Lenny Rachitsky:That was an amazing explanation. I for the first time, I'm starting to understand what these products do. Basically just sucks in a bunch of data, cleans it up so you can actually trust it, and then helps you interact with it in various use cases, maps, graphs, tables.

Nabil Qureshi:Yes.

Lenny Rachitsky:Okay, amazing. The example you gave of what you worked on at Airbus, you described it as basically Asana for making planes, is that right?

Nabil Qureshi:Yes, yes.

Lenny Rachitsky:Yes. So how much of that does become like a part of this core product versus stays this one off thing? Like is it elements, oh that's a cool innovation, let's put that into Foundry. How does that work?

Nabil Qureshi:This was a really interesting story actually. So the initial problem that we came into with Airbus was that they had a new aircraft called the A350, beautiful aircraft by the way, if you get to, I think if you fly New York to Singapore it's often an A350, really nice. And so it was a really relatively new aircraft at the time and their mandate to us was okay, we need to ramp up production of this really fast, much faster than we've ever done it before. So it's like the numbers are very approximate, right? But it's like okay, we're producing four this month, we need to do eight the next month, 16 the month after, and so forth, and you're gonna help us do it. And so this goes back to what I was saying earlier is the mandate wasn't like hey, we need to our data infrastructure, we thought you guys would be met met the list of requirements, it was much more just like help us accomplish this mission, this is like the big thing. And so we went in scoped out the problem, there were a bunch of different things that we could build that helped accelerate this, but one of the basic problems that we figured out was that without getting too much into the weeds, the way the factory would work is that there's a bunch of stations and you can think of the plane as literally moving between each station and then each station would do a certain set of work on it, right? So initially it's literally like a big fuselage and the fuselage is sitting there and then people are doing a bunch of work orders against it, they need parts in order to do that work. And then at some point they say okay this is ready to move to station 31 and the plane is physically moved to the next station and then station 31 does its next thing. So in order for the next station to do its work properly need to know one, what work was done at the previous station and what work is remaining. Two, if you think about this problem, not all work is going to get done on time, so things kind of carry over to the next team and the next team then has to kind of like, and so when I'm describing this problem to you you can kind of start to visualize like okay maybe I need some sort of Gantt chart for this and I need the ability to click in and say okay what did actually what did station thirty do and what work orders remain undone and then it's like for those work orders what parts do I need and where in the factory might they be. And so this was very very hard to do as it is, a lot of it was just relying on people going and having conversations with other people on the factory floor. And coming from tech where it's maybe not as complicated as building aircraft, that is a phenomenally complicated process, but it is easy to see like okay you can actually improve this problem with software, right? All that data was stored in SAP and SAP is like established software, it's good at what it does but it's not the most user friendly especially if you're not an expert in how it stores data. The table names are very hard to understand and read. And so one of the things we figured out was just if you can pull in these tables that may as well be written in completely alien language like the table name would just be like s three f one underscore z or something like that, right? And you'd have to know like okay this is the table where the part id is stored or something. If you could pull in those tables and join them in the right ways and then just map them to human concepts that humans can understand, so things like a part, a work order, an aircraft, etcetera, and basically build a kind of hierarchy or mapping between them, then what you can do is for a user, a user can just log in and say okay aircraft 79 where is that? Okay it's at station 31, these are the work orders, etcetera. So you've translated it into a more human legible thing. And so the thing we built, I mean I kind of slightly flippantly described it as Asana, it's a little different but basically that's what it did was it gave you a unified view of okay this is what's going on inside the factory, this is the work that needs to be done on this particular plane, and then me today going to my job at station 31 what work orders do I need to fulfill and where are the parts that I need to do that. And so did this directly become a part of Foundry? Not exactly, because the way that other companies work is not going to be using this same set of concepts but the overall idea of taking a bunch of tables and then mapping them to human understandable concepts was a very powerful one. And so this actually resulted in a big piece of Foundry now which they call ontology. You've probably heard this term as you've seen if you see Palantir presentations they always talk about ontology. This is what they actually mean by that is it is a set of concepts that is understandable to you as a human and you're not having to go and dig around and do SQL queries, you're just able to say where is the aircraft now and where is it going next. So the ontology became a huge piece of Foundry. It was directly informed by the learnings that we had from building that application inside that factory and I would say it's still a very big differentiator today like I don't think too many other companies ship this kind of stuff yet.

Lenny Rachitsky:Wow, I love how excited you still are about this because I could see it being so fulfilling to solve this big problem. I thought I saw a stat that I think you've forexed their productivity. What was the number there?

Nabil Qureshi:It was, yeah, I don't recall the exact stat but we did ramp up production I think at least four X that one year which I mean obviously they did a lot and we just helped with it but you know their CEO said that we played a critical part so.

Lenny Rachitsky:Also so you moved to France I think for this that was like how forward deployed you were you lived in France for how long

Nabil Qureshi:Yeah I lived in France for about a year and a half the way they built their planes is they manufactured different components around Europe so they built you know the tail in Spain and the fuselage in part of the UK and Germany and so forth right and so they basically ship everything to France to be assembled at the end which you can imagine this is a very messy process and so I was mostly in France but there would be weeks where I'd have to kind of fly between all these countries just to kind of figure out where things were

Lenny Rachitsky:In your post you wrote about how just the life of forward deployed engineer is pretty crazy you just get a call sometimes like hey you're flying to this random country tomorrow get get ready is that just life as a forward deployed engineer

Nabil Qureshi:It is yeah the the company had a very I would say aggressive attitude towards travel in the sense of when you join you were basically told look you have to be okay with travel are you okay with that right and the attitude which again I think is a very founder friendly one is you need to be willing to just jump on a plane that night if that's the best thing to do for this customer and if it's gonna get us to where it needs to be to win and so there are many times when it would be like oh I need to take this cross continental flight tomorrow for this particular thing because it will be it will be useful right and so I think that's one of the kind of takeaways for me was just like being in person is so so so valuable when you are working with some external party just going there for a for a few days and spending time with them maybe going out for dinner you build so much more trust than if you're trying to close a customer over zoom or do an engagement over zoom it's just the vibe is completely different and so yeah getting on a plane was a really cool part of our job for a very long time this obviously changed around 2020 because covid happened the company IPOed and so there needs be to a bit more internal controls around this but I would say pre 2020 this is like a very big part of the culture

Lenny Rachitsky:I'm excited to have Andrew Luo joining us today Andrew is CEO of OneSchema one of our longtime podcast sponsors welcome Andrew thanks for having me Lenny great to be here so what is new with OneSchema I know that you work with some of my favorite companies like Ramp and Vanza and Watershed I heard you guys launched a new data intake product that automates the hours of manual work that teams spend importing and mapping and integrating CSV and Excel files yes so we just launched the two point

Andrew Luo:O of OneSchema FileFeeds we have rebuilt it from the ground up with AI we saw so many customers coming to us with teams of data engineers that struggled with the manual work required to clean messy spreadsheets FileFeeds two point O allows nontechnical teams to automate the process of transforming CSV and Excel files with just a simple prompt we support all of the trickiest file integrations SFTP S3 and even email

Lenny Rachitsky:I can tell you that if my team had to build integrations like this how nice would it be to take this off our roadmap

Andrew Luo:And instead use something like OneSchema absolutely Lenny we've heard so many horror stories of outages from even just a single bad record in transactions employee files purchase orders you name it debugging these issues is often like finding a needle in a haystack OneSchema stops any bad data from entering your system and automatically validates your files generating error reports with the exact issues in all bad files

Lenny Rachitsky:I know that importing incorrect data can cause all kinds of pain for your customers and quickly lose their trust Andrew thank you so much for joining me if you wanna learn more head on over to 1schema.co that's 1schema.co there's a lot of founders listening to this and a question that I'm thinking and they're probably thinking and there's kinda two questions here one is just when to go like how hardcore to go potentially with their own forward deployed sort of operation and then two is just how and a company I know is actually doing this how far to go with one company's problem and invest in just like we're gonna nail solving this one customer's problem with the hope that this is something we can abstract and sell as a big platform so let me let me start there and you're you know you're building a company any just I guess insights or advice on just how far to go down this road of we'll solve customer one's problem and we bet that this is gonna be a big opportunity for a lot of other companies

Nabil Qureshi:So I would say on the on the fully deployed piece my friend Barry McCartle who's the CEO of Hex the analytics company he wrote a really good post about this actually and his take was just like you probably don't need fully deployed engineers it's very specific but I I think basically the the thing there is you have to be willing to be quite almost wasteful like you have to be willing to invest a lot in finding the thing and for that you just need a certain ticket size right so you need each customer's revenue to be probably in the billions of dollars if it's below that you're probably not looking at a traditional forward deployed engineer motion it's something a little bit different and so you know I think one thesis that a lot of people left Palantir with and started companies around was there's a lot of customers that Palantir won't serve because you know maybe they're too small a ticket size and so actually you could go and do something like Palantir for those companies but instead of charging them $5,000,000 you're charging them $2.50 Ks a year and so in a scenario like that you might still have forward deployed engineers but they're not really they're not going to France and spending five days a week in a factory it's more like you'll have one person and they're looking after five different customer accounts it's more of that ratio in order to make the numbers work and so I think a lot of the principles can be abstracted from that experience but it is a really specific sales motion that depends on a specific way of doing business I think to your other question yeah I think it's obviously something that is very hard to give a general answer to my main thing here is just that you can definitely tell when you are just doing consulting and when you are closer to building a product and I think the error that people make more often than not is they are actually too stuck on their own product vision that's the mistake I've seen a little bit more actually than the other way around if you go to I'm trying to give an example if you go to an enterprise customer and let's say you think you're the analytics software and it turns out they don't actually care about internal analytics this much they actually have this other massive burning problem and they don't have a good solution to it yet I think a lot of people are unwilling to go and pivot to the big problem because they're like well we're analytics software and so maybe this customer is a fit for our thing and maybe that's the right call in some scenarios that is the right call you should go find a different customer where your thing resonates more in other scenarios it's actually the right call to pivot and go and just put everything on that big problem instead and then go and find other customers for that thing there's no hard and fast rule I remember reading a really interesting post by I think it was David Su from Retool who had this exact thing I think he worked at Palantir for a while too and and he said that they had the Retool product and it wasn't getting any traction at all and then he tried an outbound email campaign where he literally just changed the subject line to build internal tools easily and then suddenly they started getting all these replies from CTOs who were just like oh yeah this is actually a huge pain point for me but the exact same solution they were previously kind of framing it as I think it was like supercharged Excel or something like that and nobody was biting and so they just changed the way they framed it found a different set of buyers and succeeded that way so yeah no no hard and fast rule but I think it's always you need to kind of have this matrix of options in your mind and be very deliberate about which one you are going with and why

Lenny Rachitsky:I think your piece of advice is really important there usually in your experience you're saying people index too far to like no what they're asking you to do is not kinda what I think they need or what customers will need you're saying it's actually more likely if they're right and that's maybe where you should be focusing more versus this kind of abstract vision and original idea you had

Nabil Qureshi:I think so yeah I think it's very hard to not be anchored to your own experience and your conceptions as a problem and one thing I've seen in really strong founders is they're able to sort of drop a bunch of those assumptions and almost treat something a new opportunity as a completely blank slate and then just figure out how to reshape things so that you're taking advantage of that and that's how you don't get stuck in a local maximum

Lenny Rachitsky:Your other piece of advice is also really great so people hear this and they're like we don't we can't afford an engineer to sit at our one customer prospect's office and build stuff for them but your point is you can have one for five different customers they're not there full time they kinda bounce around but they're kind of it's almost like sales engineering like what do you call it sparkling sales where they help make it successful I know Looker is a famous example they think they call them forward deployed engineers do you know any other companies by the way that did some version of forward deployed engineers

Nabil Qureshi:There's a lot I mean I know that the AI labs are hiring forward deployed engineers now they're building forward deployed engineering teams and and you know they could they could make it work right but I think there's gonna be key differences right like I don't see Anthropic going into an enterprise customer and building some entirely from scratch solution for them it's going to be something that leverages the Anthropic set of products so there's a lot of companies that have this label now but I think what's really confusing about it is just that it means a few different things there's another post by Ted Mabry who's I think the head of commercial at Palantir and that's a very good one to point point this list to

Lenny Rachitsky:So so say someone was I wanna try this sort of thing in my company and what would be like a few bullet points of things they should get right you're describing kind of the spectrum of what people describe as forward deployed engineers if they were to try to do this what do you think they need to most do correctly for it to be successful

Nabil Qureshi:The key things that made our model work were one they were actually real engineers who could build product themselves that's a very big difference right I think a lot of the time companies will say this person's a forward deployed engineer but actually they're mostly there to be more of a solutions architect or they're not necessarily building anything de novo they're just listening and trying to find a way of deploying the existing product they're not empowered to do new product and so the really radical thing Palantir said was no like go in and if you need a completely new product to do this you can go ahead and build it and and I think that's really the key difference the other stuff you know I've already mentioned the value of being in person and I think building close personal bonds with your customers I do think the better founders do this anyway right like they're on texting terms with their buyers they become friends with them outside of work and they see them as humans who they're trying to help I think that's very motivating gaining a really deep understanding of the business that your customers are in and knowing how those dynamics work so you know a simple example might be you know like say hospitals in America right like I think if you go into it it's very counterintuitive to think of a hospital as a business people think of it as you know it's it's a place where you get health care right but actually like if you kind of view it the way a COO or CMO views it it's going to look very very different to you as a very simple example sorry this is a little bit dark but you know how kind of restaurants want to turn over tables as fast as possible in order to kind of maximize their revenue for the day hospitals actually kind of want to do the same with patients right they would like to treat you and then get you out of a bed so they can free up the bed to get a new person in there so that's not super intuitive unless you kind of think hard about how the revenue for that hospital works but then once you think about it you're like oh this has a bunch of problems associated with it right and you start to go in really interesting directions so

Lenny Rachitsky:There's just like the words and memes take you a long way working yes and understanding it okay so essentially the things you wanna get right make sure it's in person make sure the person is technical make sure they have a deep understanding of the business and the problems they're having the technical piece is interesting with AI tools these days and making everyone technical in some sense you could argue this is gonna become more common people can just you know open up cursor windsurf and just start adding features

Nabil Qureshi:I think this is a really interesting thesis you've just hit on and I expect to see a lot more startups that take advantage of that insight

Lenny Rachitsky:Basically it makes forward deploying engineers cheaper exactly what is the current state of forward deploy engineers at Palantir like how much has it changed over the past few years like if you join now is this still something you can do

Nabil Qureshi:Yeah of course I mean I should I should obviously emphasize that one I left the company in 2023 and so this is just my personal view I don't speak for them I think that you know if you think about it right the the thing that one of the kind of metrics that the company had to measure its own success was essentially revenue per engineer right and so the more kind of product leverage you had the higher that number was so if you had to throw a lot of people at every marginal problem then you weren't doing so well at that because you're basically building a new thing every single time and you are in fact a consulting business if on the other hand every time you encounter a new customer the product turns out to be kind of relevant to them then then great and so this product leverage metric was actually a very unique thing and kind of a north star for the company for the whole time I was there if you reason that out what that means is that in the early stage of the company you will have a customer and then you might have five to 10 engineers working at that customer right and so over time you want that ratio to change so you want it to be you know each customer because the product is so powerful maybe AI coding's gotten a lot better each customer you only need two people and then maybe you actually get to a point where you can have one person looking after multiple customers and I I think that's how the job has changed is now it's a little bit more about you have multiple customers maybe you're spending less like deep time with each individual one of them but it's a lot clearer what problem you're solving across multiple customers and you have more of a kind of defined offering and so I do think that has been a bit of a change but the company remains a very interesting and dynamic place to be in some sense the story is already starting right because one one lens through which you can view this company is they spent twenty years basically building the mother of all data foundations for every institution in the world guess what's very valuable now that AI models are out is proprietary data that isn't public suddenly you have access to that and you are in a very privileged position to help your customers deploy AI in a way that makes them successful and that solves real business problems that is essentially the bull thesis for this company and why it's probably going to 100x again right and so it's still a really interesting time to join but I do think the kind of nature of the ratio of people to a customer for example is one big difference now

Lenny Rachitsky:Not investment advice but it might a 100 x that's I totally understand why that might happen so let's talk about the data piece you said that this might this was one of the secrets of Palantir's success there's early insight into the the power of ingesting data cleaning data being able to analyze and work with it what what more can you share there just like what they figured out about why this is so valuable why it's so hard and how they achieved it

Nabil Qureshi:I think it's just very obvious as soon as you step into a corporation and spend a couple of days there right as you're like alright like let's suppose your job is to increase sales okay so the first thing you wanna do is get a clear picture of what's going on alright so like let me go and query the sales database oh wait where is the sales database I can't get access to this okay I need to file an access ticket alright now I have to wait one week right and so every everywhere we went this was the big pain point was we have to wait six to eight weeks just to get data access and then when you do get data access it's not like the data is in an easily queryable format you actually really have to know what you're doing in order to get the right metrics out and so on and so forth and so it turned out like okay it's this iceberg analogy where the actual analysis is actually just the tip of the iceberg it's kind of the last five or 10% and the 95% before that is I am gaining access to the data I am cleaning the data I'm joining the data I'm normalizing it putting it all in the same format and so once once we spotted that then it's like okay there's actually a lot of product to be built there just to make that process easier this is one way I think Palantir does people don't think of Palantir as this place where innovative new products and UX ideas come out but I actually think it's been one of the most generative companies for that specifically in the last twenty years it's just that most of that didn't see the light of day and so people don't know but if you look at the product primitives that they developed in order to make the things I just mentioned a lot easier they're actually really valuable and interesting and could probably form the basis of independent companies themselves and so it just took every single step of that process became much much easier once there was a software solution around it so if you talk about data ingestion there's essentially a kind of universal data adapter that's part of Foundry it can read anything so JDBC S3 buckets whatever you want and it can pull that it allows you to kind of look into the data maybe preview the first 20 rows and then it allows you when you're ready to set up a schedule and just pull it in on some cadence that process alone for an engineer takes used to take a long time especially pre vibe coding and managing all those cron jobs and doing this on a Linux VM somewhere inside the customer's tenant was a huge pain right and so you productize that piece then it's like okay once you have the data it's like how do you actually join it what if you're non technical is there a way for a non technical user to be able to join tables and see what the result is and so there's all these very fascinating business problems that because I think the access was very difficult to get and people hadn't really solved before and so there was a lot of white space to do some product innovation so now I would say Foundry is definitely the best data platform in the world just because it has all these different applications within it that solve these discrete parts and it's just it came out of this years of painful experience watching people have to clean data and join it and figure out what this table name meant and so on and so forth

Lenny Rachitsky:You shared in your post this kind of evocative story of some people's jobs is just to kinda gatekeep the data like they're the they're there to help you to give you access to this very valuable data within the organization and how hard it is to get like that was a lot of this work is just breaking through those political battles of like okay we need this data for the good of the company and took a lot of work I guess anything there you wanna add

Nabil Qureshi:It is yeah I mean it's it's a it's a huge pain and there are good reasons for it right like it's not like folks are malicious here it's it's if you're IT or if you're a info sec type person then your goal is to prevent data breaches and to make sure that sensitive information doesn't spread too wide so what's the easiest way to do that is to lock the data down and basically be a gatekeeper for access right I think where it got a little bit more interesting was where your skills are valuable and depend on you being the gatekeeper so what I mean by that is like let's say I'm the guy who I'm the only guy who understands the way the sales calculation pipeline works right and I write the sequel for it all the requests from business SMEs come to me I have a big queue of them it takes me weeks to get through this queue I have a great job I have great job security and people depend on me so now along comes this company and they're like hey actually we want to make sales data available to everyone and we want make it point and click suddenly you're like hey hang on what am I going to do and so that's where I think there was a lot of difficulty I always say people are like what are Palantir's competitors I don't think it's the ones you would think of necessarily Palantir's biggest competitor is a company rolling its own solution right and so the biggest difference would just be a CIO saying I'm going to build my own data infrastructure I'm going to own it it's going be on top of one of the hyperscalers and we're all just going to do our own analytics ourselves and what we came along with which was quite disruptive to this model was saying no actually all your data is going to get ingested into this one platform and everybody in your company is going to use it the trade off is it's going to be really really easy for everyone to do things but as you can imagine some people weren't a huge fan of that model so

Lenny Rachitsky:Feels like Glean is the biggest competitor to Palantir after I hear this do you know about that company

Nabil Qureshi:I do yeah Glean is Glean looks amazing from the outside I mean you know so many so many differences there right I can totally see why you would stay this but clearly a different use case but

Lenny Rachitsky:But it feels like the reason they've been successful is they figured out a lot of this data ingestion permissions search stuff and I thought of it that way interesting okay I wanna talk about hiring you talked a bit about this you're starting a company again what are some of the kind of the key lessons you've learned from your time at Palantir when you are hiring people for your company I don't know if you're actually hiring people yet maybe when you may start hiring

Nabil Qureshi:Yeah we have six people at the moment so a reasonably small team you know I think with hiring it's funny man like there's so much hiring advice online and you read it and you're like yeah this is super obvious and then when you live it you're suddenly like ah this is why people say this right so a few simple examples are I think the thing that is really hard to find is somebody who really really cares a lot about doing the thing and will go that kind of extra 20% like I think I think when you hire out of especially not to pick on them I I think if you hire out a fan right it's like people want like a 400 K a year job they would like to work a certain number of hours they would like to ship some code and then go home like that's basically the model that you get accustomed to even if you don't intend to when you work at a big company and so if you hire out of that for a really small startup it can be really challenging because a lot of your success as a startup depends on each individual person being like no I'm gonna I'm gonna work this evening if that's what it takes to get this thing working I'm not just gonna check my boxes I'm actually gonna look towards what is the real outcome that this business is trying to achieve and everything I'm saying is feels kind of obvious but when you actually feel that difference between somebody who's just checking the boxes and somebody who's kind of an animal in this way like they'll actually go and pursue and accomplish the end outcome that difference is very very big and it matters so much for your first 20 people right and there's no science to finding these people it's not like you can just put like somebody who cares about outcomes in your JD and suddenly then you'll get all these people applying and so then it's like okay well how do you screen for that and how do you find those types of people and so that's where it gets really interesting I think that's where the mission alignment comes in and so you do have to find people who for what you're doing have this extra maybe private reason to care about it a little bit more than the average person right so I think for Palantir they did hire a lot of vets for example or maybe people who were a little bit more patriotic or pro America than the average tech employee and that those people had an extra reason to join Palantir and an extra reason to try that little bit harder and so you know what I'm doing is a little bit more in the kind of medical and health space and so I think people who have themselves had experiences with this system have maybe had relatives go through difficult experiences with things like cancer or whatever it is they're just that extra bit motivated to really care about the thing you're trying to do and then work that little bit harder and so I think aggressively filtering early on to things like mission fit how much have you cared about stuff in the past what's an example you know you ask questions like what's the hardest you've ever worked to get something done and why right and that like does differentiate a lot of people a lot of people don't actually have a great answer to that so I would say that's been a really big learning it's less about testing for the right skills yes that's important two it's much more about just like who has that extra 20%

Lenny Rachitsky:That is really interesting as you just said it's what all everything you've shared is essentially around motivation and drive and passion and kind of just like commitment to working on this intently and you almost like it's almost like a second thought of just oh so they're like really smart and skilled at stuff like it feels like that's just table stakes and this is actually what makes the difference in your experience

Nabil Qureshi:Yeah I totally agree and I think it's it's different for every business right so I think if you're in a space like B to B SaaS where maybe it's a little harder to tell the story of like oh this is so mission critical like whatever there are other ways of getting at this thing right for example I know I know a lot of people again it's little played out now but I know a lot of people who for sales teams will explicitly go for people who are professional athletes or played sports in college right and it's like okay what does that test for it's like you are very very disciplined you're very very goals and numbers oriented and you're willing to just work really really hard and so there's all these kind of lateral ways of getting at these qualities that I think you just have to be kind of intentional about as founder as a personal example I'm a runner and so I actually love meeting fellow runners and I always like to I kind of joke like oh maybe I'll go higher from run clubs or something like that it's just like same with you know I play a lot of chess I love meeting chess players I'm not necessarily saying that's the right kind of hire for me but I think having this this thing of here are some traits that seem uncorrelated but which actually give you good signal to this person's personality those are actually really important the last thing I'll say just as a funny illustration of that concept is I think Max Levchin tells the story of somebody interviewing at PayPal early on and he passed all the skill interviews and then it just to the final round and he said something about liking to shoot hoops like he liked to play basketball and they were like instant rejects and it was just like the the the vibe here was just like if you're not like a mega you know Linux nerd hardcore computer person then we don't want you here even if you actually passed all the tests just because you like to shoot hoots now whether that was the right call or the wrong call I don't know but that's an example of what I'm talking about

Lenny Rachitsky:I think that's like a great echo back like people hearing this may be like what the hell how that's like how like how dare they do that but this is exactly what you said at the beginning of our conversation that if you're like an approach to building a generational business is to be very clear about who this is not for and that's okay it's your company not everyone needs to work there and it's almost saving them time because they may they they might realize this isn't for me this isn't the people I wanna be around necessarily so I think it's important to see that side of it it's like you it's your business it's important to be clear about who is a good fit for the company and who's not speaking of that let's talk about product management for a bit I know Palantir PMs are like not very not traditional product managers what what is like did I I imagine people have the title product manager Palantir okay so if so what as far as you understand how what's the difference between say a PM at Palantir versus a traditional PM say at a FANG company

Nabil Qureshi:Palantir was as far as I remember quite anti PM for a while and eventually we did need them because we just got more serious about productivity classic story

Lenny Rachitsky:Classic story classic story many companies

Nabil Qureshi:The big difference or one big difference I noticed was that they were extremely careful about only making people PMs who had first proven themselves out as forward deployed engineers you basically could not become a PM any other way so as an example when I mentioned earlier the thing that we built for the planefactory the person who was managing that deployment she later became the PM for Anthology and it was just because she'd kind of proven her method in the field and you know the reason for that's pretty simple right it's going to be someone who understands how customers work and has that customer empathy and it's gonna be someone who has this drive to get things done because that's what BD selected for I think the failure mode that they were very very averse to in in traditional PMs was this kind of Google Docs syndrome of like okay I'm gonna write my product requirement documents and I'm gonna kind of manage it in this like very sort of sane rational way I think so the company was really rigorous about that so basically PMs were almost always internal promotions and they always came from BD I'm not aware of a single case where we took somebody who was

Lenny Rachitsky:A PM at a place

Nabil Qureshi:Like Google which produces many excellent PMs and hired them successfully into Palantir just a very different vibe so I think that was one thing you know this is maybe more of a classic PM trait right but you just had to be either an engineer yourself or extremely good at working with engineers and the ones I saw who succeeded the most were just best friends with their engineering team right and the team would always just be like one you know was called the group PM and then it would be a lot of very very good engineers and basically the successful failure mode was just like do the engineers like and trust you and I mentioned before like Palantir very kind of almost disagreeable personalities and so if you didn't gain the trust of your engineering team pretty fast you didn't last very long

Lenny Rachitsky:I think we've cracked the problem the question of why are Palantir PM so successful first of all the hiring bar is just like basically hiring for leaders in a lot of different ways to this like I don't know forge for founders where they're working with a company solving a real problem building a real product that makes money and then those are the people that become the PMs at Palantir and that then they go on to leave and that's why 30% of them end up starting I'm surprised it's not higher or become first PMs at other companies or heads of product

Nabil Qureshi:Yeah absolutely I mean it's it's crazy I was part of a pretty small team within Palantir I think it was 20 to 25 people when I joined and I think at least six of them now are either unicorn or just pre unicorn founders from that like group of 25 people which is actually a crazy ratio and then a bunch more have become founders recently at an earlier stage yeah there's all these little pockets of excellence and it's been really interesting to see I think the other thing that's driving that a little bit is you know when you leave it's just such an interesting company to work at that you know I think the retention numbers were actually very high for that company like people would often stay a lot longer than maybe the average average valley tenure so when you left was really this decision of just like something very specific is pulling you and you wanna kind of play the next level of the game and so it was very unusual for someone to leave and then join maybe a more traditional tech company it's sort of like you're either going to go become a founder or why would you leave when there's so many interesting different things to work on here and I know that sounds a little cult y but that's just that's what everyone thinks

Lenny Rachitsky:I could totally see that a lot of people that left Airbnb have never found something more meaningful right it's just hard especially if you're early there's a stat that I didn't share that I think is really interesting and when you look at YC founders and their where they've come from I think you maybe shared in this in your post that there's more YC ex Palantir founders than there are ex Google founders in spite of Google being something like 50 times bigger sample size

Nabil Qureshi:Yeah yeah

Lenny Rachitsky:Let's talk about the the moral question of Palantir a lot of people probably seeing the title of this episode hearing this or will not be excited about Palantir being highlighted and promoted a lot of people kinda disagree with what Palantir is doing you know it builds products that kill people in some ways they work with governments they don't agree with I know you wrote a really insightful way of of how you approached this question when you decided to work at Palantir and how you see people tackle with this can you just talk about the kind of the framework that you landed on how you thought about this yourself

Nabil Qureshi:Yeah it's a really interesting topic it's definitely very nuanced I think what I was trying to say in that post was a couple of things one was that there was a lot of upside there right so you know I worked on the US COVID response I have friends who you know worked on Operation Warp Speed and these are all things that I think saved a lot of lives I was pretty focused while I was working at NIH on cancer research so to me are just obviously good things and you couldn't do them anywhere else so that was alone a reason to stay

Nabil Qureshi:Question I had in that post was well okay there are definitely going to be other pieces of this that people object to right so during the kind of 2016 to 2020 era it became a pretty common thing to go into work in New York and you'd have people protesting outside your office or you know doing all kinds of things and so there was this question of well is this okay and I think the point I was trying to make was I don't think that it's rare that disengagement is the correct answer and I think it's more recognized now but especially then it went a bit too far right so the famous example here is Google kind of disengaging with a Pentagon AI project just because some people felt that working with the Pentagon was itself morally bad I think that's way too of the left of what the median American would say I think the median American would say it's fine to work on defense stuff you know within reason and assuming you're doing largely good things and so there was just this kind of almost arbitrage there at some point of just like hang on it's not like working on defense is inherently evil it's a pretty interesting thing and then there's this question of well would you rather be in the room and making this better or not I'm struggling with how much I can share here but as a simple example if you're doing even a workflow which I think many people would not be super comfortable with like let's say you're targeting somebody for some kind of strike if you compare the way it's done now to maybe the way it was done in 2010 it's going to be a lot more targeted it's going be a lot more accurate and so you've actually improved that process and reduced the chance of error maybe you should feel good about that right now that is a bullet many people are not willing to bite I I didn't work on the defense side of the company myself but I think you have to be okay with these kinds of gray zones and actually actively thinking about what you are doing and that doesn't mean that it's always the right thing to do to work at a defense company right maybe we go into a very dark future and we start being the bad guys in some ways and then it's probably not a great idea to work at a defense company right so it's a shifting landscape but I think I kind of felt pretty strongly that a lot of people in tech just didn't want to think about this at all you have engineers now who are working on optimizing short form videos for higher engagement and you sort of want to say to them like hey are you thinking about what this is doing to the brains of young children or have you seen you know an 11 year old kind of scrolling something for five hours and do you think this is a good thing and I think people don't want to think about this stuff too much I'm not saying I know the answer but there was almost this refusal to look at what tech was doing from a political lens for a very long time it was just like hey let us play with our toys let us sit in Menlo Park and like don't bother us and we're just gonna build cool stuff and launch it and 2025 we're in a very very different state of the world right you know tech is involved in politics now and politics basically came to tech right there's this famous image of Mark Zuckerberg sitting in Congress and he kinda looks very pale and he's like why why have they dragged me in here again right but I think I think tech went through this journey of oh we're suddenly becoming important now oh we're really really important now oh we better stop playing this game of politics and so I think what I'm saying now is a lot more consensus than it was ten years ago but at the time the feeling was just like look what we are doing is political so you better engage with that

Lenny Rachitsky:I think when this became really real for a lot of people is with the Ukraine war like the governments running out of certain vehicles and and ammunition were just like not able to produce it and then we're like oh thank god for a company like Anduril and all these other tech companies that are actually ahead and keeping us ahead like I think the only reason the US is ahead of the of China in the space race is because SpaceX just is the one company that just has been doing this for a long time so I think a lot of people have kinda realized okay maybe maybe we need these things

Nabil Qureshi:Right yeah and I I would make this argument as well it's like people are like well you know how can you feel good about working in defense and it's like well you're not gonna feel great if China invades Taiwan actually you're not gonna I I I think you're probably also not gonna like that outcome so we do just live in this world where you do need to build up deterrence to these things and they better be good so to me it didn't feel that difficult of a question I think when you zoom into particular things they can be very difficult questions and there have been a bunch of those in the last couple of years but yeah again disengagement isn't the answer

Lenny Rachitsky:Yeah and it's not for everyone I think that's an important kind of theme through this conversation is some companies like to build sometimes to build a generational really successful company it's need to turn some people off because that's what brings in the best talent oftentimes okay just a few more questions kind of like stepping back a little bit you're building a company again what are what are kind of like a few core pieces of advice that you're bringing to your new start up that will inform how you build this company from your experience at Palantir we talked about a lot of stuff is there anything I don't know if there are like three things that you think are like I'm definitely gonna do these things this way because it worked really well at Palantir

Nabil Qureshi:One thing is probably just really fast iteration cycles so placing a lot of bets and then being really rigorous about just going through that cycle very soon I have this article principles that one of the things on there is basically saying like your p successes goes up the bold bets you make it's sort of a function of how many bets you make and the probability of success of those individual bets right and so one easy way to almost guarantee that you'll hit something is just to make a lot of bets and then just kind of like cycle through them very quickly now obviously this is difficult there's often this question of well is this bet actually failing or like are we quitting too soon kind of thing but that's that's kind of one principle I take is just test this thing very early you know like the classic y c y c thing is just when you take something to a customer ask them to pay you a lot of money and if they say no then find a new problem like don't don't wait three weeks which is what every founding team typically does because you don't have that kind of time I do think the importance of just having a really tight distinctive internal culture and building a strong feeling of trust within a team is really important and kind of like you mentioned with Airbnb and you know people definitely felt this at Palantir there was this feeling of like well you worked here you must be good I trust you and all of that and I think it's so important to create that and you kind of know that feeling that's what like people ask me you know should I go work at place x or should I just go be a founder straight away I don't know the answer for everyone but I will say one of the benefits of working at a place like that is you just have all these internal benchmarks now for okay this is what this should feel like and if it doesn't feel like that we're off and I can't imagine not having those benchmarks and just kind of having to figure it out so yeah I think that thing two is just like distinctive internal strong team culture and then I think I think for me think three is just like working with a really messy part of the real world so you know I kind of joked when I left like excited I'm to just do pure software I'm excited to I don't know I want to build an IDE or something and just like not have a support email even and all of that but it turned out like my look my comparative advantage in a lot of ways was you know the networks I'd built and the experience I'd had in engaging with the messy parts of the world and they do need technology a lot right like there is this horrifying thought I have sometimes of just like maybe we'll get ATI in the next two years and you know the healthcare sector will still be broken and it will still be impossible to afford rent in New York City and build houses and all these things and that may well become true and so I think it's important to engage with those parts of the world too even though they're really really challenging and I think the really nice thing about LLMs is that actually there's so many workflows now that are accessible to you as a tech founder and people are somehow more open to working with tech companies than they ever were before selling into the sectors of the economy in 2015 incredibly hard I think now post the chat GPT moment people are willing to give chances to small startups that they weren't willing to do previously as you mentioned earlier the cost of doing things like forward deployed engineering has fallen by maybe five to 10 x now at least and so there's a lot of new possibilities I'm excited to engage with the best

Lenny Rachitsky:Wow that is some alpha right there that you're finding that some of these very large organizations are more open to working with startups because you know classically investors don't wanna invest in companies that are going after health care companies and governments and things like that so it is really interesting actually to hear I'm gonna mirror back the tips you just shared and there's actually like a secondary tip that I think is the more interesting piece so the first thing you're taking away is iterate quickly but I love your tip of ask for lots of money quickly early to see if it's an actual idea that people will pay lots of money for and if not move on I love that the other is build a very distinct culture but the piece you share there that I love even more is this idea of knowing what a high bar looks like knowing what awesome a plus people look like and you need to work at a company like Palantir to actually see that so the advice there I feel is they're just like work at a company that is amazing first with the best talent to understand what that should look like plus you build a network of those folks so I think that's really interesting and then the other pieces of advice you're pulling away is work on like really hard messy problems because that's where the biggest opportunities are and it's sounding like this is the easiest time to actually do that amazing okay I'm gonna take us to a recurring theme on this podcast called AI corner and what we do in AI corner is is we share some way that you and this is you sharing some way that you've found AI to be useful in your day day to day either in life or in work is there any way you found some tool some AI tool useful that you can share

Nabil Qureshi:Oh my gosh there are so many I'll give you a few examples so I use WhisperFlow quite a bit so this is the talk to your keyboard and it will transcribe for you PAP very good it's just great when you're iterating very quickly with an LLM and you sometimes you have to do these paragraph long prompts and it's just easier to speak into them right so with the flow I like

Lenny Rachitsky:Just to double down on that there's like it's like you press a button and you start talking and it's yeah writing out what you're saying I cool and they're like there have been these products for a long time Dragon Dictate and all these guys is the difference now these are just like very very good now at actually transcribing what you're saying

Nabil Qureshi:I think that's right yeah the the you know they use they use a really good model and so it rarely makes mistakes even when I think it's quite challenging and then yeah the UX I think they just nailed so that's a really good one I love Claude code for developing even though I have my complaints about it there's something just very addictive about just telling it what to do and it can it's basically something that you run within the terminal of your computer and so you just type Claude it opens up Claude interface it's very cute it's very beautifully designed and you just tell it what to do and it actually operates on the file system directly so if you're like hey create a bunch of these files that'll just do it and you don't need to go and muck around inside Finder yourself and then it'll do these really complicated pull requests and it'll basically execute them quite well so to me this is like a very exciting kind of preview of AI agents

Lenny Rachitsky:That's what I was gonna ask so this is essentially like an AI agent engineer I didn't know that's what Clotco did very cool

Nabil Qureshi:Yeah yeah yeah it's it's sort of a guided agent but yeah it's it is really sweet and then yeah I'm I'm just enjoying you know every week there's like a new wonderful new thing to play with last seven days I've been testing Gemini Pro 2.5 excellent model I don't love Google's UX sometimes but I was playing with that and I use LLNs every day for all kinds of things the other day I was doing taxes and I needed to classify a bunch of transactions based on some metadata and so I just wrote a script up really quickly and it did that so

Lenny Rachitsky:I love just like the smile on your face as you're describing all these AI tools I think a lot of people are just like holy shit I'm overwhelmed with all the things I need to be paying attention to all these things in here all these tools I gotta try and I love just this vibe of just like this is incredible and so fun we need more of that okay I'm gonna take us to another recurring segment on the podcast you're gonna get a double whammy contrarian corner so here's the question what's something that you believe that most other people don't

Nabil Qureshi:I think going to college is great I think this is a somewhat contrarian view within tech maybe not in the broader economy but you know I often see people saying just like oh if you can just drop out when you're 18 and just stop working why would you go to college and I think this is completely wrong but maybe it's good advice for 5% of the population who probably would have been to your fellows anyway but college is one of the few times when you can just make really really deep friendships you are in typically a nice campus if you're in North America you get to spend all of your time just thinking and writing papers and reading books and hanging out with your friends it's actually very precious and it's very hard to find that kind of time after you turn 21 because you know you got to pay your rent you got to work you got to do all this stuff even you know let's say you make

Lenny Rachitsky:A bunch of money

Nabil Qureshi:You take a career break it's still like all your friends are working and you always feel like there's a ticking timer on top of your head or something and so just taking those three or four years at the very beginning and going really deep on lots of different intellectual topics and being able to try different things and discover more about yourself I'm a big college fan I can't comment on the ROI or whatever I personally think the ROI is great even though the fees are kind of high in the US but that's probably my kind of contrarian within tech view is don't drop out of college unless you have a really good reason.

Lenny Rachitsky:It's so funny that that is contrarian and it does sound contrarian I had a great time in college here here okay is there anything else Nabil that you wanted to share or leave listeners with before we get to our very exciting lightning round?

Nabil Qureshi:No I think it's just it's it's a really exciting time in the world right you know I think AI can be interesting but it does really just open up the possibility of building a better world in all these ways and so I think just reassess what you're doing every couple of months and make sure that it's aligned with where I think AI is going and make sure that you are working on something that you feel has very high potential if it succeeds and I think that's more important than ever now just because the amount of leverage we have with technology is at the highest point in history.

Lenny Rachitsky:Let me double click on that real quick so for people that want to do what you're describing what helps you understand where AI is heading and just kind of like align with it is there are there like places of information and news you find useful is it just play with it kind of thing what what would you recommend?

Nabil Qureshi:This is the big question I use X a lot to keep on top of AI so I just recommend finding a good Twitter list and maybe following people off of that there's some good newsletters so I really like Latent Space I know his X handle it's Swyx S W Y X I can't remember his actual name but that one is very good and it's pretty technical I would recommend trying to stick to the more technical newsletters if possible like I think there's a lot of kind of philosophy about AI or like AI policy type stuff and I think that's good if that's your area but you know it's an area where it's very easy to have a lot of takes on it you're not necessarily learning a lot by reading those but I think it's just important to know what's going on and make sure you are revisiting your own workflows as often as possible and just making sure that like the people who went here are going to be the kind of hybrid cyborgs who fuse with the AIs right this actually played out in chess I can take a slight detour chess players who succeeded the most in the mid-2010s especially were the ones who were really early adopters of neural network based chess engines so when you know DeepMind did their thing there was very quickly an open source version of it called Leela and you find basically like the very top players like Magnus Carlsen Fabiano they they were the ones who kind of mind melded the most with Leela and learned how it played and then kind of started copying its moves and so I think this like becoming a cyborg to the extent that you can and then I think there's this barbell thing of like it's also important to just leave everything and go touch grass just for your own mental mental sanity.

Lenny Rachitsky:Excellent advice and with that Nabil we've reached our very exciting lightning round are you ready yes here we go what are two or three books that you find yourself recommending most to other people?

Nabil Qureshi:The first one that comes to mind is Emperor by Keith Johnston this is actually I wrote about it in that essay it's one of the books that Pauwatay used to send to people I just think it's a really interesting book so nominally speaking it's about improvisational theatre which I believe this guy was a pioneer of he was a British guy Keith Johnstone active between the 60s and the 80s I think Impro is just this really interesting book about creativity and how social behavior works and basically just what he taught his improv students it's a very weird book it's full of these unbelievably strange ideas like there's a lot of very tactical things he tells you to do in the first chapter for example just to break out of your own mental frameworks like really just wild stuff like he'll tell you to walk backwards while counting down from a 100 and like think about some problem that you're struggling with there's all these kind of odd things but the number of ideas per page I've found on that book is extremely high the concepts about how social interaction works and how things like status and so on play into your social behavior are super important and they made every kind of fully deployed engineer read that for the simple reason that I think it just helps you kind of read people better and interact with them better and become more conscious of how you are coming across and just modulate that.

Lenny Rachitsky:What is the title again Impro?

Nabil Qureshi:Impro is number one I think just to go a little more highbrow maybe Shakespeare's history plays there's a set of them called Henriads so like Henry IV Henry V Henry VI I find most people don't read these so you know they'll read Hamlet or Macbeth or whatever but the Henriad is absolutely incredible you don't have to be interested in British monarchy or British history in order to enjoy them they're actually some of the most interesting and insightful books I've read about power and how power works and politics and kind of what the sacrifices that you might have to make if you want to be you know a successful king in that case but it transfers over I think it just it it's worth thinking really hard about I think especially in a world where everything is kind of organized around these prominent figures and personalities now right like when you think about the current administration you think Trump Elon or like when you think about AI you think of Sam Dario right and so I think it's important to understand like how do you think about these personalities and yeah the kind of game that they're playing at Henry is actually the Henriad is an incredible kind of set of books around that they're also like easy to read which sounds hilarious when I say it but you can read a Shakespeare play in a day they're they're sort of I don't know they're like 50 pages long it's not that bad so you you have to get used to the language yes but I I would recommend that for sure I guess you asked for two to three I love High Output Management by Andy Grove I just think that's a great business book and people sort of tend to read summaries of it on the internet more than they actually read the book but the actual book has a lot of really interesting stories and explanations about like I I think the most powerful thing about that book is actually how Andy Grove thinks unless any of the specific tactics there and I think you don't get that unless you read like how he came up with all these things.

Lenny Rachitsky:Your first two books were extremely out there versus what other people have recommended and the third book was the most recommended book on this podcast so I love that spectrum that we just went on perfect okay next question do you have a favorite recent movie or TV show that you've just really enjoyed?

Nabil Qureshi:The last movie I really loved was Decision to Leave it's a Korean movie it's by the director of Old Boy which maybe some people have heard of it's a great movie I think I think it was released a couple years ago and the basic premise is there's a detective who is investigating a woman who's accused of killing her husband and he gradually starts falling for her which starts to affect his judgment all these ways just like a really fascinating kind of psychological thriller with a sort of romantic element to it visually beautiful yeah I think a lot of the most interesting movies nowadays come from abroad actually so East Asia South Asia places like that TV I don't watch so much yet it's been a while.

Lenny Rachitsky:Totally understandable for a founder okay next question do you have a favorite product that you've recently discovered that you just really love it could be an app it could be some physical it could be a water bottle?

Nabil Qureshi:I don't have a good answer to that one I guess I didn't buy enough stuff.

Lenny Rachitsky:Yeah fully acceptable there's no wrong answers in the lightning round moving on do you have a favorite life motto that you often find useful in work or in life that you share with your that you come back to that you share with friends or family?

Nabil Qureshi:So so there's this architect called Christopher Alexander who wrote these beautiful books that are about you know beauty and kind of more than architecture right and he he was a teacher at UC Berkeley and he got really frustrated with his students because he just felt like they were always turning in kind of like average work and so he would always tell them every week like the there's a gothic cathedral in France called Chartres and he would say you have to aim for Chartres like you have to make something that is better than that that should be your goal not just to like turn in something that's that's sort of you know what you feel is good enough you actually have to try and be better than the very very best that ever did it and I find myself just like repeating this a lot to myself it's just like aim for aim for that like really try and do that otherwise it's very easy to anchor on something right in the middle and you just you do this unconsciously all the time

Lenny Rachitsky:So is that the is that the motto just aim for charge

Nabil Qureshi:Yeah yeah

Lenny Rachitsky:Yeah I love that most people have no idea what that would be but with the context it's quite powerful final question what's a classic novel that would you think would be most valuable for product builders

Nabil Qureshi:I just my favorite novel is Anna Karenina and I recommend that everyone read Anna Karenina

Lenny Rachitsky:I'm reading that right now I've never read it before

Nabil Qureshi:No way yeah so it's by by Leo Tolstoy as you know it's this epic like nineteenth century Russian novel that follows a set of characters across society and I think it's just extraordinary because what's what's amazing about him is he's just able to imagine himself into the brain of anybody and so even like he will briefly just go into the consciousness of I don't know the the servant who's bringing the meal to the table or something like that he'll just tell you a page of what they were thinking and then he'll just flip back into his main character's head I think that is the most impressive demonstration of this kind of skill I've ever seen and I think to connect it to your question this is what you have to do if you're gonna be really good at product is you have to really think yourself into the other person's head and you have to be really seeing it the way that they do and it's so hard especially as a founder or product person not to just get stuck on your own way of seeing the problem right it's like you wrote up this doc you made these marks you're like this is gonna be great and then you take it to somebody they don't care that much you really have to like exercise your empathy and understand why they see it that way and what they actually care about

Lenny Rachitsky:What a beautiful way to bring it all together let me also add while I'm reading the book something a tip here is people talk about having ChatGPT voice mode just kinda sitting there next to you I found that extremely helpful with this book where I just ask like what the hell does this thing mean like there's all these Russian dances and balls and etiquette and you just ask and you're like I'm reading Anna Karenina what does this mean and it just tells you

Lenny Rachitsky:So there's another cool tip for AI okay with that Nabil this was incredible two final questions in case people wanna look you up where can they find you online and how can listeners be useful to you

Nabil Qureshi:Yes

Nabil Qureshi:Find me online my website is nabilqu.co and my X handle is nabil q u I'm probably most active on X but yeah my website has all the links and you know a bunch of essays and interesting stuff how can you help me I would say send me an email my email is on my website introduce yourself say hi I love meeting people I don't always have time for coffees nowadays or things like that but I genuinely do get a lot of energy from just receiving emails from interesting people so please do reach out

Lenny Rachitsky:Awesome definitely check out Nabil's principles is that the is that the name of that post yeah great okay that's one to start with and then also there's the Palantir post that we just talked through okay Nabil thank you so much for being here

Nabil Qureshi:Thank you appreciate it Lenny

Lenny Rachitsky:Bye everyone thank you so much for listening if you found this valuable you can subscribe to the show on Apple Podcasts Spotify or your favorite podcast app also please consider giving us a rating or leaving a review as that really helps other listeners find the podcast you can find all past episodes or learn more about the show at lennyspodcast.com see you in the next episode