Nabeel S. Qureshi (founder, writer, ex-Palantir)11 May 2025

How Palantir built the ultimate founder factory

7Frameworks

15Insights

Episode overview

Nabeel S. Qureshi explains how Palantir's selective culture and forward-deployed engineering model trained employees to solve consequential customer problems, helping produce an unusually high share of founders and product leaders. He describes how field teams embedded with organizations such as Airbus and the NIH, rapidly iterated with users, and converted repeated data problems into Foundry, Gotham, and the Ontology. The conversation also covers hiring for drive and mission fit, the ethics of defense technology, rapid startup experimentation, and Qureshi's preferred AI tools, books, and films.

Key ideas

Palantir selected independent-minded, intellectually broad, highly competitive people and used a distinctive mission as a recruiting signal.
Forward-deployed engineers worked inside customer organizations, built software themselves, and ran extremely fast feedback cycles with users.
Palantir converted lessons and internal tools from bespoke deployments into reusable products, especially Foundry's data platform and Ontology.
Data access, integration, cleaning, mapping, and organizational gatekeeping usually consume far more effort than the final analysis.
Palantir generally promoted product managers from proven forward-deployed engineers, preserving customer empathy, technical credibility, and execution drive.
A forward-deployed model requires sufficient contract value, but lighter versions can assign one engineer across several customers.
Early startups should test many bets quickly, ask customers to pay meaningful amounts early, and hire for mission-aligned drive as well as skill.
Technology work is inherently political and ethical; Qureshi argues for active engagement with difficult tradeoffs instead of automatic disengagement.

Transcript available · source text is retained privately and is not published

Frameworks in this episode

Innovation4 steps

Be Your Own First Customer: Internal Tools to Product

Turn the ugly tools your team builds to serve customers into the product — most of the value is below the waterline

Read →

Leadership4 steps

Hire by Repelling: The Distinctive Bat Signal

The best talent magnets deliberately turn some people off — clarity on who you're NOT for is the point

Read →

Leadership4 steps

Hiring for the Extra 20%

Skills are table stakes — screen for the people who'll chase the real outcome, using lateral personality signals

Read →

Entrepreneurship4 steps

Many Bets, Charge Early

Maximize the number of fast bets, then force a verdict by asking the customer to pay a lot — now

Read →

Strategy4 steps

Pivot to the Burning Problem

Founders are usually too anchored to their own product vision — index to the customer's real fire instead

Read →

Entrepreneurship4 steps

The Forward Deployed Engineer Loop

Embed a real engineer inside the customer's building and run a build-show-iterate cycle every single day

Read →

Strategy4 steps

The Murder Board

Before starting a project, invite smart outsiders whose only job is to tear your two-page plan apart

Read →

People & resources mentioned

Attributed to the moment in the episode. Timestamps are approximate.

People · 20

Lenny RachitskyMentionstoday we've got another very special compilation episode something I've been pulling on more and more with the podcast and the newsletter
“Today my guest is Nabil Kareshi.”
▶ Watch at ~0:30approx.
Nabeel S. QureshiMentionsNabil is a founder, a writer, a researcher and an engineer.
“Nabil is a founder, a writer, a researcher and an engineer.”
▶ Watch at ~1:00approx.
Tyler CowenMentionshe has this awesome blog marginal Revolution and he's really good at sharing insights from research papers
“He was recently a visiting scholar researching AI policy at the Mercada Center alongside Tyler Cohen.”
▶ Watch at ~1:00approx.
Nabeel S. QureshiMentionsNabil is a founder, a writer, a researcher and an engineer.
“Nibil, thank you so much for being here. Welcome to the podcast.”
▶ Watch at ~5:00approx.
Peter ThielMentionsyou had this debate with Peter Teal that I came across where you were debating whether technologies stop progressing
“I don't know how else you would start start this company if you were not somebody like Peter Teal.”
▶ Watch at ~8:00approx.
Stephen CohenMentionsmentioned
“with Stefan it would be you'd be chatting about philosophy for an hour and a half”
▶ Watch at ~9:30approx.
Joe LonsdaleMentionsmentioned
“earlier on it might have been somebody like Joe Londale but it was always like one of these people”
▶ Watch at ~9:30approx.
Alex KarpMentionsmentioned
“a founder it could have been Alex Cobb it could have been Stefan Cohen”
▶ Watch at ~9:30approx.
Shyam SankarMentionsPalantir executive who mandated customer use of its internal tools.
“Sean Sankar who's one who's uh I think he's the CTO or maybe he's the president now”
▶ Watch at ~28:00approx.
Barry McCardelMentionsCEO of Hex, an analytics company.
“my friend Barry Mardle who's the CEO of Hex uh the analytics company he wrote a really good post about this”
▶ Watch at ~42:00approx.
David HsuMentionsyou mentioned Lenny this this quote from David Sue from ret which I love too
“I remember reading a really interesting post by I think it was David Sue from Retool”
▶ Watch at ~44:30approx.
Ted MabreyMentionsDescribed as Palantir's head of commercial.
“There's another post by Ted Mabry, who's I think the head of commercial at Palanteer”
▶ Watch at ~47:30approx.
Max LevchinMentionsPeter Thiel and Max Levchin marshaled an incredible density of talent.
“I think Max Le tells this story of somebody interviewing at PayPal early on”
▶ Watch at ~1:04:00approx.
Fabiano CaruanaMentionsTop chess player cited as an early adopter of neural-network chess engines.
“the very top players like Magnus Carlson Fabiano they they were the ones who kind of mindmelded the most with Leela”
▶ Watch at ~1:27:30approx.
Magnus CarlsenMentionswatching him I think he was like number one in speed chess in addition to just regular chess
“the very top players like Magnus Carlson Fabiano they they were the ones who kind of mindmelded the most with Leela”
▶ Watch at ~1:27:30approx.
Keith JohnstoneMentionsBritish improvisational-theatre pioneer and author of Impro.
“The first one that comes to mind is uh Impro by Keith Johnstone.”
▶ Watch at ~1:28:00approx.
William ShakespeareMentionsQuoted in support of making career decisions consistent with one's nature and strengths.
“maybe Shakespeare's uh history plays, uh there's a there's a set of them called the Henriad.”
▶ Watch at ~1:30:00approx.
Andy GroveMentionsBusiness leader cited for distinguishing competency from motivation.
“I love uh High Output Management by Andy Grove.”
▶ Watch at ~1:31:00approx.
Christopher AlexanderMentionsThere's one book in particular by an architect named Christopher Alexander
“So, so there's this architect called Christopher Alexander who wrote these beautiful books”
▶ Watch at ~1:33:00approx.
Leo TolstoyMentionsin inocrine and a Tolstoy is basically like the dysfunctional families are all different and the happy families are the same
“So, it's by by Leo Toltoy as you know.”
▶ Watch at ~1:34:30approx.

Resources · 42

Mercatus CenterMentionscompany
“He was recently a visiting scholar researching AI policy at the Mercada Center alongside Tyler Cohen.”
▶ Watch at ~1:00approx.
National Institutes of HealthMentionscompany
“At one point he worked with the National Institute of Health and major clinical centers”
▶ Watch at ~1:00approx.
Bank of EnglandMentionscompany
“He worked at the Bank of England for a bit.”
▶ Watch at ~1:00approx.
GoCardlessMentionscompany
“He was founding member and VP of business development at Go Cardless”
▶ Watch at ~1:00approx.
Lenny's NewsletterMentionsnewsletter · Lenny Rachitsky
“if you become an annual subscriber of my newsletter, you get a bunch of amazing products for free for a year”
▶ Watch at ~2:30approx.
AttioMentionssoftware · Attio
“This episode is brought to you by Atio, the AI native CRM.”
▶ Watch at ~4:00approx.
Palantir TechnologiesMentionscompany
“30% of PMs that leave Palunteer start a company”
▶ Watch at ~5:30approx.
Palantir TechnologiesMentionscompany
“Palunteer is I the way I describe it right is they um achieve outcomes for their customers very tactically.”
▶ Watch at ~6:30approx.
GothamMentionssoftware · Palantir Technologies
“there's one that's optimized for intelligence and defense use cases. That one is called Gotham.”
▶ Watch at ~7:00approx.
FoundryMentionssoftware · Palantir Technologies
“there's one that's more optimized for commercial use cases and that one's called Foundry.”
▶ Watch at ~7:00approx.
AnthropicMentionscompany
“I think in the present day Open AI Antropic, they're both sucking up like some of the best talent”
▶ Watch at ~10:30approx.
OpenAIMentionscompany
“I think in the present day Open AI Antropic, they're both sucking up like some of the best talent”
▶ Watch at ~10:30approx.
AirbnbMentionscompany · Brian Chesky, Joe Gebbia, and Nathan Blecharczyk
“I was involved in the creating the core values at Airbnb”
▶ Watch at ~12:00approx.
Zero to OneMentionsbook · Peter Thiel and Blake Masters
“I do know that Teal writes about this in 0ero to one.”
▶ Watch at ~16:00approx.
GoogleMentionscompany · Google
“if you take Google for example there's a lot of interesting posts by people who left Google”
▶ Watch at ~16:30approx.
AirbusMentionscompany
“So at Airbus I would be at the factory where the planes were produced”
▶ Watch at ~22:00approx.
DatabricksMentionscompany · Ali Ghodsi, Matei Zaharia and co-founders
“It's similar to Snowflake or data bricks or one of these other providers.”
▶ Watch at ~23:00approx.
SnowflakeMentionscompany · Snowflake Inc.
“It's similar to Snowflake or data bricks or one of these other providers.”
▶ Watch at ~23:00approx.
JupyterUsessoftware
“early on you were basically armed with Jupyter notebooks and some some kind of data integration stuff”
▶ Watch at ~27:30approx.
Airbus A350Mentionsproduct · Airbus
“they had a new aircraft called the A350. Beautiful aircraft by the way.”
▶ Watch at ~33:00approx.
SAPMentionscompany · SAP
“all their data was stored in SAP and you know SAP is like established software.”
▶ Watch at ~35:00approx.
OntologyMentionssoftware · Palantir Technologies
“which they call ontology. You probably heard this you know term as you've seen if you see palented presentations”
▶ Watch at ~37:00approx.
OneSchemaMentionssoftware · Christina Gilbert
“Andrew is CEO of One Schkeema, one of our longtime podcast sponsors.”
▶ Watch at ~40:00approx.
HexMentionssoftware · Hex Technologies
“my friend Barry Mardle who's the CEO of Hex uh the analytics company”
▶ Watch at ~42:00approx.
RetoolMentionssoftware · Retool
“I remember reading a really interesting post by I think it was David Sue from Retool”
▶ Watch at ~44:30approx.
WindsurfMentionssoftware · Codeium
“People can just you know open up cursor winds surf and just start adding features.”
▶ Watch at ~50:00approx.
CursorMentionssoftware · Anysphere
“People can just you know open up cursor winds surf and just start adding features.”
▶ Watch at ~50:00approx.
GleanMentionscompany · Glean
“So feels like Glean is the biggest competitor to Palunteer after I hear this.”
▶ Watch at ~59:00approx.
ChatGPTMentionssoftware · OpenAI
“I think now post the chat GBT moment, people are willing to give chances to small startups”
▶ Watch at ~1:19:00approx.
Wispr FlowUsessoftware · Wispr AI
“So I use Whisper Flow quite a bit.”
▶ Watch at ~1:21:30approx.
Claude CodeUsessoftware · Anthropic
“I love clawed code for developing even though I have my complaints about it.”
▶ Watch at ~1:22:00approx.
Gemini 2.5 ProUsessoftware · Google
“Last seven days I've been testing Gemini Pro 2.5. Excellent model.”
▶ Watch at ~1:23:00approx.
XUseswebsite · X Corp.
“I use X a lot to keep on top of AI”
▶ Watch at ~1:26:30approx.
Latent SpaceRecommendsnewsletter · Shawn Wang
“There's some good newsletters. So I really like Lent Space.”
▶ Watch at ~1:26:30approx.
Leela Chess ZeroMentionssoftware
“there was very quickly an open source version of it called Leela”
▶ Watch at ~1:27:30approx.
ImproRecommendsbook · Keith Johnstone
“The first one that comes to mind is uh Impro by Keith Johnstone.”
▶ Watch at ~1:28:00approx.
The HenriadRecommendsbook · William Shakespeare
“maybe Shakespeare's uh history plays, uh there's a there's a set of them called the Henriad.”
▶ Watch at ~1:30:00approx.
High Output ManagementRecommendsbook · Andy Grove
“I love uh High Output Management by Andy Grove.”
▶ Watch at ~1:31:00approx.
OldboyMentionsfilm · Park Chan-wook
“It's by the director of Old Boy, which maybe some people have heard of.”
▶ Watch at ~1:32:00approx.
Decision to LeaveRecommendsfilm · Park Chan-wook
“The last movie I really loved was uh Decision to Leave. It's a Korean movie.”
▶ Watch at ~1:32:00approx.
Anna KareninaRecommendsbook · Leo Tolstoy
“I just my favorite novel is Anna Karanina and I would recommend that”
▶ Watch at ~1:34:00approx.
Lenny's PodcastMentionspodcast · Lenny Rachitsky
“You can find all past episodes or learn more about the show at lennispodcast.com.”
▶ Watch at ~1:37:00approx.

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Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Hot Take· 4

Hot Take10:00

The Best Companies Send a 'Bat Signal' That Turns People Off

Nabeel argues that great talent magnets put out a distinctive 'bat signal' that intentionally repels some people — that repulsion is the point. He compares it to how OpenAI and Anthropic attract people who are almost messianic about AGI, while Palantir's version was defense and 'save the shire' patriotism during an era dominated by social and mobile apps. Lenny connects it to defining Airbnb's values by being clear about who the company is not for.

A good recruiting signal has to turn some people off by design
OpenAI/Anthropic attract people who are messianic about artificial super intelligence
Palantir's signal was defense and 'save the shire' when hot companies were Facebook and Pinterest
Defining company values means clarifying who it is NOT for

“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…”
Nabeel · 10:30

“it's really important to clarify who this is not for”
Lenny · 12:00

#hiring#culture#mission#recruiting

Hot Take57:30

Palantir's Biggest Competitor Isn't Who You Think

Nabeel makes a contrarian point: Palantir's real competitor isn't another vendor but a company deciding to roll its own data infrastructure — a CIO building on a hyperscaler and doing analytics in-house. He also surfaces the human politics: data gatekeepers whose job security depends on being the only person who understands, say, the sales-calculation SQL pipeline, and who resist a platform that makes data point-and-click for everyone.

Palantir's biggest competitor is a company rolling its own solution, not a named vendor
That looks like a CIO building on top of a hyperscaler and owning analytics internally
Some gatekeepers resist because their value depends on being the sole owner of the data pipeline
Palantir's disruptive pitch: all data ingested into one platform, easy for everyone — which threatens those gatekeepers

“Palant's biggest competitor is a company rolling its own solution right and so the biggest difference would just be a c a c a CIO…”
Nabeel · 58:00

“let's say I'm the guy who I'm the only guy who understands the the way the sales calculation pipeline works”
Nabeel · 57:30

#competition#data platform#org politics#palantir

Hot Take1:10:30

Nabeel's Case Against Disengaging From Defense Work

Addressing the moral objections to Palantir, Nabeel argues that reflexive disengagement is usually the wrong answer. He points to real upside (COVID response, Operation Warp Speed, cancer research) and contends working on defense isn't inherently evil — being 'in the room' can make things like targeting more accurate and reduce error. His broader charge is that tech long refused to look at its own work through a political lens while optimizing, say, short-form video for engagement.

Reflexive disengagement is usually not the correct answer
Genuine upside existed: COVID response, Operation Warp Speed, NIH cancer research
Being in the room can make defense workflows more targeted and accurate, reducing error
Tech avoided viewing its own products (e.g. engagement-optimized short video) through a political/moral lens

“it's not like working on defense is inherently evil. It's actually a pretty interesting thing.”
Nabeel · 1:11:30

“again, disengagement isn't the answer.”
Nabeel · 1:15:30

#ethics#defense#palantir#tech and politics

Hot Take1:24:00

Contrarian Corner: Going to College Is Great

In Contrarian Corner, Nabeel's belief that most in tech reject: going to college is great, and the 'drop out at 18' advice is mostly wrong. He argues that maybe only ~5% of people (who'd have been Thiel Fellows anyway) should skip it. College is one of the few windows to make deep friendships and spend years reading, writing, and exploring intellectual topics — time that's very hard to reclaim after 21.

The 'just drop out and start working' advice is mostly wrong; it fits maybe 5% of people
College uniquely enables deep friendships and years of unstructured intellectual exploration
That kind of time is very hard to find after 21 once rent and work take over
He thinks the ROI is great despite high US fees

“I think going to college is great. I think this is a somewhat contrarian view within tech.”
Nabeel · 1:24:00

“don't drop out of college unless you have a really good reason.”
Nabeel · 1:25:30

#college#contrarian#education#career

Explainer· 7

Explainer06:30

What Palantir Actually Does (Finally Explained Simply)

Nabeel answers the question every Palantir employee gets: what does the company do? It achieves tactical outcomes for customers through what he calls the world's best data platform, sold in two flavors: Gotham for intelligence/defense and Foundry for commercial use. It typically sells to very large customers like Fortune 50 companies and governments.

Palantir achieves outcomes for customers, delivered through a data platform
Gotham is optimized for intelligence and defense; Foundry for commercial use cases
Customers are typically very large: Fortune 50 firms and governments worldwide

“Um so Palunteer is I the way I describe it right is they um achieve outcomes for their customers very tactically.”
Nabeel · 06:30

“So they sell a data platform. They typically work with very large customers is the other thing.”
Nabeel · 07:00

#palantir#data platform#foundry#gotham#enterprise

Explainer08:30

The Three Traits Palantir Screened Hard For

Nabeel describes the kind of people early Palantir attracted and deliberately screened for. Three traits stood out: fiercely independent-minded people who pushed back and thought for themselves, people with broad intellectual interests, and intensely competitive people with a win-at-all-costs mentality. The screening mechanism was unusual too — a founder had to personally interview you, often as a wide-ranging philosophy conversation.

Trait one: independent-minded people unafraid to push back and question the frame
Trait two: people with broad intellectual interests beyond tech
Trait three: intensely competitive people with a win-at-all-costs mentality
A founder (Karp, Cohen, or Lonsdale) had to interview you before an offer; interviews were unpreppable deep-dive conversations

“one is like very independent-minded people, people who weren't afraid to push back, who, you know, questioned the frame of everything and thought for themselves…”
Nabeel · 08:30

“with with Stefan it would be you'd be chatting about philosophy for an hour and a half”
Nabeel · 09:30

#hiring#culture#palantir#talent

Explainer16:00

Why Palantir Gave Almost Everyone the Same Title

For a long time nearly everyone at Palantir had the same generic title — forward deployed engineer — with titles reserved for the CEO and six directors. Nabeel explains the logic (which Thiel writes about in Zero to One): titles become a mimetic totem people compete for, triggering Goodhart's-law gaming like starting new products just to get promoted. Removing them kept roles fluid and meritocratic, though it pushed competition toward gaining favor with key executives instead.

Titles become something people compete for, producing unproductive conflict and metric-gaming
Thiel writes about this in Zero to One; example given of promotion-driven new products at big companies
Only the CEO and six directors had titles; everyone else was 'forward deployed engineer'
Downside: competition shifts to who can get into an executive's inner circle

“as soon as you have these titles, you have a thing that people are competing for and then you get these very unproductive conflicts.”
Nabeel · 16:30

“everyone's just going to have the same slightly meaningless title which is for deployed engineer and the only people who did have titles were the…”
Nabeel · 17:00

#culture#titles#org design#palantir

Explainer19:00

What a Forward Deployed Engineer Actually Is

Nabeel explains Palantir's signature role. Unlike core-product engineers who stay in the Palo Alto or New York office, forward deployed engineers were sent into the field — spending Monday to Thursday physically inside the customer's building, getting their own desk and login access, and building product side by side with the customer's staff. There were two sub-types: classic software engineers and less-code, more 'human-savvy' engineers who could reason about data and navigate executive social dynamics.

FDEs literally get a desk inside the customer's building four days a week
The role sits inside BD (business development), distinct from PD (product development)
Two types: technical software engineers, and 'technical-adjacent' people strong at reasoning about data and reading a room
It's radically more embedded than the usual model of occasional customer interviews and Zoom calls

“You would literally get a desk there and so that engineer became known as a forward deployed engineer.”
Nabeel · 19:30

“all of that was given the title of for deployed engineer and it's just an engineer who works with customers”
Nabeel · 21:00

#forward deployed engineer#product#sales engineering#palantir

Explainer26:00

How Palantir Turned 'Sparkling Accenture' Into an 80%-Margin Product

For years people dismissed Palantir as a consulting business dressed up as a product company. Nabeel explains how it became undeniably a product: 80%+ margins (versus 20–30% for consulting), and the fact you can now sign up with a credit card. The mechanism was that FDEs were their own first customers, building internal tooling to create value — and eventually a mandate that every deployment had to put a customer on those tools, which forged them into Foundry.

Palantir's 80%+ margins are the tell that it's a product company, not a 20–30% consultancy
FDEs were 'our own first customers,' building internal tooling that later became product
Sean Sankar mandated that every deployment get a customer using the internal tools within ~3 months
That painful 3–4 year process of hardening crash-prone internal tools produced Foundry

“So they have like 80% plus margins which is not really what you would get if you were actually a consulting company. It would be…”
Nabeel · 26:30

“so we were our own first customers”
Nabeel · 28:00

#business model#product#foundry#margins#services-to-product

Explainer53:30

The Real Secret: Analysis Is Just the Tip of the Data Iceberg

Nabeel argues Palantir's underrated edge was recognizing that inside big organizations, getting and cleaning data is the actual work. Everywhere they went, people waited six to eight weeks just to get data access, and even then the data wasn't queryable. The analysis everyone fixates on is only the top 5–10% of the iceberg; the hidden 90–95% is gaining access, cleaning, joining, and normalizing data — which is exactly where Palantir built product.

The big recurring pain point: waiting six to eight weeks just to get data access
Analysis is only the last 5–10%; the 90–95% before it is access, cleaning, joining, normalizing
Foundry productized each step, e.g. a universal data adapter that reads JDBC, S3 buckets, etc.
This white space existed because access was so hard that nobody had solved the problems before

“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…”
Nabeel · 54:00

“this was the big pain point was we have to wait six to eight weeks just to get data access.”
Nabeel · 54:00

#data integration#data platform#foundry#enterprise#insight

Explainer1:05:30

Why Palantir PMs Had to Be Forward Deployed Engineers First

Nabeel explains what made Palantir PMs different: you basically couldn't become a PM without first proving yourself as a forward deployed engineer. The PM for Foundry's ontology, for example, had earlier managed the Airbus factory deployment. The failure mode they were averse to was 'Google Docs syndrome' — writing PRDs and managing rationally from a distance. Successful PMs were best friends with their engineering team and won its trust fast.

You could not become a Palantir PM without first proving yourself as an FDE
The ontology PM had previously run the Airbus factory deployment
They were averse to 'Google Docs syndrome' — managing product via PRDs from a distance
PMs succeeded by being trusted best friends with their (often disagreeable) engineering teams

“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…”
Nabeel · 1:05:30

“the ones I saw who succeeded the most were just best friends with their engineering team, right?”
Nabeel · 1:07:00

#product management#palantir#hiring#forward deployed engineer

Story· 1

Story32:30

The Airbus Factory Problem That Became Foundry's Ontology

Nabeel tells the story of his Airbus deployment, where the mandate was to help ramp A350 production dramatically (roughly 4x in a year). The team built software to pull Airbus's cryptically-named SAP tables and map them to human concepts — a part, a work order, an aircraft — so any worker could ask 'where is aircraft 79?' and see its station, remaining work, and needed parts. That idea of mapping raw tables to human-legible concepts became Foundry's 'ontology,' still a major differentiator.

Airbus's mandate wasn't 'upgrade our data infrastructure' — it was 'help us accelerate A350 production'
All data lived in SAP with unreadable table names like S3F1_Z
The team mapped tables to human concepts (part, work order, aircraft) into a single legible view
This generalized into Foundry's 'ontology,' still a big differentiator today
Airbus's CEO said Palantir played a critical part; production ramped ~4x that year

“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…”
Nabeel · 36:30

“the table name would just be like S3 F1_Z or something like that”
Nabeel · 35:30

#airbus#ontology#foundry#case study#data mapping

Tool· 2

Tool1:21:30

The AI Tools Nabeel Uses Every Day

In the AI Corner, Nabeel shares the tools he actually uses. Whisper Flow for voice-to-text (great for dictating long LLM prompts, and finally accurate where Dragon and older dictation apps weren't). Claude Code as an addictive terminal-based coding agent that operates directly on the filesystem and executes complex pull requests. And Gemini Pro 2.5, which he'd been testing for a week and calls an excellent model.

Whisper Flow: button-press voice transcription, now accurate enough for long prompts
Claude Code: terminal-based coding agent that acts on the filesystem and runs complex PRs
Gemini Pro 2.5: an excellent model he'd been testing recently
He uses LLMs daily for ad hoc jobs, e.g. scripting classification of tax transactions

“I love clawed code for developing even though I have my complaints about it.”
Nabeel · 1:22:00

“So I use Whisper Flow quite a bit.”
Nabeel · 1:21:30

#ai tools#whisper flow#claude code#gemini#productivity

Tool1:28:00

Nabeel's Book Recommendations: Impro, the Henriad, High Output Management

In the lightning round, Nabeel recommends three books. Impro by Keith Johnstone — nominally about improvisational theater but really a dense book on creativity, status, and social behavior, which Palantir made every forward deployed engineer read to better read and interact with people. Shakespeare's Henriad (Henry IV, V, VI) as some of the most insightful writing on power and politics. And High Output Management by Andy Grove, valuable for how Grove thinks, not just the tactics.

Impro by Keith Johnstone: creativity, status, and social behavior; required reading for FDEs to read people better
Shakespeare's Henriad (Henry IV/V/VI): the best books on power and politics, and quick to read
High Output Management by Andy Grove: read the full book, not summaries, for how Grove thinks
Palantir also used Impro to send to people, per Karp

“they made every kind of for deployed engineer read that for the simple reason that I think it just helps you kind of read people…”
Nabeel · 1:29:00

“I love uh High Output Management by Andy Grove. I just think that's a great business book”
Nabeel · 1:31:00

#books#recommendations#impro#high output management

Takeaway· 1

Takeaway59:30

Hire for the 'Extra 20%,' Not the Skills

Reflecting on hiring for his own six-person startup, Nabeel says the hardest thing to find is someone who deeply cares and will go the extra 20% — 'an animal' who pursues the real outcome rather than checking boxes. FANG habits train people to ship code and go home, which is dangerous for a startup's first 20 hires. His answer is mission fit and screening questions like 'what's the hardest you've ever worked to get something done and why' — skills are table stakes; drive is the differentiator.

The rare, decisive hire is someone who'll work the evening to get the real outcome, not just check boxes
Big-company habits produce people who want a 400k job, set hours, and going home
Screen for mission fit and a private reason to care more than average
Useful question: 'what's the hardest you've ever worked to get something done and why' — many people have no good answer

“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…”
Nabeel · 1:00:30

“you'll ask questions like what's the hardest you've ever worked to get something done and why, right?”
Nabeel · 1:02:00

#hiring#startups#mission fit#drive

Key ideas

Frameworks in this episode

Be Your Own First Customer: Internal Tools to Product

Hire by Repelling: The Distinctive Bat Signal

Hiring for the Extra 20%

Many Bets, Charge Early

Pivot to the Burning Problem

The Forward Deployed Engineer Loop

The Murder Board

People & resources mentioned

People · 20

Resources · 42

Insights & moments

◆Hot Take· 4

The Best Companies Send a 'Bat Signal' That Turns People Off

Palantir's Biggest Competitor Isn't Who You Think

Nabeel's Case Against Disengaging From Defense Work

Contrarian Corner: Going to College Is Great

✶Explainer· 7

What Palantir Actually Does (Finally Explained Simply)

The Three Traits Palantir Screened Hard For

Why Palantir Gave Almost Everyone the Same Title

What a Forward Deployed Engineer Actually Is

How Palantir Turned 'Sparkling Accenture' Into an 80%-Margin Product

The Real Secret: Analysis Is Just the Tip of the Data Iceberg

Why Palantir PMs Had to Be Forward Deployed Engineers First

❝Story· 1

The Airbus Factory Problem That Became Foundry's Ontology

✦Tool· 2

The AI Tools Nabeel Uses Every Day

Nabeel's Book Recommendations: Impro, the Henriad, High Output Management

▲Takeaway· 1

Hire for the 'Extra 20%,' Not the Skills

Hot Take· 4

Explainer· 7

Story· 1

Tool· 2

Takeaway· 1