"Turpentine VC" | Venture Capital and Investing

This episode of Turpentine VC was recorded in front of a live audience in San Francisco in October 2018.Keith Rabois discusses his frameworks for identifying talent, sharing anecdotes about notable operators and companies like PayPal, LinkedIn, and Square. He emphasizes the importance of talent assessment, strategic thinking, and offers career advice while reflecting on his own experiences and observations. —  📰 Be notified early when Turpentine drops new publication: https://www.turpentine.co/exclusiveaccess   🙏 Help shape our show by taking our quick listener survey at https://bit.ly/TurpentinePulse   — RECOMMENDED PODCAST: 🎙️This Won't Last Eavesdrop on Keith Rabois, Kevin Ryan, Logan Bartlett, and Zach Weinberg's monthly backchannel. They unpack their hottest takes on the future of tech, business, venture, investing, and politics. Apple Podcasts: https://podcasts.apple.com/us/podcast/id1765665937 Spotify: https://open.spotify.com/show/2HwSNeVLL1MXy0RjFPyOSz  YouTube: https://www.youtube.com/@ThisWontLastpodcast   — SPONSOR: ☁️ Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds and offers one consistent price. Oracle is offering to cut your cloud bill in half. See if your company qualifies at oracle.com/turpentine  — X / TWITTER: @rabois @eriktorenberg — HIGHLIGHTS FROM THE EPISODE: "You don't want to be the best at what you do. You want to be the only one who does what you do." This was a key lesson Keith learned from a Pat Riley book. Great talent can be found in unexpected places, as demonstrated by Keith's hiring of successful executives like David Han, Jared Fleisler, and Brian Gastronomy who came from non-elite schools without technical backgrounds. You should only start a company if you have a specific idea you're deeply passionate about - Keith doesn't believe in starting companies just for the sake of being a founder. Working at a high-growth company for two years is valuable because the constant flow of problems creates unique learning opportunities, but you hit diminishing returns after about two years. The identification of talent often comes from seeing unique "sparks" - like when Taylor Francis solved the complex smoothie delivery problem at Square in an innovative way. When evaluating people, Keith tests them by continuously expanding their scope of responsibilities until they show signs of struggling. Strategic thinking means understanding how different parts of the business connect to each other - like understanding how turning different "knobs" affects the entire system. The best market opportunities exist in industries with low NPS scores that are highly fragmented and can be improved through vertical integration and simplification. Good judgment means understanding your limitations and knowing when to ask for help before getting in too deep. Getting adequate sleep (8 hours) is crucial for maintaining high performance and making good decisions - Keith believes most human problems stem from lack of sleep. A venture capitalist can effectively handle about 8-10 meetings per day before their energy and creativity begin to decline. Reading should combine both professional necessity and serendipitous discovery, with Keith still valuing physical bookstores for finding unexpected insights.

This week on Turpentine VC, Andy Price, a veteran executive recruiter and venture capitalist, joins Nolan Church and Kelli Dragovich from HR Heretics, a Turpentine podcast, for a deep dive into the crucial aspects of hiring, retaining, and developing top talent. Andy has built leadership teams for renowned companies like Snowflake and DocuSign. Check out HR Heretics for more conversations like this one (links below) —  🙏 Help shape our show by taking our quick listener survey at https://bit.ly/TurpentinePulse — SPONSORS: 📑 Discover Carta, the innovative end-to-end accounting platform revolutionizing private fund management with streamlined operations and on-demand insights. Experience the new standard at carta.com/investors. ☁️ Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds and offers one consistent price. Oracle is offering to cut your cloud bill in half. See if your company qualifies at oracle.com/turpentine  🤲🏼 GiveWell spends 50,000 hours every year doing deep-dives into different charitable programs to try to find the ways to do the most good for your dollar. GiveWell has now spent over 17 years researching charitable organizations and only directs funding to a few of the HIGHEST-IMPACT opportunities they’ve found. Visit https://www.givewell.org to find out more or make a donation. (Select PODCAST and enter Econ 102 at checkout to support our show.) 💥 Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist. — RECOMMENDED PODCAST: Listen and subscribe to HR Heretics: Apple: https://podcasts.apple.com/us/podcast/hr-heretics-how-cpos-chros-founders-and-boards-build/id1712407491 Spotify: https://open.spotify.com/show/1WML9AfadzaH9WCR4HHqbZ Substack: https://hrheretics.substack.com/ — LINKS: Artisanal Ventures: https://artisanalv.com/  — FOLLOW: https://www.linkedin.com/in/andyprice1/ https://www.linkedin.com/in/nolan-church/  https://www.linkedin.com/in/kellidragovich/  — HIGHLIGHTS FROM THE EPISODE: Even at top companies like DoorDash, executive hiring only succeeds two-thirds of the time, while most firms see one-third success rates. To mitigate hiring failures, recruiters must deeply understand a company's problems and weaknesses, not just focus on their strengths. Back-channel references are crucial but must be handled carefully, with recruiters making vague inquiries without revealing specific roles or companies. The ideal number of references is 5-7 meaningful ones, focusing on depth of conversation rather than quantity of references. Founders often get attached to "shiny new" executive candidates and forget about the people who helped build the company. When layering an existing executive, the person needs to be involved in the interview process but with clear expectations about their role. The best companies like Snowflake and ServiceNow succeed through seamless executive transitions and continuity. To help up-and-coming executives scale, companies need to invest in advisory networks and strong board members who can provide mentorship. The best executives rarely actively job hunt - instead, they study industry trends in their spare time and maintain relationships with select recruiters. Multiple one-year executive tenures are a red flag; ideal careers show 3-6 year commitments at successful companies.

Today we're sharing a conversation between Martin Casado, general partner at Andreessen Horowitz and Nathan Labenz, AI scout, which originally aired on The Cognitive Revolution podcast from Turpentine. Their discussion explores AI systems complexity and debates whether AI development will lead to AGI. The conversation covers model scaling, biological AI, driverless cars, and AI safety concerns. —  🙏 Help shape our show by taking our quick listener survey at https://bit.ly/TurpentinePulse — SPONSORS: 📑 Discover Carta, the innovative end-to-end accounting platform revolutionizing private fund management with streamlined operations and on-demand insights. Experience the new standard at carta.com/investors. ☁️ Oracle Cloud Infrastructure (OCI) is a single platform for your infrastructure, database, application development, and AI needs. OCI has four to eight times the bandwidth of other clouds and offers one consistent price. Oracle is offering to cut your cloud bill in half. See if your company qualifies at oracle.com/turpentine  🤲🏼 GiveWell spends 50,000 hours every year doing deep-dives into different charitable programs to try to find the ways to do the most good for your dollar. GiveWell has now spent over 17 years researching charitable organizations and only directs funding to a few of the HIGHEST-IMPACT opportunities they’ve found. Visit https://www.givewell.org to find out more or make a donation. (Select PODCAST and enter Econ 102 at checkout to support our show.) 💥 Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist. — RECOMMENDED PODCAST: Check out Modern Relationships, where Erik Torenberg interviews tech power couples and leading thinkers to explore how ambitious people actually make partnerships work. Founders Fund's Delian Asparouhov and researcher Nadia Asparouhova kick off the series with an unfiltered conversation about their relationship evolution. Apple: https://podcasts.apple.com/us/podcast/id1786227593 Spotify: https://open.spotify.com/show/5hJzs0gDg6lRT6r10mdpVg YouTube: https://www.youtube.com/@ModernRelationshipsPod -- 🎙️ The Cognitive Revolution Apple: https://podcasts.apple.com/us/podcast/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk — FOLLOW: @martin_casado @labenz @eriktorenberg @TurpentineVC — HIGHLIGHTS FROM THE EPISODE: Martin Casado argues AI has shown consistent incremental progress over 80 years rather than dramatic leaps, with apparent breakthroughs often being advances in specific domains rather than general intelligence. The self-driving car industry demonstrates how early promising results don't necessarily translate to general solutions, with unit economics still being 3x worse than human drivers after 20 years and ~$100B investment. The universe operates on heavy-tailed distributions where most new instances are exceptions, making truly general systems extremely difficult to create. Language Models primarily perform kernel smoothing over positional embeddings to predict average human responses, excelling at routine tasks but struggling with unique cases. Advances in biological applications of AI represent extensions of simulation capabilities in specific domains rather than steps toward general intelligence. On regulation, Martin advocates treating AI like other software - regulating applications rather than the underlying technology to avoid hampering innovation. The AI industry exhibits a "perverse economy of scale" where market leaders must spend increasingly more to maintain their advantage while followers can use their outputs to catch up. Looking forward, Martin expects continued incremental progress in specific domains rather than sudden AGI emergence, emphasizing practical applications over theoretical risks.

This ‘lost episode’ of Turpentine VC with investor Elad Gil was recorded at a unique moment in time (September 2022) — before ChatGPT, Claude and Perplexity launched. Drawing from his experiences at Google, Elad discusses early ML systems, the open source debate, NVIDIA, labor markets, and AI alignment and shares some behind the scenes anecdotes. —  🙏 Help shape our show by taking our quick listener survey at https://bit.ly/TurpentinePulse — RECOMMENDED PODCAST: Check out Modern Relationships, where Erik Torenberg interviews tech power couples and leading thinkers to explore how ambitious people actually make partnerships work. Founders Fund's Delian Asparouhov and researcher Nadia Asparouhova kick off the series with an unfiltered conversation about their relationship evolution. Apple: https://podcasts.apple.com/us/podcast/id1786227593 Spotify: https://open.spotify.com/show/5hJzs0gDg6lRT6r10mdpVg YouTube: https://www.youtube.com/@ModernRelationshipsPod -- SPONSORS: 📑Discover Carta, the innovative end-to-end accounting platform revolutionizing private fund management with streamlined operations and on-demand insights. Experience the new standard at carta.com/investors. 🤲🏼GiveWell spends 50,000 hours every year doing deep-dives into different charitable programs to try to find the ways to do the most good for your dollar. GiveWell has now spent over 17 years researching charitable organizations and only directs funding to a few of the HIGHEST-IMPACT opportunities they’ve found. Visit https://www.givewell.org to find out more or make a donation. (Select PODCAST and enter Econ 102 at checkout to support our show.) 💥 Head to Squad to access global engineering without the headache and at a fraction of the cost: head to https://choosesquad.com/ and mention “Turpentine” to skip the waitlist. — LINKS: Attention Is All You Need: https://proceedings.neurips.cc/paper_files/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf  AI Revolution - Transformers and Large Language Models (LLMs): https://blog.eladgil.com/p/ai-revolution-transformers-and-large  Elad’s website: https://eladgil.com/  High Growth Handbook by Elad Gil: https://growth.eladgil.com/ | https://www.amazon.com/High-Growth-Handbook-Elad-Gil/dp/1732265100  — FOLLOW: @eladgil @eriktorenberg @TurpentineVC — HIGHLIGHTS FROM THE EPISODE: This episode was recorded in 2022, before the launch of ChatGPT, Claude, and other major AI applications that are now common. This interview captured a moment in time when industry leaders were anticipating major breakthroughs in AI. Elad explained how AI's definition has evolved from basic automation in the 1980s to sophisticated applications, with Google emerging as the first true "AI-first" company at scale through its search and ad targeting systems. The 2017 "Attention is All You Need" paper proved pivotal, with six of its eight authors going on to start companies, creating what Gil compared to a "Xerox PARC moment" where Google developed breakthrough technology but others, particularly OpenAI, commercialized it. Elad outlined three main categories of emerging AI companies: platforms and infrastructure providers like OpenAI, AI-first standalone companies, and tech-enabled incumbents adding AI capabilities. Initial predictions about AI's impact on labor markets proved incorrect, with AI currently affecting white-collar, repetitive tasks more than blue-collar jobs, and creative and caring fields experiencing more disruption than anticipated. The semiconductor industry lacks a massive AI-specific chip company, with NVIDIA's continued success attributed to strong founder leadership, superior software tooling, and advanced interconnect capabilities. Elad emphasized the importance of open-source models and predicted the AI platform market would likely consolidate into an oligopoly similar to cloud infrastructure, with a few dominant players rather than a single winner.