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BREAKING: Inside Anthropic's $100M Anthology Fund x $6.8B+ AUM Menlo Ventures Deedy Das (Deedy), AI Partner at Menlo x Anthology Fund Not short on hot takes: “Almost no iconic company came from a VC thesis” “Most engineers don't do sh*t” We cover: - Menlo Ventures : 48+ years, 80+...

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Molly O’Shea

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67,107 görüntüleme • 6 ay önce •via X (Twitter)

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From early engineer at Glean to Partner at Menlo Ventures co-leading the Anthology Fund with Anthropic, Deedy Das has gone from shipping “boring” enterprise search to backing frontier labs, infra, and research plays like Anthropic, OpenRouter, Goodfire, Prime Intellect, and Whisper. We sat down with Deedy to unpack how Glean quietly built a real AI moat before LLMs were cool, why enterprise search is significantly different than consumer search, where value actually accrues in the model vs app stack, Anthropic’s rise and the importance of Claude Code, the Anthology Fund thesis, OpenRouter’s wedge, mechanistic interpretability, the coming compute arms race, coding agents and “LLM psychosis,” and what all of this means for AI engineers deciding what to build. Deedy swyx 🔜 NeurIPS + #DevWritersRetreat Alessio Fanelli
1:15

From early engineer at Glean to Partner at Menlo Ventures co-leading the Anthology Fund with Anthropic, Deedy Das has gone from shipping “boring” enterprise search to backing frontier labs, infra, and research plays like Anthropic, OpenRouter, Goodfire, Prime Intellect, and Whisper. We sat down with Deedy to unpack how Glean quietly built a real AI moat before LLMs were cool, why enterprise search is significantly different than consumer search, where value actually accrues in the model vs app stack, Anthropic’s rise and the importance of Claude Code, the Anthology Fund thesis, OpenRouter’s wedge, mechanistic interpretability, the coming compute arms race, coding agents and “LLM psychosis,” and what all of this means for AI engineers deciding what to build. Deedy swyx 🔜 NeurIPS + #DevWritersRetreat Alessio Fanelli

Latent.Space

269,074 görüntüleme • 8 ay önce

NEW: How 137 Ventures Built a 1%+ Position in SpaceX Over 16 Years Interview with Justin Fishner-Wolfson, Co-Founder & Managing Partner One of the most underrated investment stories in tech: a contrarian approach that built one of the most consequential ownership positions in the industry. 137 quietly accumulated SpaceX since 2011, investing over 2 dozen times & never sold a share. Today the firm runs $15B+ AUM, deployed $1.7B last year, holds positions in 40+ companies, & has backed nearly 60 portfolio companies in company’s history. Big names include: SpaceX, Palantir, Uber, Anduril, Cognition, Brex, Impulse Space, Gusto, Ramp, & Hadrian. The thesis, circa 2011: companies would stay private longer. That bet built into one of venture's largest SpaceX positions, accumulated through secondaries and tenders. We cover: - Early SpaceX conviction - Buying the tender cadence - Why secondary, why now - Companies over categories - Cash on cash discipline - Passing on foundational models - Impulse Series D 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Justin Fishner-Wolfson, Co-Founder & Managing Partner at 137 Ventures (00:51) The story of SpaceX (02:50) Why companies are staying private longer (04:15) What Liquidity actually means for Founders and Employees (05:38) Why he left Founders Fund to start from scratch (06:23) $240B Secondaries market (07:01) What made SpaceX a generational bet (07:52) How the Falcon 9 made the entire Space Industry obsolete (10:59) When Starlink became the obvious winner (13:29) How 137 Ventures turns Conviction into Compounding (14:09) Backing SpaceX alumni: the Impulse investment (14:32) Will the secondary market keep growing? (15:15) Companies vs. Categories (16:25) Separating AI hype from long-term durability (17:47) How 137 Ventures is structurally different from traditional VC (22:19) SpaceX made blue collar workers rich (23:24) Ownership percentage vs. Cash on cash returns (24:31) The most memorable moments (25:43) The Third Falcon 1 Launch (26:55) Why test failures are actually a good sign (28:32) The biggest lessons from Elon and Gwynne (29:07) What's next for 137 Ventures
29:55

NEW: How 137 Ventures Built a 1%+ Position in SpaceX Over 16 Years Interview with Justin Fishner-Wolfson, Co-Founder & Managing Partner One of the most underrated investment stories in tech: a contrarian approach that built one of the most consequential ownership positions in the industry. 137 quietly accumulated SpaceX since 2011, investing over 2 dozen times & never sold a share. Today the firm runs $15B+ AUM, deployed $1.7B last year, holds positions in 40+ companies, & has backed nearly 60 portfolio companies in company’s history. Big names include: SpaceX, Palantir, Uber, Anduril, Cognition, Brex, Impulse Space, Gusto, Ramp, & Hadrian. The thesis, circa 2011: companies would stay private longer. That bet built into one of venture's largest SpaceX positions, accumulated through secondaries and tenders. We cover: - Early SpaceX conviction - Buying the tender cadence - Why secondary, why now - Companies over categories - Cash on cash discipline - Passing on foundational models - Impulse Series D 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Justin Fishner-Wolfson, Co-Founder & Managing Partner at 137 Ventures (00:51) The story of SpaceX (02:50) Why companies are staying private longer (04:15) What Liquidity actually means for Founders and Employees (05:38) Why he left Founders Fund to start from scratch (06:23) $240B Secondaries market (07:01) What made SpaceX a generational bet (07:52) How the Falcon 9 made the entire Space Industry obsolete (10:59) When Starlink became the obvious winner (13:29) How 137 Ventures turns Conviction into Compounding (14:09) Backing SpaceX alumni: the Impulse investment (14:32) Will the secondary market keep growing? (15:15) Companies vs. Categories (16:25) Separating AI hype from long-term durability (17:47) How 137 Ventures is structurally different from traditional VC (22:19) SpaceX made blue collar workers rich (23:24) Ownership percentage vs. Cash on cash returns (24:31) The most memorable moments (25:43) The Third Falcon 1 Launch (26:55) Why test failures are actually a good sign (28:32) The biggest lessons from Elon and Gwynne (29:07) What's next for 137 Ventures

Molly O’Shea

158,129 görüntüleme • 1 ay önce

Failing to Understand the Exponential, Again? My conversation with Julian Schrittwieser - Julian Schrittwieser (Anthropic, AlphaGo Zero, MuZero) - on Move 37, Scaling RL, Nobel Prize for AI, and the AI frontier: 00:00 - Cold open: “We’re not seeing any slowdown.” 00:32 - Intro — Meet Julian 01:09 - The “exponential” from inside frontier labs 04:46 - 2026–2027: agents that work a full day; expert-level breadth 08:58 - Benchmarks vs reality: long-horizon work, GDP-Val, user value 10:26 - Move 37 — what actually happened and why it mattered 13:55 - Novel science: AlphaCode/AlphaTensor → when does AI earn a Nobel? 16:25 - Discontinuity vs smooth progress (and warning signs) 19:08 - Does pre-training + RL get us there? (AGI debates aside) 20:55 - Sutton’s “RL from scratch”? Julian’s take 23:03 - Julian’s path: Google → DeepMind → Anthropic 26:45 - AlphaGo (learn + search) in plain English 30:16 - AlphaGo Zero (no human data) 31:00 - AlphaZero (one algorithm: Go, chess, shogi) 31:46 - MuZero (planning with a learned world model) 33:23 -Lessons for today’s agents: search + learning at scale 34:57 - Do LLMs already have implicit world models? 39:02 - Why RL on LLMs took time (stability, feedback loops) 41:43 - Compute & scaling for RL — what we see so far 42:35 - Rewards frontier: human prefs, rubrics, RLVR, process rewards 44:36 - RL training data & the “flywheel” (and why quality matters) 48:02 - RL & Agents 101 — why RL unlocks robustness 50:51 - Should builders use RL-as-a-service? Or just tools + prompts? 52:18 - What’s missing for dependable agents (capability vs engineering) 53:51 - Evals & Goodhart — internal vs external benchmarks 57:35 - Mechanistic interpretability & “Golden Gate Claude” 1:00:03 - Safety & alignment at Anthropic — how it shows up in practice 1:03:48 - Jobs: human–AI complementarity (comparative advantage) 1:06:33 - Inequality, policy, and the case for 10× productivity → abundance 1:09:24 - Closing thoughts
1:09:56

Failing to Understand the Exponential, Again? My conversation with Julian Schrittwieser - Julian Schrittwieser (Anthropic, AlphaGo Zero, MuZero) - on Move 37, Scaling RL, Nobel Prize for AI, and the AI frontier: 00:00 - Cold open: “We’re not seeing any slowdown.” 00:32 - Intro — Meet Julian 01:09 - The “exponential” from inside frontier labs 04:46 - 2026–2027: agents that work a full day; expert-level breadth 08:58 - Benchmarks vs reality: long-horizon work, GDP-Val, user value 10:26 - Move 37 — what actually happened and why it mattered 13:55 - Novel science: AlphaCode/AlphaTensor → when does AI earn a Nobel? 16:25 - Discontinuity vs smooth progress (and warning signs) 19:08 - Does pre-training + RL get us there? (AGI debates aside) 20:55 - Sutton’s “RL from scratch”? Julian’s take 23:03 - Julian’s path: Google → DeepMind → Anthropic 26:45 - AlphaGo (learn + search) in plain English 30:16 - AlphaGo Zero (no human data) 31:00 - AlphaZero (one algorithm: Go, chess, shogi) 31:46 - MuZero (planning with a learned world model) 33:23 -Lessons for today’s agents: search + learning at scale 34:57 - Do LLMs already have implicit world models? 39:02 - Why RL on LLMs took time (stability, feedback loops) 41:43 - Compute & scaling for RL — what we see so far 42:35 - Rewards frontier: human prefs, rubrics, RLVR, process rewards 44:36 - RL training data & the “flywheel” (and why quality matters) 48:02 - RL & Agents 101 — why RL unlocks robustness 50:51 - Should builders use RL-as-a-service? Or just tools + prompts? 52:18 - What’s missing for dependable agents (capability vs engineering) 53:51 - Evals & Goodhart — internal vs external benchmarks 57:35 - Mechanistic interpretability & “Golden Gate Claude” 1:00:03 - Safety & alignment at Anthropic — how it shows up in practice 1:03:48 - Jobs: human–AI complementarity (comparative advantage) 1:06:33 - Inequality, policy, and the case for 10× productivity → abundance 1:09:24 - Closing thoughts

Matt Turck

235,526 görüntüleme • 9 ay önce

Leaving Citadel & launching a $1B AI hedge fund — how Renee Yao built NeoIvy Capital from scratch Renee Yao walked away from two of the most elite hedge funds on Wall Street — Citadel & Millennium — and built a quant fund on a fundamentally different model: modern AI instead of human-powered alpha generation. The result: $1B+ in regulatory AUM, uncorrelated returns through COVID, & a fund Business Insider named one of the top transforming investing in North America. We cover: - Why large multi-manager quant firms rely on massive global researcher headcounts — & why Renee saw that as a model worth disrupting - The 3 barriers to entry in AI-driven quant — & why legacy sequential infrastructure can be a disadvantage compared to modern parallel distributed systems - How NeoIvy's self-evolving models adapted in real time during the March 2020 crash — while traditional quant managers had a nightmare month - The difference between beta returns, factor returns & pure alpha — & why size is the enemy of true idiosyncratic returns - Why the "black box" reputation of quant funds has been the #1 fundraising obstacle - How a 4-year-old girl visiting her uncle's room-sized supercomputer in China set the foundation for all of this - The edge/breadth/constraint framework from Grinold & Kahn — & how it shaped Renee's thinking on diversification - Renee's raw advice on staying disciplined when everyone around you is chasing beta in a bull market Transcript: 00:00 Intro 01:14 Renee Yao’s journey to founding Neo Ivy 02:28 Joining Citadel after the financial crisis 04:13 Hedge fund diversification and breadth of edge 04:45 Why Neo Ivy trades with AI strategies 07:50 How self-learning AI adapts to markets 09:40 Causation vs correlation in AI hedge funds 10:33 Barriers to entry for AI hedge funds 14:47 Risks of crowded factor bets explained 16:39 Why big funds struggle with AI talent 17:29 From PM at Citadel to hedge fund founder 18:47 Challenges of launching a quant hedge fund 20:25 Biggest constraint for AI hedge fund startups 22:08 How AI hedge funds adapted during COVID 24:04 Modern AI tools used in quant trading 25:13 Building hedge fund infrastructure from scratch 26:26 Career advice for aspiring quants and traders 28:55 Adapting career goals to changing job markets 31:57 Life lessons from trading and risk management 32:51 Staying disciplined while running a hedge fund 34:38 Obsession and belief in AI hedge funds 35:41 Closing thoughts on hedge funds and life
35:59

Leaving Citadel & launching a $1B AI hedge fund — how Renee Yao built NeoIvy Capital from scratch Renee Yao walked away from two of the most elite hedge funds on Wall Street — Citadel & Millennium — and built a quant fund on a fundamentally different model: modern AI instead of human-powered alpha generation. The result: $1B+ in regulatory AUM, uncorrelated returns through COVID, & a fund Business Insider named one of the top transforming investing in North America. We cover: - Why large multi-manager quant firms rely on massive global researcher headcounts — & why Renee saw that as a model worth disrupting - The 3 barriers to entry in AI-driven quant — & why legacy sequential infrastructure can be a disadvantage compared to modern parallel distributed systems - How NeoIvy's self-evolving models adapted in real time during the March 2020 crash — while traditional quant managers had a nightmare month - The difference between beta returns, factor returns & pure alpha — & why size is the enemy of true idiosyncratic returns - Why the "black box" reputation of quant funds has been the #1 fundraising obstacle - How a 4-year-old girl visiting her uncle's room-sized supercomputer in China set the foundation for all of this - The edge/breadth/constraint framework from Grinold & Kahn — & how it shaped Renee's thinking on diversification - Renee's raw advice on staying disciplined when everyone around you is chasing beta in a bull market Transcript: 00:00 Intro 01:14 Renee Yao’s journey to founding Neo Ivy 02:28 Joining Citadel after the financial crisis 04:13 Hedge fund diversification and breadth of edge 04:45 Why Neo Ivy trades with AI strategies 07:50 How self-learning AI adapts to markets 09:40 Causation vs correlation in AI hedge funds 10:33 Barriers to entry for AI hedge funds 14:47 Risks of crowded factor bets explained 16:39 Why big funds struggle with AI talent 17:29 From PM at Citadel to hedge fund founder 18:47 Challenges of launching a quant hedge fund 20:25 Biggest constraint for AI hedge fund startups 22:08 How AI hedge funds adapted during COVID 24:04 Modern AI tools used in quant trading 25:13 Building hedge fund infrastructure from scratch 26:26 Career advice for aspiring quants and traders 28:55 Adapting career goals to changing job markets 31:57 Life lessons from trading and risk management 32:51 Staying disciplined while running a hedge fund 34:38 Obsession and belief in AI hedge funds 35:41 Closing thoughts on hedge funds and life

Ethan Kho

138,224 görüntüleme • 5 ay önce

BREAKING: Thomas Laffont, Co-Founder of Coatue "The next Mag 7 may still be private" With $70B AUM including $30B on the private side, Thomas & I discuss Anthropic, Private/Public Markets, AI Volatility, Citrini Paper, & more. Highlights: • Anthropic: Coatue leads $30B Series G at $380B → ~$19B ARR • AI coding tools spreading across enterprises • SaaS multiples being repriced • What happens to software engineers? • Managing a mega fund with autonomous agents? • Interpreting Citrini AI “Global Intelligence Crisis” paper • Where is Thomas' French accent? Live from Upfront Summit 2026. coatue.thomas COATUE Upfront Ventures 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Thomas Laffont, Co-Founder Coatue Management (01:18) The rapid rise of Claude Code (04:15) Anthropic’s revenue growth and trajectory (05:25) Where capital is flowing: private vs public markets (08:10) The Citrini paper and AI market volatility (10:15) Are new Claude releases hurting SaaS companies? (17:22) Will AI reduce the number of engineers? (19:38) The ATM analogy for AI and jobs (21:02) Could autonomous agents automate investing? (23:18) How Coatue got conviction on Nvidia (24:18) Why TAM does not matter? (26:43) Running Coatue with his brother Philippe
29:49

BREAKING: Thomas Laffont, Co-Founder of Coatue "The next Mag 7 may still be private" With $70B AUM including $30B on the private side, Thomas & I discuss Anthropic, Private/Public Markets, AI Volatility, Citrini Paper, & more. Highlights: • Anthropic: Coatue leads $30B Series G at $380B → ~$19B ARR • AI coding tools spreading across enterprises • SaaS multiples being repriced • What happens to software engineers? • Managing a mega fund with autonomous agents? • Interpreting Citrini AI “Global Intelligence Crisis” paper • Where is Thomas' French accent? Live from Upfront Summit 2026. coatue.thomas COATUE Upfront Ventures 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Thomas Laffont, Co-Founder Coatue Management (01:18) The rapid rise of Claude Code (04:15) Anthropic’s revenue growth and trajectory (05:25) Where capital is flowing: private vs public markets (08:10) The Citrini paper and AI market volatility (10:15) Are new Claude releases hurting SaaS companies? (17:22) Will AI reduce the number of engineers? (19:38) The ATM analogy for AI and jobs (21:02) Could autonomous agents automate investing? (23:18) How Coatue got conviction on Nvidia (24:18) Why TAM does not matter? (26:43) Running Coatue with his brother Philippe

Molly O’Shea

195,560 görüntüleme • 5 ay önce

BREAKING: Inside Jake Paul's VC Fund Yes, that Jake Paul. Jake Paul & Geoffrey Woo (GEOFF) break down Anti Fund (Anti Fund) Anti Fund is a $65M+ AUM venture firm built to challenge traditional VC playbooks by investing flexibly across stages, leveraging culture, distribution, & AI Investments include: OpenAI, Anduril, Ramp, Cognition, Polymarket, Physical Intelligence, Flock Safety (via Aerodome), Chronosphere, Merge, & more.. We get into: • JP's Business Empire: W, Betr, Anti Fund, Most Valuable Promotions, Boxing Bullies, Celsius, Dog Haus, & his new Ranch • Flexible Strategy: enter early, scale conviction as companies prove out • Core Bets across AI, robotics, & defense • OpenAI Partnership, Sam Altman + involvement in the viral Sora launch • New Addition: Logan Paul Highlights: (00:00) Jake Paul & Geoffrey Woo, Anti Fund (01:26) Private jet new productivity unlock (03:37) Jake’s empire: W, Betr, Anti Fund, & more... (05:12) Silicon Valley then vs now: more alpha, same chaos (07:47) Daily routines: training, recovery, & anti-fund (10:39) Extreme context switching: from OpenAI meetings to TMZ interviews (12:54) Multiple personalities? (13:39) What it really means to be an entrepreneur (20:28) Thesis: culture, tech, timing, & urgency to win (23:11) Fund structure: AUM, check sizes, & strategy (25:45) Dynamic strategies in fast-moving AI markets (27:42) Creativity (30:33) Investment areas: AI infrastructure, applied AI, robotics, & defense tech (32:11) Meeting Sam Altman & Sora launch (35:32) Lessons from Sam Altman (37:30) Hot takes on influencers (40:46) Human stories, AI content, and robot boxing (43:22) Logan Paul joins Anti Fund (51:06) Scams (54:25) What Jake's excited about right now? (56:44) Anti Fund summit, building a 6,000-acre ranch (59:49) Doomsday bunker? (01:02:26) Setting benchmarks and goals for the next 12 months
1:06:08

BREAKING: Inside Jake Paul's VC Fund Yes, that Jake Paul. Jake Paul & Geoffrey Woo (GEOFF) break down Anti Fund (Anti Fund) Anti Fund is a $65M+ AUM venture firm built to challenge traditional VC playbooks by investing flexibly across stages, leveraging culture, distribution, & AI Investments include: OpenAI, Anduril, Ramp, Cognition, Polymarket, Physical Intelligence, Flock Safety (via Aerodome), Chronosphere, Merge, & more.. We get into: • JP's Business Empire: W, Betr, Anti Fund, Most Valuable Promotions, Boxing Bullies, Celsius, Dog Haus, & his new Ranch • Flexible Strategy: enter early, scale conviction as companies prove out • Core Bets across AI, robotics, & defense • OpenAI Partnership, Sam Altman + involvement in the viral Sora launch • New Addition: Logan Paul Highlights: (00:00) Jake Paul & Geoffrey Woo, Anti Fund (01:26) Private jet new productivity unlock (03:37) Jake’s empire: W, Betr, Anti Fund, & more... (05:12) Silicon Valley then vs now: more alpha, same chaos (07:47) Daily routines: training, recovery, & anti-fund (10:39) Extreme context switching: from OpenAI meetings to TMZ interviews (12:54) Multiple personalities? (13:39) What it really means to be an entrepreneur (20:28) Thesis: culture, tech, timing, & urgency to win (23:11) Fund structure: AUM, check sizes, & strategy (25:45) Dynamic strategies in fast-moving AI markets (27:42) Creativity (30:33) Investment areas: AI infrastructure, applied AI, robotics, & defense tech (32:11) Meeting Sam Altman & Sora launch (35:32) Lessons from Sam Altman (37:30) Hot takes on influencers (40:46) Human stories, AI content, and robot boxing (43:22) Logan Paul joins Anti Fund (51:06) Scams (54:25) What Jake's excited about right now? (56:44) Anti Fund summit, building a 6,000-acre ranch (59:49) Doomsday bunker? (01:02:26) Setting benchmarks and goals for the next 12 months

Molly O’Shea

823,056 görüntüleme • 5 ay önce

Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack
1:05:15

Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack

Matt Turck

11,908 görüntüleme • 2 ay önce

NEW: a16z bought Turpentine. OpenAI bought TBPN. Jack Altman joined Benchmark. Now Lightspeed makes its move.. The $40B AUM VC fund hired Claire Zau (aka 'Zauey Talks' on IG) to lead *new media* & co-host Lightwork, its weekly AI podcast Zauey Talks Stats: - 350K+ followers - 10M+ monthly impressions - Built in ~1 year We cover: - The tech media land grab - Split investing + media role - Tech X vs mainstream social media - AI bubble? - Why does GenZ hate AI? - Who tells the AI story best? Lightwork is co-hosted by Claire Zau & CMO Josh Machiz Since 2000, Lightspeed has been an early backer of Abridge, Anthropic, Anduril, Castelion, Databricks, Glean, Mistral, Navan, Neko Health, Netskope, Thinking Machines, Reflection AI, Rubrik, Snap, Skild AI, Vinted, Wiz, & more. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Claire Zau, Partner at Lightspeed Venture Partners (00:54) Inside Lightspeed's new podcast studio (02:37) How Josh Found Claire on TikTok (04:34) Why venture expertise is missing from the mainstream (08:23) The content that actually works (10:19) What TikTok comments taught her about AI perception (13:01) Keeping editorial independence at a mega fund (14:42) The split role nobody thought was possible (17:20) The show built to bring mainstream audiences into venture (20:43) The AI bubble question everyone's asking (22:00) What Claire is most excited about covering (23:39) Why Gen Z hating AI makes no sense (28:50) How big tech companies can fix their image problem (32:16) Who tells the AI story best (34:14) The Lightspeed portfolio companies to watch (38:40) Two creators compare notes on building in media (43:31) Getting recognized in the wild (45:43) Expanding beyond ed tech into AI frontier
48:56

NEW: a16z bought Turpentine. OpenAI bought TBPN. Jack Altman joined Benchmark. Now Lightspeed makes its move.. The $40B AUM VC fund hired Claire Zau (aka 'Zauey Talks' on IG) to lead *new media* & co-host Lightwork, its weekly AI podcast Zauey Talks Stats: - 350K+ followers - 10M+ monthly impressions - Built in ~1 year We cover: - The tech media land grab - Split investing + media role - Tech X vs mainstream social media - AI bubble? - Why does GenZ hate AI? - Who tells the AI story best? Lightwork is co-hosted by Claire Zau & CMO Josh Machiz Since 2000, Lightspeed has been an early backer of Abridge, Anthropic, Anduril, Castelion, Databricks, Glean, Mistral, Navan, Neko Health, Netskope, Thinking Machines, Reflection AI, Rubrik, Snap, Skild AI, Vinted, Wiz, & more. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Claire Zau, Partner at Lightspeed Venture Partners (00:54) Inside Lightspeed's new podcast studio (02:37) How Josh Found Claire on TikTok (04:34) Why venture expertise is missing from the mainstream (08:23) The content that actually works (10:19) What TikTok comments taught her about AI perception (13:01) Keeping editorial independence at a mega fund (14:42) The split role nobody thought was possible (17:20) The show built to bring mainstream audiences into venture (20:43) The AI bubble question everyone's asking (22:00) What Claire is most excited about covering (23:39) Why Gen Z hating AI makes no sense (28:50) How big tech companies can fix their image problem (32:16) Who tells the AI story best (34:14) The Lightspeed portfolio companies to watch (38:40) Two creators compare notes on building in media (43:31) Getting recognized in the wild (45:43) Expanding beyond ed tech into AI frontier

Molly O’Shea

156,791 görüntüleme • 1 ay önce

NEW: How AWS Sold Cloud Computing to the CIA (and legitimized it for the entire world.) Teresa Carlson built AWS Public Sector from $0 to $10 Billion in Revenue in 10 years Now, as Founding CEO of General Catalyst Institute, she's helping startups gain an unfair advantage. Teresa breaks down the deal that defined cloud — & what AI likely needs to do next. We cover: → How AWS won the CIA contract → Lessons from Jeff Bezos & Andy Jassy → One-way vs two-way doors as a decision framework → Why AI is a "double or triple-strap-in" cloud → How startups actually win in DC today → The case for a federal AI framework → Inside the General Catalyst Institute Teresa Carlson General Catalyst 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Teresa Carlson, Founding CEO at GCI (01:08) The historic Kentucky Derby win (02:38) $10B AWS blueprint (04:56) Converting the skeptics (12:03) Contract that changed the trajectory of AWS (17:05) Building a world-class team (24:01) The scaling mantra (29:12) Lessons from Jeff Bezos & Andy Jassy (35:33) Why is AI scaling scaring governments? (40:23) Surviving the AI debt trap (44:56) Why do government deals matter? (48:55) Founding the General Catalyst Institute with Hemant Taneja (Hemant Taneja) (54:49) Founders storming Capitol Hill (59:53) The unspoken rule of DC (01:05:53) The next big AI shockwave
1:07:58

NEW: How AWS Sold Cloud Computing to the CIA (and legitimized it for the entire world.) Teresa Carlson built AWS Public Sector from $0 to $10 Billion in Revenue in 10 years Now, as Founding CEO of General Catalyst Institute, she's helping startups gain an unfair advantage. Teresa breaks down the deal that defined cloud — & what AI likely needs to do next. We cover: → How AWS won the CIA contract → Lessons from Jeff Bezos & Andy Jassy → One-way vs two-way doors as a decision framework → Why AI is a "double or triple-strap-in" cloud → How startups actually win in DC today → The case for a federal AI framework → Inside the General Catalyst Institute Teresa Carlson General Catalyst 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Teresa Carlson, Founding CEO at GCI (01:08) The historic Kentucky Derby win (02:38) $10B AWS blueprint (04:56) Converting the skeptics (12:03) Contract that changed the trajectory of AWS (17:05) Building a world-class team (24:01) The scaling mantra (29:12) Lessons from Jeff Bezos & Andy Jassy (35:33) Why is AI scaling scaring governments? (40:23) Surviving the AI debt trap (44:56) Why do government deals matter? (48:55) Founding the General Catalyst Institute with Hemant Taneja (Hemant Taneja) (54:49) Founders storming Capitol Hill (59:53) The unspoken rule of DC (01:05:53) The next big AI shockwave

Molly O’Shea

78,617 görüntüleme • 2 ay önce

LIVE NOW - Is The Crypto-Native Era Coming to an End? - Lessons from 10 Years in Crypto Joey Krug (Founders Fund partner, former Pantera Capital co-CIO, and Augur co-founder) returns to unpack whether the “crypto-native era” is fading as institutions and mainstream apps adopt crypto rails without adopting crypto culture. We dig into: - The prediction markets breakout (and why Polymarket finally found product-market fit). - The coming regulatory fights around market structure and “insider” edges. - What’s next for founders building in a post-cypherpunk, distribution-first phase of crypto. Enjoy the episode! -------------- TIMESTAMPS 0:00 Intro 5:45 Is Crypto-Native Dead? 16:37 Lessons From Augur 20:29 Prediction Market’s Success 25:24 Just Gambling? 27:50 Prediction Market Regulation 41:03 Founders Fund Polymarket Bet 44:37 FBI Raid 46:47 Founders Fund Crypto Investment Thesis 53:46 DATs 57:02 Layer1 Valuation 1:00:40 ETH Valuation 1:04:32 What Would Joey Build Today? 1:06:13 Crypto x AI 1:10:09 Frontier Tech x Crypto 1:14:26 4-Year Cycles 1:16:16 Less Upside in Crypto Now? 1:19:37 Crypto Privacy 1:20:41 Last & Next Decade 1:23:05 Closing & Disclaimers
1:23:50

LIVE NOW - Is The Crypto-Native Era Coming to an End? - Lessons from 10 Years in Crypto Joey Krug (Founders Fund partner, former Pantera Capital co-CIO, and Augur co-founder) returns to unpack whether the “crypto-native era” is fading as institutions and mainstream apps adopt crypto rails without adopting crypto culture. We dig into: - The prediction markets breakout (and why Polymarket finally found product-market fit). - The coming regulatory fights around market structure and “insider” edges. - What’s next for founders building in a post-cypherpunk, distribution-first phase of crypto. Enjoy the episode! -------------- TIMESTAMPS 0:00 Intro 5:45 Is Crypto-Native Dead? 16:37 Lessons From Augur 20:29 Prediction Market’s Success 25:24 Just Gambling? 27:50 Prediction Market Regulation 41:03 Founders Fund Polymarket Bet 44:37 FBI Raid 46:47 Founders Fund Crypto Investment Thesis 53:46 DATs 57:02 Layer1 Valuation 1:00:40 ETH Valuation 1:04:32 What Would Joey Build Today? 1:06:13 Crypto x AI 1:10:09 Frontier Tech x Crypto 1:14:26 4-Year Cycles 1:16:16 Less Upside in Crypto Now? 1:19:37 Crypto Privacy 1:20:41 Last & Next Decade 1:23:05 Closing & Disclaimers

Bankless

12,983 görüntüleme • 7 ay önce

NEW: Brian Singerman, fmr Founders Fund, now GPx, on why he only invests in *people* SpaceX is the reason he joined Founders Fund in 2008 "If SpaceX didn't work, Founders Fund would not exist." From Elon & SpaceX to Karp & Palantir, to Anduril, Airbnb, Stripe, & Stemcentrx, Brian Singerman's whole framework is one question: Is this the best founder in the world at their particular thing? We get into: - What makes Founders Fund unique: a team of strong-willed, genuinely authentic individuals - Why a 3x fund loses to the S&P - How a lifetime of strategy gaming shapes how he reads founders & now GPs - Why he bets against the end of the world every time - Why he's bullish on N-of-1 human cultural artifacts in an AI world - Why Cyan Banister & Palmer Luckey are genuinely N-of-1 people Thank you to Max Levchin, Trae Stephens & Scott Nolan for great questions 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Brian Singerman, Co-Founder of GPx, Former Partner at Founders Fund (00:42) Founders Fund (02:09) Max Levchin's unfiltered questions (05:25) How gaming shaped his investing (06:11) Joining Founders Fund in 2008 (07:34) Silicon Valley's most fascinating characters (09:29) Lessons from Peter Thiel (11:26) Building a culture of conviction (11:59) The art of spotting A+ founders (13:55) Trae's biggest lesson from Peter Thiel (14:41) Is socialism a threat to America? (15:58) Why capital is leaving California (17:03) The obsession with Hawaii (20:59) The Founders Fund playbook (24:51) "If SpaceX didn't work, Founders Fund would not exist" (26:03) Why Elon is one of one (27:30) Why everyone knew Starlink would win (28:42) Inside Founders Fund's biggest bets (31:06) The Founders Fund founder archetype (33:25) Backing fund managers instead of startups (35:22) The new generation of GPs (36:34) The most authentic people in tech (41:38) Why other VCs aren't the audience (44:05) Music, Memorabilia & N-of-1 Artifacts (46:25) The story behind Brian's music studio (49:22) What's next for Brian?
51:06

NEW: Brian Singerman, fmr Founders Fund, now GPx, on why he only invests in *people* SpaceX is the reason he joined Founders Fund in 2008 "If SpaceX didn't work, Founders Fund would not exist." From Elon & SpaceX to Karp & Palantir, to Anduril, Airbnb, Stripe, & Stemcentrx, Brian Singerman's whole framework is one question: Is this the best founder in the world at their particular thing? We get into: - What makes Founders Fund unique: a team of strong-willed, genuinely authentic individuals - Why a 3x fund loses to the S&P - How a lifetime of strategy gaming shapes how he reads founders & now GPs - Why he bets against the end of the world every time - Why he's bullish on N-of-1 human cultural artifacts in an AI world - Why Cyan Banister & Palmer Luckey are genuinely N-of-1 people Thank you to Max Levchin, Trae Stephens & Scott Nolan for great questions 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Brian Singerman, Co-Founder of GPx, Former Partner at Founders Fund (00:42) Founders Fund (02:09) Max Levchin's unfiltered questions (05:25) How gaming shaped his investing (06:11) Joining Founders Fund in 2008 (07:34) Silicon Valley's most fascinating characters (09:29) Lessons from Peter Thiel (11:26) Building a culture of conviction (11:59) The art of spotting A+ founders (13:55) Trae's biggest lesson from Peter Thiel (14:41) Is socialism a threat to America? (15:58) Why capital is leaving California (17:03) The obsession with Hawaii (20:59) The Founders Fund playbook (24:51) "If SpaceX didn't work, Founders Fund would not exist" (26:03) Why Elon is one of one (27:30) Why everyone knew Starlink would win (28:42) Inside Founders Fund's biggest bets (31:06) The Founders Fund founder archetype (33:25) Backing fund managers instead of startups (35:22) The new generation of GPs (36:34) The most authentic people in tech (41:38) Why other VCs aren't the audience (44:05) Music, Memorabilia & N-of-1 Artifacts (46:25) The story behind Brian's music studio (49:22) What's next for Brian?

Molly O’Shea

250,577 görüntüleme • 1 ay önce

BREAKING: Unpacking the largest investment in the history of Altimeter → OpenAI Reaching a $500B valuation & 700M WAUs, Apoorv Agrawal, AI & Software Partner at Altimeter, breaks down how to value OpenAI's insane growth We dig into the numbers. + PLTR FDE, XBOW, Power Laws, Supercycles Highlights - AI Supercycle Mirrors Past Technology Shifts - “Speed Is the Only Moat” - Power Law of VC - XBOW & the Future of Cybersecurity - Palantir Culture → Forward Deployed Engineers Timestamps (00:00) Altimeter’s $10B+ AUM strategy (01:57) Why Altimeter concentrated its largest investment ever in OpenAI (04:45) VC Power Law: Why 0.3% of companies drive 99% of returns (09:25) Consumer adoption of ChatGPT & enterprise spillover (12:08) Velocity: Why speed is the ultimate moat in AI (14:18) Parasocial relationships with ChatGPT (19:29) Adoption curves: Raising the ceiling vs. raising the floor (23:30) Defining AGI & DOOM (25:40) GPT-5 release: Volatility, iteration, & anti-fragility (32:00) XBOW AI: When AI becomes the world’s top hacker (38:22) Where AI value accrues: Chips, infrastructure, or applications (42:50) $1B talent wars & Meta’s AI strategy (44:12) Palantir’s billion-dollar FDE culture (50:10) Lessons from Shyam Sankar & Alex Karp (53:52) Evaluating founder performance & IPO readiness (55:36) IPO Predictions: Klarna, Discord, Databricks, Cerebras, Anduril Apoorv Agrawal | Altimeter Capital
59:15

BREAKING: Unpacking the largest investment in the history of Altimeter → OpenAI Reaching a $500B valuation & 700M WAUs, Apoorv Agrawal, AI & Software Partner at Altimeter, breaks down how to value OpenAI's insane growth We dig into the numbers. + PLTR FDE, XBOW, Power Laws, Supercycles Highlights - AI Supercycle Mirrors Past Technology Shifts - “Speed Is the Only Moat” - Power Law of VC - XBOW & the Future of Cybersecurity - Palantir Culture → Forward Deployed Engineers Timestamps (00:00) Altimeter’s $10B+ AUM strategy (01:57) Why Altimeter concentrated its largest investment ever in OpenAI (04:45) VC Power Law: Why 0.3% of companies drive 99% of returns (09:25) Consumer adoption of ChatGPT & enterprise spillover (12:08) Velocity: Why speed is the ultimate moat in AI (14:18) Parasocial relationships with ChatGPT (19:29) Adoption curves: Raising the ceiling vs. raising the floor (23:30) Defining AGI & DOOM (25:40) GPT-5 release: Volatility, iteration, & anti-fragility (32:00) XBOW AI: When AI becomes the world’s top hacker (38:22) Where AI value accrues: Chips, infrastructure, or applications (42:50) $1B talent wars & Meta’s AI strategy (44:12) Palantir’s billion-dollar FDE culture (50:10) Lessons from Shyam Sankar & Alex Karp (53:52) Evaluating founder performance & IPO readiness (55:36) IPO Predictions: Klarna, Discord, Databricks, Cerebras, Anduril Apoorv Agrawal | Altimeter Capital

Molly O’Shea

207,506 görüntüleme • 11 ay önce

At 23, with no legal background, Max Junestrand co-founded Legora to transform how lawyers work. Today, Legora’s AI workspace is used by tens of thousands of lawyers across Europe—valued at $675M just 13 months after launch. From due diligence grids that turn days of work into minutes, to Word integrations that renegotiate contracts, Max sat down with Gustaf Alströmer to share how Legora won over skeptical firms, scaled from 10 to 100 people, and built a new category in legal AI. 00:45 – Legora's Origin Story 01:00 – Building an AI Workspace for Lawyers 02:20 – The GPT Unlock 04:10 – The “Aha Moment” with Law Firms 06:15 – Raising $80M and Scaling Fast 06:30 – How Legora Works 09:40 – How It Transforms Legal Work 11:40 – Selling To AI Skeptics 14:40 – Creative Use Cases: From Court Battles to NDAs 17:30 – Starting Without Industry Expertise 18:40 – Interviewing 100 Lawyers 20:30 – Competing with Legacy Legal Tech Giants 23:50 – Tech Stack and Model Strategy 25:00 – Who Actually Buys AI inside a Law Firm? 27:00 – Cracking Sales in Conservative Industries 28:00 – Max’s Background: From eSports to Startups 30:50 – Hypergrowth: 10 → 100 People in 13 Months 34:00 – Why Hiring Ex-Founders Works 36:45 – The Future Job of a Lawyer 38:35 – What PMF Felt Like 39:45 – Why They Stayed in Stockholm (Not SF) 41:00 – Becoming the Category Leader in Legal AI 42:00 – Advice for Founders Building Vertical AI Companies 43:20 – What It’s Like to Work at Legora
45:25

At 23, with no legal background, Max Junestrand co-founded Legora to transform how lawyers work. Today, Legora’s AI workspace is used by tens of thousands of lawyers across Europe—valued at $675M just 13 months after launch. From due diligence grids that turn days of work into minutes, to Word integrations that renegotiate contracts, Max sat down with Gustaf Alströmer to share how Legora won over skeptical firms, scaled from 10 to 100 people, and built a new category in legal AI. 00:45 – Legora's Origin Story 01:00 – Building an AI Workspace for Lawyers 02:20 – The GPT Unlock 04:10 – The “Aha Moment” with Law Firms 06:15 – Raising $80M and Scaling Fast 06:30 – How Legora Works 09:40 – How It Transforms Legal Work 11:40 – Selling To AI Skeptics 14:40 – Creative Use Cases: From Court Battles to NDAs 17:30 – Starting Without Industry Expertise 18:40 – Interviewing 100 Lawyers 20:30 – Competing with Legacy Legal Tech Giants 23:50 – Tech Stack and Model Strategy 25:00 – Who Actually Buys AI inside a Law Firm? 27:00 – Cracking Sales in Conservative Industries 28:00 – Max’s Background: From eSports to Startups 30:50 – Hypergrowth: 10 → 100 People in 13 Months 34:00 – Why Hiring Ex-Founders Works 36:45 – The Future Job of a Lawyer 38:35 – What PMF Felt Like 39:45 – Why They Stayed in Stockholm (Not SF) 41:00 – Becoming the Category Leader in Legal AI 42:00 – Advice for Founders Building Vertical AI Companies 43:20 – What It’s Like to Work at Legora

Y Combinator

185,285 görüntüleme • 11 ay önce

NEW: The Death of Spreadsheet Investing. Inside Benchmark's New AI Playbook Everett Randle (Everett Randle), GP at Benchmark Why every golden rule of SaaS just got inverted & how AI is rewriting venture investing: › You can now pass $1B+ in revenue with unproven unit economics.. › Late-stage companies can have much higher upside than a Series C Benchmark's AI Bets: Cerebras, Manus, Mercor, Sierra, Legora, Fireworks, Exa, Starcloud, Gumloop.. We cover: › The Disorientation: Scale No Longer De-Risks a Company › What Happened to the Golden Rules? › AI Inverted Nearly Every Framework › New Taxonomy: P x Q x M › Inference Is the Demand Engine › Tokenomics: Frontier vs Open Source › The Liquidity Shock: Reframing the Returns Math › Benchmark's Model: Founders Over Themes 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Everett Randle, General Partner at Benchmark (00:58) Coming off Benchmark's AGM (04:05) The Golden rules of Investing are all gone (08:58) Who actually has a handle on AI Economics? (12:57) Why Benchmark bets on Founders, not Categories (15:31) Brad Gerstner's "Age of Inference" Thesis (19:07) The most important shift since the Cloud (23:55) Inside Gumloop's AI automation canvas (26:40) The Token Maxing problem nobody's solving (27:25) Ev's "Mom Test" for frontier AI (31:33) What happens when frontier models get too cheap (34:44) Inside the new funding playbook (40:31) Venture Capital became a product, not a firm (42:35) The Biggest IPO wave Wall Street's ever seen (49:08) The secret behind Benchmark's wildly diverse bets (52:54) The mentors who shaped him
57:04

NEW: The Death of Spreadsheet Investing. Inside Benchmark's New AI Playbook Everett Randle (Everett Randle), GP at Benchmark Why every golden rule of SaaS just got inverted & how AI is rewriting venture investing: › You can now pass $1B+ in revenue with unproven unit economics.. › Late-stage companies can have much higher upside than a Series C Benchmark's AI Bets: Cerebras, Manus, Mercor, Sierra, Legora, Fireworks, Exa, Starcloud, Gumloop.. We cover: › The Disorientation: Scale No Longer De-Risks a Company › What Happened to the Golden Rules? › AI Inverted Nearly Every Framework › New Taxonomy: P x Q x M › Inference Is the Demand Engine › Tokenomics: Frontier vs Open Source › The Liquidity Shock: Reframing the Returns Math › Benchmark's Model: Founders Over Themes 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Everett Randle, General Partner at Benchmark (00:58) Coming off Benchmark's AGM (04:05) The Golden rules of Investing are all gone (08:58) Who actually has a handle on AI Economics? (12:57) Why Benchmark bets on Founders, not Categories (15:31) Brad Gerstner's "Age of Inference" Thesis (19:07) The most important shift since the Cloud (23:55) Inside Gumloop's AI automation canvas (26:40) The Token Maxing problem nobody's solving (27:25) Ev's "Mom Test" for frontier AI (31:33) What happens when frontier models get too cheap (34:44) Inside the new funding playbook (40:31) Venture Capital became a product, not a firm (42:35) The Biggest IPO wave Wall Street's ever seen (49:08) The secret behind Benchmark's wildly diverse bets (52:54) The mentors who shaped him

Molly O’Shea

294,168 görüntüleme • 1 ay önce

BREAKING: Inside a16z's $22B AUM Growth Fund Waymo, Kalshi, Coinbase, Robinhood, Stripe, Revolut, ElevenLabs, Flock Safety, Harvey, EliseAI, Hebbia, Roblox, Anduril, Sardine With a fresh $6.75B Growth fund, General Partner Alex Immerman (Alex Immerman) shares how a16z evaluates category leaders & why firms are rethinking old metrics in the AI era. “If you look at OpenAI & Anthropic alone, those two companies added as much revenue last year as 1/2 of the public cloud universe excluding the Mag Seven.” Even as AI added ~$6T in market value to the stock market in 2025, we discuss the private companies driving the next wave of growth. Topics include: • Marc Andreessen lore • Why the fastest-growing tech companies are still private • Waymo’s expansion & the future of autonomous vehicles • ElevenLabs & the breakout of voice AI platforms • Kalshi & the rise of prediction markets • The four largest tech companies adding 1% to U.S. GDP growth with $400B in spending in 2025 • How a16z grew from a startup VC to capturing 18% of all U.S. venture capital • Why engagement, retention, & product defensibility matter more than ever Full conversation ↓ 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Alex Immerman, GP a16z (00:53) Flock Safety: Most underrated company in America (03:43) Private vs public market growth gap (04:43) Do gross margins matter in AI companies? (06:33) Waymo’s growth & $16B funding round (08:13) The future of ride sharing & autonomous vehicles (10:01) Where the value in self driving tech will accrue (12:27) Tesla FSD vs Waymo’s full stack approach (13:50) The growing brand power of Waymo (15:43) What comes after autonomous cars? (17:41) Are people really worried about AI taking over? (18:55) Inside ElevenLabs’ $500M funding round (22:12) The real world use cases of voice AI agents (22:55) How a16z invested in Kalshi (24:11) Why Kalshi over Polymarket? (26:35) Prediction markets vs g*mbling (29:33) Is fintech making a comeback? (32:44) Why stablecoins are becoming important (33:30) Lessons from Coinbase founder Brian Armstrong (34:19) How a16z evaluates growth companies (36:52) Where startups spend money: R&D vs marketing (38:44) Why startups need a strong Act 2 (40:08) Why venture outcomes are getting bigger & bigger (42:24) Why backing the market leader matters (43:49) The best books for founders (44:59) How a16z built its media machine (47:03) Who will be the first Trillionaire?
48:41

BREAKING: Inside a16z's $22B AUM Growth Fund Waymo, Kalshi, Coinbase, Robinhood, Stripe, Revolut, ElevenLabs, Flock Safety, Harvey, EliseAI, Hebbia, Roblox, Anduril, Sardine With a fresh $6.75B Growth fund, General Partner Alex Immerman (Alex Immerman) shares how a16z evaluates category leaders & why firms are rethinking old metrics in the AI era. “If you look at OpenAI & Anthropic alone, those two companies added as much revenue last year as 1/2 of the public cloud universe excluding the Mag Seven.” Even as AI added ~$6T in market value to the stock market in 2025, we discuss the private companies driving the next wave of growth. Topics include: • Marc Andreessen lore • Why the fastest-growing tech companies are still private • Waymo’s expansion & the future of autonomous vehicles • ElevenLabs & the breakout of voice AI platforms • Kalshi & the rise of prediction markets • The four largest tech companies adding 1% to U.S. GDP growth with $400B in spending in 2025 • How a16z grew from a startup VC to capturing 18% of all U.S. venture capital • Why engagement, retention, & product defensibility matter more than ever Full conversation ↓ 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Alex Immerman, GP a16z (00:53) Flock Safety: Most underrated company in America (03:43) Private vs public market growth gap (04:43) Do gross margins matter in AI companies? (06:33) Waymo’s growth & $16B funding round (08:13) The future of ride sharing & autonomous vehicles (10:01) Where the value in self driving tech will accrue (12:27) Tesla FSD vs Waymo’s full stack approach (13:50) The growing brand power of Waymo (15:43) What comes after autonomous cars? (17:41) Are people really worried about AI taking over? (18:55) Inside ElevenLabs’ $500M funding round (22:12) The real world use cases of voice AI agents (22:55) How a16z invested in Kalshi (24:11) Why Kalshi over Polymarket? (26:35) Prediction markets vs g*mbling (29:33) Is fintech making a comeback? (32:44) Why stablecoins are becoming important (33:30) Lessons from Coinbase founder Brian Armstrong (34:19) How a16z evaluates growth companies (36:52) Where startups spend money: R&D vs marketing (38:44) Why startups need a strong Act 2 (40:08) Why venture outcomes are getting bigger & bigger (42:24) Why backing the market leader matters (43:49) The best books for founders (44:59) How a16z built its media machine (47:03) Who will be the first Trillionaire?

Molly O’Shea

145,674 görüntüleme • 4 ay önce

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:
1:11:41

My conversation with OpenAI co-founder Greg Brockman This is the most detailed first-person account of the 72 hours after Sam Altman was fired. We also go deep on what comes next: the global race to AGI, why ChatGPT stopped showing reasoning, how much of OpenAI's own code is now written by AI ("it's hard to know what percent is not"), and the untold story of how OpenAI actually started in 2015. 00:00:00 Introduction 00:00:49 Meeting Sam Altman and Starting OpenAI 00:02:40 Building the Founding Team 00:04:25 DeepMind's Lead Over OpenAI 00:04:54 Changing OpenAI to a For-Profit Model 00:06:05 Breakthrough Moments at OpenAI 00:08:22 What Dota 2 Meant for OpenAI 00:10:04 Reasoning Versus Prediction 00:11:59 Tensions Grow at OpenAI 00:15:44 Sam Altman's Firing 00:17:49 Greg Quits OpenAI 00:19:56 Sam Explores Deal with Microsoft's Satya 00:20:28 Petition for Altman's Return 00:23:43 Ilya Sutskever Leaves OpenAI 00:24:59 Lessons Learned after Sam Ousting 00:28:22 The Thing Ilya Said that Greg Can't Forget 00:32:22 Is AI Going Parabolic? 00:33:24 How Much of OpenAI's Code is Written by AI? 00:36:21 Do AI Chatbots Tell Us What We Want to Hear? 00:38:06 The Global AI Race to Reach AGI 00:38:40 What Happens if US Doesn't Reach AGI First? 00:39:49 Are Countries Stealing AI Advancements? 00:40:38 Why ChatGPT No Longer Shows Reasoning 00:41:47 The Finite Constraints of Compute 00:43:38 On Investing Early in Data Centers 00:46:31 The Future of Data Center Specialization 00:47:52 How to Decide Whose Queries to Serve 00:49:08 OpenAI on Consumer vs Enterprise Models 00:53:05 Data Centers in Space? 01:00:56 What Should AI Regulation Look Like? 01:04:33 The Future of AI-Powered Entrepreneurship 01:04:44 AI and Job Loss 01:07:15 The Skills Young People Should Invest In 01:11:30 What Does Success Look Like For You? Full episode on X below. Also find it on: • YouTube: • Spotify: • Apple:

Shane Parrish

450,952 görüntüleme • 3 ay önce

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead
1:09:53

My dear friend, Vlad Tenev, changed the landscape of investing forever! The rise of the retail investor is largely due to Robinhood's success... and in this new Journey Man, we discuss it all... Enjoy! 00:00 - Intro 00:53 - Introducing Vlad Tenev of Robinhood 01:27 - Why Take on Wall Street? 01:54 - Robinhood’s Zero-Fee Origin Story 02:53 - Inspiration from Instagram and Uber 04:24 - Reimagining Trading for Mobile 05:05 - The Challenge of Disrupting Finance 05:42 - Why Everything Is Hard 06:34 - Early Wrong Assumptions 07:42 - Raising Capital with a Small Vision 08:48 - Funding Robinhood on AngelList 09:50 - Early Investors Changed Their Lives 10:38 - The Crypto Explosion Begins 11:07 - Considering a Bitcoin Exchange First 12:17 - Bitcoin’s Early Skepticism and Growth 13:08 - Robinhood Launches Crypto in 2018 14:03 - 2020: Crypto Revenue Surges Overnight 15:04 - The Challenge of Crypto Cyclicality 16:11 - Staffing a Volatile Business 17:10 - Building Robinhood’s Lean Crypto Team 18:46 - Robinhood’s First Crypto Event Coming 19:38 - Where TradFi Meets DeFi 20:34 - Tokenizing Everything 21:09 - Robinhood’s Vision for Crypto + Finance 21:47 - Thoughts on Crypto Options Demand 23:04 - Why Crypto Options Haven’t Taken Off 24:09 - Millennials and the Speculative Economy 25:22 - Democratizing Trading for Everyone 26:08 - Why Buy-and-Hold Doesn’t Work for All 27:15 - Trading vs Investing: A Matter of Wealth 28:01 - Trading as a Skill Anyone Can Build 29:13 - Robinhood’s Role in Onboarding Millions 30:06 - The Fed's Role and Retail Insight 31:03 - The Rise of the Retail Macro Trader 32:17 - Helping Users Succeed with Robinhood Strategies 33:35 - Power of Community and the Hive Mind 34:55 - Will AI Disrupt Community Too? 36:14 - Technological Waves and Investor Opportunity 37:10 - Human Purpose in an AI World 37:52 - Tokenizing Human Connection 38:28 - Creators, Platforms, and Future-Proofing 39:26 - Vlad’s Long-Term View of the Future 40:05 - Financial Services at the Heart of Disruption 41:14 - If AI Replaces Jobs, What Happens to Investing? 42:25 - Entering the Economic Singularity 43:31 - What Happens When AIs Win the Markets? 44:16 - AI's Role in Capital and Markets 45:07 - Will AI Eliminate Human Emotion from Markets? 46:06 - HFT: The Original AI Traders 47:20 - AI and Long-Term Probabilistic Forecasting 48:48 - GPUs, Gaming, and the Origins of AI 50:01 - Nvidia, CUDA, and Wall Street Arms Races 51:04 - Flash Boys and Microwave Trading 51:54 - Will AI Costs Go to Zero? 52:52 - Lower Cost, Higher Usage 53:41 - Robinhood’s UX Won’t Be Just a Chatbox 55:16 - Cortex: AI-Powered Features at Robinhood 56:54 - Tokenization and the Future of Asset Management 57:44 - Crowdsourced, Tokenized Hedge Funds 58:48 - Portability of Tokenized Assets 59:39 - Blockchain as the New Rails of Finance 01:00:09 - The Trump Token and Capital Formation 01:01:00 - Capital Access Unlocks Innovation 01:01:49 - Why Crypto Needs Regulatory Clarity 01:03:17 - From Meme Coins to Real Assets 01:04:17 - Crypto's Path to $100 Trillion? 01:05:15 - The Financial System Will Run on Blockchains 01:06:00 - Platform Layer vs Application Layer Wealth 01:06:29 - AI Raises Money and Launches Tokens 01:07:39 - AIs Creating Software and Capital Formation 01:08:00 - Final Thoughts: A Wild Future Ahead 01:08:20 - When Will Vlad Buy a CryptoPunk? 01:08:51 - Wrapping Up: AI, Crypto, and the Road Ahead

Raoul Pal

172,640 görüntüleme • 1 yıl önce