May 8, 2024 · 1h 17m · news

Tom Hulme: Lessons from a 24x Angel Track Record, 275x on Robinhood & Making Billions on Uber |E1150 · 20VC with Harry Stebbings

Tom Hulme · 53m spoken Harry Stebbings · 17m spoken
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

This video features an in-depth interview with Tom Hulme, Managing Partner at Google Ventures, as he shares critical insights on angel investing strategies, venture capital market dynamics, and founder psychology. Through personal anecdotes and frameworks, Tom explores the realities of portfolio management, the risks of overfunding, and the future of the artificial intelligence landscape.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Harry holds 25% of the talking time here. How this is scored →

Harry as informed peer 5.4 Guest teaching 3.9 Guest disagreement 2.3 Harry pushing back 3.4
05100:0020:0040:001:00:000:47–3:14 · Harry as informed peer 3/10 A Long-Awaited Interview Harry shares personal reflections on childhood bullying and conflict avoidance, citing Jason Lemkin to argue that founders do not want feedback. Tom playfully counters that top founders are attuned to feedback and teasingly suggests the issue might just be Harry's specific feedback. Harry accepts the ribbing lightheartedly.3:14–7:09 · Harry as informed peer 6/10 The Angel Experiment and Three Types of Investors Harry uses his sample size of 2,700 VC interviews to aggressively lower Tom's optimistic 25% estimate of 'smart' VCs down to 3%. He also pushes back on the idea that bad VCs actively damage companies, prompting Tom to counter with deal structure traps.7:09–9:57 · Harry as informed peer 6/10 The Danger of Deal Structure and TVPI Inflation Harry quotes Charlie Munger and Warren Buffett on incentive alignment regarding TVPI inflation and LP reporting. He challenges Tom on practical founder realities when cash is needed, leading to an agreeable dialogue on deal ratchets and liquidation preferences.9:57–13:43 · Harry as informed peer 6/10 The Pitfalls of Overfunding and 'Foie Gras-ing' Harry introduces the vivid concept of 'foie gras-ing' startups with excessive capital. When Tom admits his inability to stack-rank his own top angel investments in hindsight, Harry immediately connects this to his thesis on why reserve models fail.13:43–15:46 · Harry as informed peer 5/10 Lessons from Winners, Losers, and 'Hot' Rounds Tom breaks down historical exits like GoCardless versus hyper-hyped write-offs like Fab and Jawbone. Harry synthesizes the pattern into a clear thesis on the inverse correlation between seed round heat and ultimate company success.15:46–19:30 · Harry as informed peer 6/10 The Importance of Liquidity and Taking Money off the Table Harry demonstrates high domain familiarity by detailing the 'social validity' trap where multi-billion dollar funds write tiny checks that trick naive angels into co-investing. Tom strongly agrees with Harry's explanation.19:30–23:07 · Harry as informed peer 5/10 Caliber Questions: Unfair Advantage and Healthy Paranoia Harry asks whether founders really need a unique unfair advantage or if simply spotting an unfulfilled market need is enough. Tom firmly rejects the idea that ideas alone matter, emphasizing that execution is everything.23:07–25:19 · Harry as informed peer 5/10 The True Cost of Learning Venture and Check Size Consistency When Harry asks if it takes $20–30 million of burned capital to learn venture investing, Tom explicitly rejects the dollar figure framing as 'bananas'. Harry adjusts his estimate and shares his own strict rule of fixed check sizes.25:19–30:38 · Harry as informed peer 5/10 The Dilemma of Founders Raising Side Funds Harry introduces the distinction between active founders doing personal angel checks versus raising external side funds. Tom expands on the 4 S's of venture and compares VC to being a founder on antidepressants.30:38–33:23 · Harry as informed peer 6/10 The Rise of 'Tourist VCs' and Lack of Operating Empathy Harry delivers a strong critique of 30-year-old VCs from Bain writing $10M checks without operating empathy. The two share playful banter regarding Tom's Wired articles and Harry's TED talk.33:23–37:01 · Harry as informed peer 5/10 Optimism, Pre-Mortems, and the Multi-S-Curve Fallacy Tom references Daniel Kahneman's pre-mortems and questions how anyone in VC can claim complete conviction. Harry pushes back, arguing that projecting conviction is necessary salesmanship to win over founders.37:01–44:21 · Harry as informed peer 6/10 Conviction, Honesty, and the $10 Billion Founder Formula Harry argues that stellar founders can easily turn a $2B business into a $10B outcome through second-act product expansions. Tom counters with statistical reality, citing market persistence and competition constraints. Harry pushes back using the Hopin case study.44:35–51:45 · Harry as informed peer 6/10 Sifting Through the AI Frenzy: Why Foundation Models are Bad Investments Tom details foundation model economics, comparing them to rapid-depreciating power stations and framing the Inflection deal as a simple GPU cluster acquisition. Harry presses Tom on underwriting OpenAI at $90 billion.51:45–56:19 · Harry as informed peer 7/10 Capitalizing on the AI Application Layer and Incumbent Distribution Harry cites specific cash generation numbers for Microsoft ($350M/day) and Amazon to highlight why incumbents are unbeatable in AI distribution. Tom reinforces this with estimates on capital loss across AI tiers.56:19–1:00:00 · Harry as informed peer 6/10 Psychological Biases in VC: Navigating FOMO, FOOLS, and the Stripe Late-Stage Bet Tom describes GV's $100M Stripe investment at a $32B valuation. Harry pushes back hard on the underwriting math, arguing that the opportunity cost of capital makes a 3x return over 7–10 years unappealing compared to index funds.1:00:00–1:04:57 · Harry as informed peer 5/10 Founder Archetypes, Startup Clock Speed, and Generating Real Market Signals Tom discusses founder archetypes (Lemonade vs CurrencyCloud), startup clock speed, and why free pricing destroys signal. Harry enriches the segment by citing Ryan at Letterdrop on velocity versus speed.1:04:57–1:09:53 · Harry as informed peer 6/10 Managing Cultural Debt and Navigating the Remote vs. In-Person Dilemma Harry articulates the informal mentorship lost in remote work, describing 'the value in the cracks' during post-meeting taxi rides with senior mentors. Tom agrees, criticizing hybrid work mandates.1:09:53–1:17:50 · Harry as informed peer 4/10 Quick-Fire Round: AGI Hype, Defense Tech, Robotics, and the Nature of Founders In the quickfire round, Tom reveals key insights, including a strong correlation between founders hyping imminent AGI and their immediate need to raise massive capital. Harry facilitates a smooth conclusion.0:47–3:14 · Guest teaching 5/10 A Long-Awaited Interview Harry shares personal reflections on childhood bullying and conflict avoidance, citing Jason Lemkin to argue that founders do not want feedback. Tom playfully counters that top founders are attuned to feedback and teasingly suggests the issue might just be Harry's specific feedback. Harry accepts the ribbing lightheartedly.3:14–7:09 · Guest teaching 4/10 The Angel Experiment and Three Types of Investors Harry uses his sample size of 2,700 VC interviews to aggressively lower Tom's optimistic 25% estimate of 'smart' VCs down to 3%. He also pushes back on the idea that bad VCs actively damage companies, prompting Tom to counter with deal structure traps.7:09–9:57 · Guest teaching 3/10 The Danger of Deal Structure and TVPI Inflation Harry quotes Charlie Munger and Warren Buffett on incentive alignment regarding TVPI inflation and LP reporting. He challenges Tom on practical founder realities when cash is needed, leading to an agreeable dialogue on deal ratchets and liquidation preferences.9:57–13:43 · Guest teaching 3/10 The Pitfalls of Overfunding and 'Foie Gras-ing' Harry introduces the vivid concept of 'foie gras-ing' startups with excessive capital. When Tom admits his inability to stack-rank his own top angel investments in hindsight, Harry immediately connects this to his thesis on why reserve models fail.13:43–15:46 · Guest teaching 3/10 Lessons from Winners, Losers, and 'Hot' Rounds Tom breaks down historical exits like GoCardless versus hyper-hyped write-offs like Fab and Jawbone. Harry synthesizes the pattern into a clear thesis on the inverse correlation between seed round heat and ultimate company success.15:46–19:30 · Guest teaching 3/10 The Importance of Liquidity and Taking Money off the Table Harry demonstrates high domain familiarity by detailing the 'social validity' trap where multi-billion dollar funds write tiny checks that trick naive angels into co-investing. Tom strongly agrees with Harry's explanation.19:30–23:07 · Guest teaching 3/10 Caliber Questions: Unfair Advantage and Healthy Paranoia Harry asks whether founders really need a unique unfair advantage or if simply spotting an unfulfilled market need is enough. Tom firmly rejects the idea that ideas alone matter, emphasizing that execution is everything.23:07–25:19 · Guest teaching 4/10 The True Cost of Learning Venture and Check Size Consistency When Harry asks if it takes $20–30 million of burned capital to learn venture investing, Tom explicitly rejects the dollar figure framing as 'bananas'. Harry adjusts his estimate and shares his own strict rule of fixed check sizes.25:19–30:38 · Guest teaching 4/10 The Dilemma of Founders Raising Side Funds Harry introduces the distinction between active founders doing personal angel checks versus raising external side funds. Tom expands on the 4 S's of venture and compares VC to being a founder on antidepressants.30:38–33:23 · Guest teaching 2/10 The Rise of 'Tourist VCs' and Lack of Operating Empathy Harry delivers a strong critique of 30-year-old VCs from Bain writing $10M checks without operating empathy. The two share playful banter regarding Tom's Wired articles and Harry's TED talk.33:23–37:01 · Guest teaching 4/10 Optimism, Pre-Mortems, and the Multi-S-Curve Fallacy Tom references Daniel Kahneman's pre-mortems and questions how anyone in VC can claim complete conviction. Harry pushes back, arguing that projecting conviction is necessary salesmanship to win over founders.37:01–44:21 · Guest teaching 5/10 Conviction, Honesty, and the $10 Billion Founder Formula Harry argues that stellar founders can easily turn a $2B business into a $10B outcome through second-act product expansions. Tom counters with statistical reality, citing market persistence and competition constraints. Harry pushes back using the Hopin case study.44:35–51:45 · Guest teaching 6/10 Sifting Through the AI Frenzy: Why Foundation Models are Bad Investments Tom details foundation model economics, comparing them to rapid-depreciating power stations and framing the Inflection deal as a simple GPU cluster acquisition. Harry presses Tom on underwriting OpenAI at $90 billion.51:45–56:19 · Guest teaching 4/10 Capitalizing on the AI Application Layer and Incumbent Distribution Harry cites specific cash generation numbers for Microsoft ($350M/day) and Amazon to highlight why incumbents are unbeatable in AI distribution. Tom reinforces this with estimates on capital loss across AI tiers.56:19–1:00:00 · Guest teaching 4/10 Psychological Biases in VC: Navigating FOMO, FOOLS, and the Stripe Late-Stage Bet Tom describes GV's $100M Stripe investment at a $32B valuation. Harry pushes back hard on the underwriting math, arguing that the opportunity cost of capital makes a 3x return over 7–10 years unappealing compared to index funds.1:00:00–1:04:57 · Guest teaching 4/10 Founder Archetypes, Startup Clock Speed, and Generating Real Market Signals Tom discusses founder archetypes (Lemonade vs CurrencyCloud), startup clock speed, and why free pricing destroys signal. Harry enriches the segment by citing Ryan at Letterdrop on velocity versus speed.1:04:57–1:09:53 · Guest teaching 4/10 Managing Cultural Debt and Navigating the Remote vs. In-Person Dilemma Harry articulates the informal mentorship lost in remote work, describing 'the value in the cracks' during post-meeting taxi rides with senior mentors. Tom agrees, criticizing hybrid work mandates.1:09:53–1:17:50 · Guest teaching 5/10 Quick-Fire Round: AGI Hype, Defense Tech, Robotics, and the Nature of Founders In the quickfire round, Tom reveals key insights, including a strong correlation between founders hyping imminent AGI and their immediate need to raise massive capital. Harry facilitates a smooth conclusion.0:47–3:14 · Guest disagreement 4/10 A Long-Awaited Interview Harry shares personal reflections on childhood bullying and conflict avoidance, citing Jason Lemkin to argue that founders do not want feedback. Tom playfully counters that top founders are attuned to feedback and teasingly suggests the issue might just be Harry's specific feedback. Harry accepts the ribbing lightheartedly.3:14–7:09 · Guest disagreement 4/10 The Angel Experiment and Three Types of Investors Harry uses his sample size of 2,700 VC interviews to aggressively lower Tom's optimistic 25% estimate of 'smart' VCs down to 3%. He also pushes back on the idea that bad VCs actively damage companies, prompting Tom to counter with deal structure traps.7:09–9:57 · Guest disagreement 2/10 The Danger of Deal Structure and TVPI Inflation Harry quotes Charlie Munger and Warren Buffett on incentive alignment regarding TVPI inflation and LP reporting. He challenges Tom on practical founder realities when cash is needed, leading to an agreeable dialogue on deal ratchets and liquidation preferences.9:57–13:43 · Guest disagreement 1/10 The Pitfalls of Overfunding and 'Foie Gras-ing' Harry introduces the vivid concept of 'foie gras-ing' startups with excessive capital. When Tom admits his inability to stack-rank his own top angel investments in hindsight, Harry immediately connects this to his thesis on why reserve models fail.13:43–15:46 · Guest disagreement 1/10 Lessons from Winners, Losers, and 'Hot' Rounds Tom breaks down historical exits like GoCardless versus hyper-hyped write-offs like Fab and Jawbone. Harry synthesizes the pattern into a clear thesis on the inverse correlation between seed round heat and ultimate company success.15:46–19:30 · Guest disagreement 1/10 The Importance of Liquidity and Taking Money off the Table Harry demonstrates high domain familiarity by detailing the 'social validity' trap where multi-billion dollar funds write tiny checks that trick naive angels into co-investing. Tom strongly agrees with Harry's explanation.19:30–23:07 · Guest disagreement 3/10 Caliber Questions: Unfair Advantage and Healthy Paranoia Harry asks whether founders really need a unique unfair advantage or if simply spotting an unfulfilled market need is enough. Tom firmly rejects the idea that ideas alone matter, emphasizing that execution is everything.23:07–25:19 · Guest disagreement 4/10 The True Cost of Learning Venture and Check Size Consistency When Harry asks if it takes $20–30 million of burned capital to learn venture investing, Tom explicitly rejects the dollar figure framing as 'bananas'. Harry adjusts his estimate and shares his own strict rule of fixed check sizes.25:19–30:38 · Guest disagreement 1/10 The Dilemma of Founders Raising Side Funds Harry introduces the distinction between active founders doing personal angel checks versus raising external side funds. Tom expands on the 4 S's of venture and compares VC to being a founder on antidepressants.30:38–33:23 · Guest disagreement 2/10 The Rise of 'Tourist VCs' and Lack of Operating Empathy Harry delivers a strong critique of 30-year-old VCs from Bain writing $10M checks without operating empathy. The two share playful banter regarding Tom's Wired articles and Harry's TED talk.33:23–37:01 · Guest disagreement 3/10 Optimism, Pre-Mortems, and the Multi-S-Curve Fallacy Tom references Daniel Kahneman's pre-mortems and questions how anyone in VC can claim complete conviction. Harry pushes back, arguing that projecting conviction is necessary salesmanship to win over founders.37:01–44:21 · Guest disagreement 4/10 Conviction, Honesty, and the $10 Billion Founder Formula Harry argues that stellar founders can easily turn a $2B business into a $10B outcome through second-act product expansions. Tom counters with statistical reality, citing market persistence and competition constraints. Harry pushes back using the Hopin case study.44:35–51:45 · Guest disagreement 3/10 Sifting Through the AI Frenzy: Why Foundation Models are Bad Investments Tom details foundation model economics, comparing them to rapid-depreciating power stations and framing the Inflection deal as a simple GPU cluster acquisition. Harry presses Tom on underwriting OpenAI at $90 billion.51:45–56:19 · Guest disagreement 1/10 Capitalizing on the AI Application Layer and Incumbent Distribution Harry cites specific cash generation numbers for Microsoft ($350M/day) and Amazon to highlight why incumbents are unbeatable in AI distribution. Tom reinforces this with estimates on capital loss across AI tiers.56:19–1:00:00 · Guest disagreement 3/10 Psychological Biases in VC: Navigating FOMO, FOOLS, and the Stripe Late-Stage Bet Tom describes GV's $100M Stripe investment at a $32B valuation. Harry pushes back hard on the underwriting math, arguing that the opportunity cost of capital makes a 3x return over 7–10 years unappealing compared to index funds.1:00:00–1:04:57 · Guest disagreement 1/10 Founder Archetypes, Startup Clock Speed, and Generating Real Market Signals Tom discusses founder archetypes (Lemonade vs CurrencyCloud), startup clock speed, and why free pricing destroys signal. Harry enriches the segment by citing Ryan at Letterdrop on velocity versus speed.1:04:57–1:09:53 · Guest disagreement 1/10 Managing Cultural Debt and Navigating the Remote vs. In-Person Dilemma Harry articulates the informal mentorship lost in remote work, describing 'the value in the cracks' during post-meeting taxi rides with senior mentors. Tom agrees, criticizing hybrid work mandates.1:09:53–1:17:50 · Guest disagreement 2/10 Quick-Fire Round: AGI Hype, Defense Tech, Robotics, and the Nature of Founders In the quickfire round, Tom reveals key insights, including a strong correlation between founders hyping imminent AGI and their immediate need to raise massive capital. Harry facilitates a smooth conclusion.0:47–3:14 · Harry pushing back 3/10 A Long-Awaited Interview Harry shares personal reflections on childhood bullying and conflict avoidance, citing Jason Lemkin to argue that founders do not want feedback. Tom playfully counters that top founders are attuned to feedback and teasingly suggests the issue might just be Harry's specific feedback. Harry accepts the ribbing lightheartedly.3:14–7:09 · Harry pushing back 6/10 The Angel Experiment and Three Types of Investors Harry uses his sample size of 2,700 VC interviews to aggressively lower Tom's optimistic 25% estimate of 'smart' VCs down to 3%. He also pushes back on the idea that bad VCs actively damage companies, prompting Tom to counter with deal structure traps.7:09–9:57 · Harry pushing back 4/10 The Danger of Deal Structure and TVPI Inflation Harry quotes Charlie Munger and Warren Buffett on incentive alignment regarding TVPI inflation and LP reporting. He challenges Tom on practical founder realities when cash is needed, leading to an agreeable dialogue on deal ratchets and liquidation preferences.9:57–13:43 · Harry pushing back 3/10 The Pitfalls of Overfunding and 'Foie Gras-ing' Harry introduces the vivid concept of 'foie gras-ing' startups with excessive capital. When Tom admits his inability to stack-rank his own top angel investments in hindsight, Harry immediately connects this to his thesis on why reserve models fail.13:43–15:46 · Harry pushing back 2/10 Lessons from Winners, Losers, and 'Hot' Rounds Tom breaks down historical exits like GoCardless versus hyper-hyped write-offs like Fab and Jawbone. Harry synthesizes the pattern into a clear thesis on the inverse correlation between seed round heat and ultimate company success.15:46–19:30 · Harry pushing back 2/10 The Importance of Liquidity and Taking Money off the Table Harry demonstrates high domain familiarity by detailing the 'social validity' trap where multi-billion dollar funds write tiny checks that trick naive angels into co-investing. Tom strongly agrees with Harry's explanation.19:30–23:07 · Harry pushing back 4/10 Caliber Questions: Unfair Advantage and Healthy Paranoia Harry asks whether founders really need a unique unfair advantage or if simply spotting an unfulfilled market need is enough. Tom firmly rejects the idea that ideas alone matter, emphasizing that execution is everything.23:07–25:19 · Harry pushing back 4/10 The True Cost of Learning Venture and Check Size Consistency When Harry asks if it takes $20–30 million of burned capital to learn venture investing, Tom explicitly rejects the dollar figure framing as 'bananas'. Harry adjusts his estimate and shares his own strict rule of fixed check sizes.25:19–30:38 · Harry pushing back 2/10 The Dilemma of Founders Raising Side Funds Harry introduces the distinction between active founders doing personal angel checks versus raising external side funds. Tom expands on the 4 S's of venture and compares VC to being a founder on antidepressants.30:38–33:23 · Harry pushing back 3/10 The Rise of 'Tourist VCs' and Lack of Operating Empathy Harry delivers a strong critique of 30-year-old VCs from Bain writing $10M checks without operating empathy. The two share playful banter regarding Tom's Wired articles and Harry's TED talk.33:23–37:01 · Harry pushing back 4/10 Optimism, Pre-Mortems, and the Multi-S-Curve Fallacy Tom references Daniel Kahneman's pre-mortems and questions how anyone in VC can claim complete conviction. Harry pushes back, arguing that projecting conviction is necessary salesmanship to win over founders.37:01–44:21 · Harry pushing back 5/10 Conviction, Honesty, and the $10 Billion Founder Formula Harry argues that stellar founders can easily turn a $2B business into a $10B outcome through second-act product expansions. Tom counters with statistical reality, citing market persistence and competition constraints. Harry pushes back using the Hopin case study.44:35–51:45 · Harry pushing back 4/10 Sifting Through the AI Frenzy: Why Foundation Models are Bad Investments Tom details foundation model economics, comparing them to rapid-depreciating power stations and framing the Inflection deal as a simple GPU cluster acquisition. Harry presses Tom on underwriting OpenAI at $90 billion.51:45–56:19 · Harry pushing back 3/10 Capitalizing on the AI Application Layer and Incumbent Distribution Harry cites specific cash generation numbers for Microsoft ($350M/day) and Amazon to highlight why incumbents are unbeatable in AI distribution. Tom reinforces this with estimates on capital loss across AI tiers.56:19–1:00:00 · Harry pushing back 6/10 Psychological Biases in VC: Navigating FOMO, FOOLS, and the Stripe Late-Stage Bet Tom describes GV's $100M Stripe investment at a $32B valuation. Harry pushes back hard on the underwriting math, arguing that the opportunity cost of capital makes a 3x return over 7–10 years unappealing compared to index funds.1:00:00–1:04:57 · Harry pushing back 2/10 Founder Archetypes, Startup Clock Speed, and Generating Real Market Signals Tom discusses founder archetypes (Lemonade vs CurrencyCloud), startup clock speed, and why free pricing destroys signal. Harry enriches the segment by citing Ryan at Letterdrop on velocity versus speed.1:04:57–1:09:53 · Harry pushing back 2/10 Managing Cultural Debt and Navigating the Remote vs. In-Person Dilemma Harry articulates the informal mentorship lost in remote work, describing 'the value in the cracks' during post-meeting taxi rides with senior mentors. Tom agrees, criticizing hybrid work mandates.1:09:53–1:17:50 · Harry pushing back 2/10 Quick-Fire Round: AGI Hype, Defense Tech, Robotics, and the Nature of Founders In the quickfire round, Tom reveals key insights, including a strong correlation between founders hyping imminent AGI and their immediate need to raise massive capital. Harry facilitates a smooth conclusion.

speaking balance: gold is Harry, purple is the guest (3 minute bins)

0:00 · Harry 30.7% · guest 69.3%0:00 · Harry 30.7% · guest 69.3%3:00 · Harry 23.9% · guest 76.1%3:00 · Harry 23.9% · guest 76.1%6:00 · Harry 27.4% · guest 72.6%6:00 · Harry 27.4% · guest 72.6%9:00 · Harry 32.2% · guest 67.8%9:00 · Harry 32.2% · guest 67.8%12:00 · Harry 18.5% · guest 81.5%12:00 · Harry 18.5% · guest 81.5%15:00 · Harry 25.6% · guest 74.4%15:00 · Harry 25.6% · guest 74.4%18:00 · Harry 36.2% · guest 63.8%18:00 · Harry 36.2% · guest 63.8%21:00 · Harry 25.4% · guest 74.6%21:00 · Harry 25.4% · guest 74.6%24:00 · Harry 36.7% · guest 63.3%24:00 · Harry 36.7% · guest 63.3%27:00 · Harry 13.5% · guest 86.5%27:00 · Harry 13.5% · guest 86.5%30:00 · Harry 31.2% · guest 68.8%30:00 · Harry 31.2% · guest 68.8%33:00 · Harry 26.9% · guest 73.1%33:00 · Harry 26.9% · guest 73.1%36:00 · Harry 33% · guest 67%36:00 · Harry 33% · guest 67%39:00 · Harry 25.6% · guest 74.4%39:00 · Harry 25.6% · guest 74.4%42:00 · Harry 28.8% · guest 71.2%42:00 · Harry 28.8% · guest 71.2%45:00 · Harry 11% · guest 89%45:00 · Harry 11% · guest 89%48:00 · Harry 30.3% · guest 69.7%48:00 · Harry 30.3% · guest 69.7%51:00 · Harry 16.4% · guest 83.6%51:00 · Harry 16.4% · guest 83.6%54:00 · Harry 29.6% · guest 70.4%54:00 · Harry 29.6% · guest 70.4%57:00 · Harry 22.7% · guest 77.3%57:00 · Harry 22.7% · guest 77.3%1:00:00 · Harry 13% · guest 87%1:00:00 · Harry 13% · guest 87%1:03:00 · Harry 24.9% · guest 75.1%1:03:00 · Harry 24.9% · guest 75.1%1:06:00 · Harry 24.1% · guest 75.9%1:06:00 · Harry 24.1% · guest 75.9%1:09:00 · Harry 27% · guest 73%1:09:00 · Harry 27% · guest 73%1:12:00 · Harry 8% · guest 92%1:12:00 · Harry 8% · guest 92%1:15:00 · Harry 27.9% · guest 72.1%1:15:00 · Harry 27.9% · guest 72.1%
Sharpest disagreement ▶ 23:22 Tom calls Harry's $20M learning framing 'bananas'

Tom directly and forcefully rejects Harry's assertion that it takes $20–30 million to learn venture investing, calling the dollar-based metric bananas.

Hardest push from Harry ▶ 58:14 Harry challenges the underwriting logic of late-stage Stripe

Harry aggressively pushes back on Tom's $100M bet on Stripe at a $32B valuation, challenging the financial math and opportunity cost of capital.

Biggest teaching moment ▶ 48:53 Tom reframes the Microsoft/Inflection deal as a hardware grab

Tom educates Harry on the reality of the Inflection deal, pointing out that Microsoft was simply acquiring GPU compute rather than buying an obsolete model.

Harry holds his own ▶ 54:42 Harry demonstrates incumbent dominance with hard financial data

Harry counters general AI startup optimism by citing Microsoft's $350 million daily cash generation, proving why incumbents hold insurmountable distribution advantages.

the scores for every segment, with the reasoning behind each
ChapterTopicHarry as informed peerGuest teachingGuest disagreementHarry pushing backWhy
A Long-Awaited Interview 3543 Harry shares personal reflections on childhood bullying and conflict avoidance, citing Jason Lemkin to argue that founders do not want feedback. Tom playfully counters that top founders are attuned to feedback and teasingly suggests the issue might just be Harry's specific feedback. Harry accepts the ribbing lightheartedly.
The Angel Experiment and Three Types of Investors 6446 Harry uses his sample size of 2,700 VC interviews to aggressively lower Tom's optimistic 25% estimate of 'smart' VCs down to 3%. He also pushes back on the idea that bad VCs actively damage companies, prompting Tom to counter with deal structure traps.
The Danger of Deal Structure and TVPI Inflation 6324 Harry quotes Charlie Munger and Warren Buffett on incentive alignment regarding TVPI inflation and LP reporting. He challenges Tom on practical founder realities when cash is needed, leading to an agreeable dialogue on deal ratchets and liquidation preferences.
The Pitfalls of Overfunding and 'Foie Gras-ing' 6313 Harry introduces the vivid concept of 'foie gras-ing' startups with excessive capital. When Tom admits his inability to stack-rank his own top angel investments in hindsight, Harry immediately connects this to his thesis on why reserve models fail.
Lessons from Winners, Losers, and 'Hot' Rounds 5312 Tom breaks down historical exits like GoCardless versus hyper-hyped write-offs like Fab and Jawbone. Harry synthesizes the pattern into a clear thesis on the inverse correlation between seed round heat and ultimate company success.
The Importance of Liquidity and Taking Money off the Table 6312 Harry demonstrates high domain familiarity by detailing the 'social validity' trap where multi-billion dollar funds write tiny checks that trick naive angels into co-investing. Tom strongly agrees with Harry's explanation.
Caliber Questions: Unfair Advantage and Healthy Paranoia 5334 Harry asks whether founders really need a unique unfair advantage or if simply spotting an unfulfilled market need is enough. Tom firmly rejects the idea that ideas alone matter, emphasizing that execution is everything.
The True Cost of Learning Venture and Check Size Consistency 5444 When Harry asks if it takes $20–30 million of burned capital to learn venture investing, Tom explicitly rejects the dollar figure framing as 'bananas'. Harry adjusts his estimate and shares his own strict rule of fixed check sizes.
The Dilemma of Founders Raising Side Funds 5412 Harry introduces the distinction between active founders doing personal angel checks versus raising external side funds. Tom expands on the 4 S's of venture and compares VC to being a founder on antidepressants.
The Rise of 'Tourist VCs' and Lack of Operating Empathy 6223 Harry delivers a strong critique of 30-year-old VCs from Bain writing $10M checks without operating empathy. The two share playful banter regarding Tom's Wired articles and Harry's TED talk.
Optimism, Pre-Mortems, and the Multi-S-Curve Fallacy 5434 Tom references Daniel Kahneman's pre-mortems and questions how anyone in VC can claim complete conviction. Harry pushes back, arguing that projecting conviction is necessary salesmanship to win over founders.
Conviction, Honesty, and the $10 Billion Founder Formula 6545 Harry argues that stellar founders can easily turn a $2B business into a $10B outcome through second-act product expansions. Tom counters with statistical reality, citing market persistence and competition constraints. Harry pushes back using the Hopin case study.
Sifting Through the AI Frenzy: Why Foundation Models are Bad Investments 6634 Tom details foundation model economics, comparing them to rapid-depreciating power stations and framing the Inflection deal as a simple GPU cluster acquisition. Harry presses Tom on underwriting OpenAI at $90 billion.
Capitalizing on the AI Application Layer and Incumbent Distribution 7413 Harry cites specific cash generation numbers for Microsoft ($350M/day) and Amazon to highlight why incumbents are unbeatable in AI distribution. Tom reinforces this with estimates on capital loss across AI tiers.
Psychological Biases in VC: Navigating FOMO, FOOLS, and the Stripe Late-Stage Bet 6436 Tom describes GV's $100M Stripe investment at a $32B valuation. Harry pushes back hard on the underwriting math, arguing that the opportunity cost of capital makes a 3x return over 7–10 years unappealing compared to index funds.
Founder Archetypes, Startup Clock Speed, and Generating Real Market Signals 5412 Tom discusses founder archetypes (Lemonade vs CurrencyCloud), startup clock speed, and why free pricing destroys signal. Harry enriches the segment by citing Ryan at Letterdrop on velocity versus speed.
Managing Cultural Debt and Navigating the Remote vs. In-Person Dilemma 6412 Harry articulates the informal mentorship lost in remote work, describing 'the value in the cracks' during post-meeting taxi rides with senior mentors. Tom agrees, criticizing hybrid work mandates.
Quick-Fire Round: AGI Hype, Defense Tech, Robotics, and the Nature of Founders 4522 In the quickfire round, Tom reveals key insights, including a strong correlation between founders hyping imminent AGI and their immediate need to raise massive capital. Harry facilitates a smooth conclusion.

Statements from this episode (61)

Insight
Hulme: Venture capital is like being a founder on antidepressants
“Venture capital. It's like being a founder on antidepressants. You basically have all of the highs, just not as high. All of the lows, just not as low.”
Tom Hulme May 8, 2024 ▶ 0:00
Insight
Hulme: Founders must avoid passive investors who think they are smart
“There are basically three types of investors. You've got smart investors that know they're smart and they're going to add value. Then you've got passive investors that are going to stay passive and they're not going to get in the way. Both of those are absolut…”
Tom Hulme May 8, 2024 ▶ 3:47
Opinion
Stebbings: The majority of startup founders do not want feedback
“The majority of founders actually just don't want the feedback.”
Harry Stebbings May 8, 2024 ▶ 2:36
Insight
Hulme: Second-time founders strongly prefer passive investors over value-add ones
“First time founders are looking for investors that add a lot of value. Those that are second time around understand it, bias, and skew wildly towards the passive.”
Tom Hulme May 8, 2024 ▶ 6:14
Insight
Hulme: Heavy deal structure in venture investments damages businesses
“I think a lot of structure in a deal can actually damage a business.”
Tom Hulme May 8, 2024 ▶ 7:06
Assertion Supported
Hulme: Priced rounds are declining as founders avoid valuation write-downs
“Oh, I think we're seeing that firstly price rounds are less common because people aren't willing to accept the new and fair valuation. So you get convertible notes.”
Tom Hulme May 8, 2024 ▶ 7:16
Insight
Hulme: Founders should accept realistic valuations instead of complex deal structures
“I think actually, if you want to maximize value for the business, you're much better off accepting the valuation That's closer to reality in the moment and building from there.”
Tom Hulme May 8, 2024 ▶ 8:21
Prediction Held up
Hulme: The tech IPO window will not open anytime soon
“Particularly since kind of the IPO window isn't open anytime soon.”
Tom Hulme May 8, 2024 ▶ 9:22
Insight
Hulme: Premature scaling inflates costs and destroys startup adaptability
“And I think what you're talking about is when the money's used for premature scaling, it's really damaging because costs go up. When your costs go up, ironically, you actually become less adaptable. So your clock speed goes down. So if your primary job in a bu…”
Tom Hulme May 8, 2024 ▶ 10:40
Insight
Hulme: Second-time founders handle overfunding better than first-time founders
“Again, one of the reasons second time founders do so well is they would be less affected. No one is unaffected, but they would be less affected.”
Tom Hulme May 8, 2024 ▶ 11:13
Assertion Not checkable as stated
Hulme: Pre-2015 angel investments achieved 4.5x DPI and 24x TVPI
“You could take a batch of my angel investments Pre- twenty-fifteen. And I tracked this roughly 27 portfolio companies, about 4.5 X DPI, about 25 X or 24 X TVPI.”
Tom Hulme May 8, 2024 ▶ 11:36
Insight
Hulme: Angel investors should refrain from making follow-on investments
“It led me to draw the conclusion as an angel, I shouldn't follow on. So I had examples of companies that would go up sort of 50 X, my pro rata allocation in the next round would be a million dollars plus, and they went to zero.”
Tom Hulme May 8, 2024 ▶ 13:02
Assertion Supported
Hulme: GoCardless has reached nine-figure annual recurring revenue
“Look, GoCardless would be an example where the business kind of nine figure ARR, they have just continued growing.”
Tom Hulme May 8, 2024 ▶ 14:12
Disclosure
Hulme: Angel investments in Fab.com acquired firm and Massive Health went to zero
“So I invested in a company that was acquired by fab.com. So I thought I had a lot of money in equity in fab at one point. I invested in really brilliant team in California called Massive Health that were acquired by Jawbone. I thought that was going to be very…”
Tom Hulme May 8, 2024 ▶ 14:34
Insight
Hulme: Founders and VCs should take secondary liquidity to minimize regret
“And my recommendation often to founders, often to VCs is to take some money off the table. It's a classic place. I like to apply a kind of regret minimization framework. Will you regret taking 10% or 20% off the table in this round? Probably not. Will you regr…”
Tom Hulme May 8, 2024 ▶ 16:19
Insight
Hulme: Angel investors frequently rely on others to do due diligence
“I think too many people in our industry, particularly angels who have other jobs, full-time jobs, We'll take the view that probably someone else has done the work. I actually think often it's surprising how people haven't done the work.”
Tom Hulme May 8, 2024 ▶ 17:49
Insight
Hulme: Asking founders about product is a lens to evaluate thinking
“I spend a lot of time with founders, and I'll ask them a lot about the product they're going to build. I know that that's probably not what they'll end up being successful with. In fact, empirically, the product often changes a lot. But I'm asking about that p…”
Tom Hulme May 8, 2024 ▶ 18:50
Opinion
Stebbings: Great entrepreneurs do not start in corporate Bain or Oxford jobs
“I don't think great, great entrepreneurs first made money from getting a job at Bain after three years at Oxford. Like they did something before.”
Harry Stebbings May 8, 2024 ▶ 19:38
Insight
Stebbings: The best founders openly acknowledge what terrifies them
“The real pattern is the best founders say, are you kidding me? Here's 10 things that are challenging me, and I'm terrified about them, and I'm like, okay, let's go through them one by one.”
Harry Stebbings May 8, 2024 ▶ 20:40
Insight
Hulme: Being too early in a market equals being wrong
“Being too early is tantamount to being wrong.”
Tom Hulme May 8, 2024 ▶ 22:14
Insight
Hulme: VC learning depends on deal cadence over time, not cash losses
“The learning cycle is number of deals and time To see how they do. And so for me, it looks more like five deals over five years to figure out, actually, if you're building the muscle and you're learning, then it looks like an absolute quantum of cash.”
Tom Hulme May 8, 2024 ▶ 23:38
Insight
Hulme: Aspiring angels should write $5k checks rather than waiting for $200k
“If your job is to learn and to demonstrate you add value, then just write small five K checks. I see so many people that never start angel investing because they think they have to invest 200 K at a time. It's crazy. If you believe you've got to learn, you wan…”
Tom Hulme May 8, 2024 ▶ 24:21
Disclosure
Stebbings: I write $25,000 angel checks consistently across all investments
“And I just do 25 every time. Every time I'm 25.”
Harry Stebbings May 8, 2024 ▶ 24:53
Opinion
Hulme: Active founders angel investing personal capital provides high-value empathy
“Yeah, so the former, I think is actually great for the portfolio companies they invest in, because I think they're in our category of smart, smart. Like, they will be specialists at something, and the founder will be able to ask them for advice, and there's no…”
Tom Hulme May 8, 2024 ▶ 25:47
Opinion
Hulme: Active startup founders raising side funds is concerning
“Now, when you start talking about raising funds, that worries me a lot because building a company is ridiculously hard. Like there's only a handful of people that have ever managed to kind of build multiple companies concurrently. And this idea of having a sid…”
Tom Hulme May 8, 2024 ▶ 26:07
Insight
Hulme: Salesmanship is the essential fourth pillar of venture capital
“The fourth S that I increasingly think is important is actually selling salesmanship. Like, great VCs are selling to LPs, they're selling to founders to take their money, and then increasingly, they're also selling to, you know, exec hires to go into portfolio…”
Tom Hulme May 8, 2024 ▶ 27:37
Insight
Hulme: Great board members act as shock absorbers for founders
“Great board members are like shock absorbers. They kind of reduce the highs and they will cushion the blows and let founders know the negatives aren't as bad.”
Tom Hulme May 8, 2024 ▶ 30:19
Opinion
Stebbings: Young VCs from Bain lack real operating and fundraising empathy
“I just see so many thirty-year-olds come out of Bain who are writing ten million dollar checks at large funds, and I'm like, you have no fucking idea how hard it is to raise money to run a business.”
Harry Stebbings May 8, 2024 ▶ 31:08
Opinion
Hulme: Venture capital is undoubtedly a game of access
“Look, without doubt it is. I think it would be really unfair to say that actually everyone has even access.”
Tom Hulme May 8, 2024 ▶ 32:54
Insight
Hulme: Investors underestimate winners by assuming single S-curve growth trajectories
“We have a sort of bias that whenever we're looking at businesses, we see them on an S curve. It's very difficult to imagine new S curves, but the best businesses will continuously put themselves on new S curves and create new opportunities.”
Tom Hulme May 8, 2024 ▶ 35:15
Insight
Hulme: Great founders collect data early to preserve option value
“Most of the best founders I've ever worked with have collected data without knowing really what it might be used for, but they've instinctively known there's option value in it.”
Tom Hulme May 8, 2024 ▶ 36:03
Opinion
Hulme: Absolute conviction in VC investments is irrational and unrealistic
“I don't understand in our industry how anyone can have complete conviction on anything. That makes no sense to me. Like I studied physics at university. We would go through a proof and I still didn't have complete conviction that I got it right. And then now w…”
Tom Hulme May 8, 2024 ▶ 36:38
Insight
Stebbings: Great founders and teams separate $2B from $10B companies
“I think the difference between a two billion and a ten billion dollar business is a fucking great exec team and founder.”
Harry Stebbings May 8, 2024 ▶ 37:42
Insight
Hulme: Ex-rocket ship employees make the best startup founders
“I think one of the best groups of founders are those that have come out of the rocket ship companies because actually they kind of instinctively know they need to aim at big opportunities and they know how to run a Fast growth business.”
Tom Hulme May 8, 2024 ▶ 39:44
Opinion
Hulme: Requiring every VC investment to be a fund-returner is flawed
“I think, ah, a lot of VC strategy is a lagging indicator of what did work in the past, and the test, Or the experiment that worked very well in the past is funds with 25 portfolio companies, power law of returns, and one or two return the whole fund, and then …”
Tom Hulme May 8, 2024 ▶ 40:18
Disclosure
Hulme: GV manages $10B with 10 to 20-year holding periods
“So our approach at GV is primarily be founder first, and we can take a very long time. You know, we have ten billion dollars under management. Alphabet does not put us under time pressure. We're less worried about IRR than we are absolute returns. And so we fo…”
Tom Hulme May 8, 2024 ▶ 41:34
Assertion Supported
Stebbings: Hopin founder Johnny Boufarhat cashed out $200M in secondary sales
“And so Johnny took two hundred million off.”
Harry Stebbings May 8, 2024 ▶ 42:15
Opinion
Hulme: Virtual event platform Hopin had product-COVID fit, not product-market fit
“Is Hopin, does Hopin have product market fit or product COVID fit? It clearly had product COVID fit. It was, you know, no one was excited to do events online. They were forced to do events online.”
Tom Hulme May 8, 2024 ▶ 42:34
Prediction Held up
Hulme: Mark Zuckerberg will own 14% of world's H100s by year-end
“He'll have 350,000 H-one hundreds by the end of this year. That is 14% of the world's H-one hundreds, and he's going to open source the result.”
Tom Hulme May 8, 2024 ▶ 45:55
Disclosure
Hulme: GV has avoided investing directly in foundation model startups
“Now we have made investments in Gen AI, but more in infrastructure, more in the application layer, more in the sort of picks and shovels to support, but we've not thus far invested in foundation models.”
Tom Hulme May 8, 2024 ▶ 46:27
Insight
Hulme: Generative AI is a sustaining innovation, not internet-scale creative destruction
“I think one of the frustrations with Gen AI, as the technology is commoditizing so quickly, is it's a sustaining innovation. It's actually going to get sprinkled across all businesses to lower costs in call centers or to improve the product in personalization.…”
Tom Hulme May 8, 2024 ▶ 47:39
Assertion Contradicted
Hulme: Microsoft acquired Inflection primarily for its 12,000 H100 GPU cluster
“I do not believe that Microsoft were buying the Pi model. I think Microsoft are GPU constrained, and we're buying a cluster of 12,000 H-one hundreds.”
Tom Hulme May 8, 2024 ▶ 49:13
Opinion
Hulme: GV would not invest in OpenAI at a $90B valuation
“I would struggle To make that investment today. No.”
Tom Hulme May 8, 2024 ▶ 50:12
Opinion
Hulme: Expecting AI researchers to build profitable businesses is ridiculous
“The idea that they can all go out and create highly profitable, fast moving businesses seems ridiculous.”
Tom Hulme May 8, 2024 ▶ 53:30
Prediction Open · timeframe May 2027
Hulme: 90% of AI foundation model capital will go to zero
“Foundation models, 90%. Application layer, 70%. And in the incumbents, the value going into the incumbents, only 20%.”
Tom Hulme May 8, 2024 ▶ 54:01
Assertion Supported
Hulme: 60% to 70% of Fortune 500 companies use Microsoft Copilot
“If you look at the proportion of the, like, Fortune 500 that are using Copilot, I think it's 60 or 70% I heard last week.”
Tom Hulme May 8, 2024 ▶ 54:18
Assertion Supported
Stebbings: Microsoft generates $350 million in cash daily
“Microsoft is throwing off three hundred and fifty million in cash a day.”
Harry Stebbings May 8, 2024 ▶ 54:50
Disclosure
Hulme: GV invested $100M into Stripe's Series G in 2020
“We invested a hundred million bucks into Stripe in 2020. We extended the series G round”
Tom Hulme May 8, 2024 ▶ 57:37
Disclosure
Hulme: GV invested in Lemonade Series A despite zero insurance experience
“We invested in Lemonade, Series A, wonderful founders. One, Shai, had done Fiverr, product and design guy. Daniel, lawyer, had done hardware, and they were going into insurance. Combined insurance experience between those two? Zero.”
Tom Hulme May 8, 2024 ▶ 1:00:33
Assertion Supported
Hulme: Currencycloud sold to Visa for $1 billion
“We invested in CurrencyCloud. Mike Lavin, the founder, I think had 30 years experience in fintech. He was so well placed to understand actually what those buyers wanted and ultimately sold the business to Visa for a billion dollars.”
Tom Hulme May 8, 2024 ▶ 1:01:18
Insight
Hulme: Execution clock speed is the primary driver from zero to one
“I think every startup is a series of unanswered questions and the best founders choose the order in which they answer the questions, and they answer them extremely efficiently, and that is basically speed of execution.”
Tom Hulme May 8, 2024 ▶ 1:02:06
Insight
Hulme: Free products generate bad feedback because users don't value them
“I see a lot of businesses, and it's slightly different in consumer, but they will not charge their early adopters, they won't charge their design partners, they won't charge their ICPs, and the problem with that is you don't know if it's valued. And generally …”
Tom Hulme May 8, 2024 ▶ 1:03:26
Insight
Hulme: Generative AI minimizes the long-term impact of technical debt
“I actually think technical debt is almost less of an issue over time, particularly with generative AI, which is actually incredibly forgiving of how you integrate it. You don't have to have like perfect systems like you perhaps used to, or certainly not as mon…”
Tom Hulme May 8, 2024 ▶ 1:05:22
Insight
Hulme: Best founders execute aggressive cuts rather than repeated shallow cuts
“I think it's one of the reasons you've seen the best founders are quite aggressive in cuts. They never do shallow cuts too often. They see that burning platform as a way to actually shift the culture and maybe move this cultural debt to the side.”
Tom Hulme May 8, 2024 ▶ 1:06:24
Insight
Hulme: Staggering hybrid attendance in small offices is a false economy
“That's a classic false economy, where people say, we can have a small office, and then we can have a third of the team in at any one time. Much better to have the full office and have all of the team in a third of the time.”
Tom Hulme May 8, 2024 ▶ 1:08:20
Opinion
Hulme: Early-career professionals must work in-office for critical learning
“I think people early in their career, being in the office is a ridiculously important learning opportunity. You learn the interpersonal stuff. You can shadow people in a way that's pretty hard on a Zoom call.”
Tom Hulme May 8, 2024 ▶ 1:08:40
Prediction Held up
Hulme: Nothing will reach $600M revenue in 2024
“I think they'll do six hundred million dollars revenue this year. They've sold three, three million devices so far”
Tom Hulme May 8, 2024 ▶ 1:10:31
Insight
Hulme: AGI hype correlates directly with founders' capital fundraising needs
“I think there is a Correlation between how aggressively people predict AGI is coming and how much capital they need to raise. So you've got Emodi from Anthropic, you've got Altman, OpenAI, Musk, XAI, all of these guys are saying that it's just around the corne…”
Tom Hulme May 8, 2024 ▶ 1:11:38
Disclosure
Hulme: GV invested in Neuralink during COVID
“During COVID, we invested in Neuralink.”
Tom Hulme May 8, 2024 ▶ 1:12:50
Prediction Not checkable as stated
Hulme: Defense tech collaboration will become increasingly vital over 20 years
“I'm going to say working with the military is important, and it's going to become more important over the next 20 years.”
Tom Hulme May 8, 2024 ▶ 1:14:54
Insight
Hulme: VCs cannot fundamentally change founders
“I think it's a good reminder that you can't change founders. Like, you can help them be better, you can give advice, et cetera, but this idea that you can just fundamentally change founders, I think it's completely wrong.”
Tom Hulme May 8, 2024 ▶ 1:16:38

Shorts cut from this episode

▶ 3 roles of a VC 💪 · 20VC with Harry Stebbings (@27:04) ▶ Why Microsoft is winning AI 🤖🚀 · 20VC with Harry Stebbings (@55:14) ▶ How to become an Angel Investor 💰🪽 · 20VC with Harry Stebb (@24:12) ▶ Why working from home is BS 🏡❌ · 20VC with Harry Stebbings (@1:08:40) ▶ The 3 types of investors 💰 · 20VC with Harry Stebbings (@0:14) ▶ Biggest lessons to win in Venture 🏅 · 20VC with Harry Stebb (@0:01)
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