Larry Ashbrook

Founder and Managing Partner of G-Squared, a growth-stage venture capital firm with a concentrated investment strategy.

Claims

As speaker

Mentioned in

Key positions and views

The traditional 10-year venture capital fund lifecycle is 'fundamentally broken' and unsuited for modern markets where companies stay private for longer periods.

Distributions to Paid-In Capital (DPI) is the only performance metric that matters for LPs; Total Value to Paid-In (TVPI) and Multiple on Invested Capital (MOIC) are 'fake numbers' representing unrealized paper gains.

A highly concentrated portfolio, where 80-90% of risk is allocated to just 10 companies, is the optimal strategy for generating outsized returns in the late-stage growth market.

The Large Language Model (LLM) market is a consolidated duopoly, and it is highly improbable that any new competitor will be able to challenge the scale of OpenAI and Anthropic within the next three years.

Fund managers have a deep personal responsibility to their LPs, which can extend to personally absorbing a multi-million dollar loss to prevent the fund from entering a fraudulent investment like Theranos.

Podcast consensus on Ashbrook

Points of consensus

▶Larry Ashbrook consistently advocates for a highly concentrated investment strategy, with claims indicating G-Squared focuses 80-90% of its risk in just 10 companies, exemplified by a single investment in Spotify representing 40% of a $380 million fund.Mar 2026

▶Multiple claims detail Ashbrook's track record of both massive wins and significant losses, highlighting a high-risk, high-reward approach. He cites billion-dollar and $800 million returns from Spotify and Coursera, respectively, alongside a $500 million loss on Getir and a $70 million loss on 23andMe.Mar 2026

▶Ashbrook is a vocal critic of traditional venture capital structures and metrics. He states the fund lifecycle model is 'fundamentally broken' and advises LPs to ignore TVPI and MOIC as 'fake numbers' in favor of focusing solely on DPI (Distributions to Paid-In Capital).Mar 2026

Points of debate

▶There is a notable contrast in G-Squared's performance within the same sector, as Ashbrook claims the firm lost 20% on its Uber investment while generating a 3x return on its direct competitor, Lyft.Mar 2026

▶Ashbrook's narrative presents a tension between embracing extreme risk and learning from its consequences. While his core strategy involves massive, concentrated bets, he also recounts personally paying a multi-million dollar settlement to exit a Theranos deal, a painful experience that taught him caution.Mar 2026

▶A contradiction exists between Ashbrook's critique of the 'fundamentally broken' VC model and his firm's ability to generate billion-dollar outcomes for LPs within that same system, suggesting a strategy of exploiting the model's flaws rather than operating outside of it.Mar 2026

▶There is a contrast between G-Squared's successful investments in mature tech companies like Coursera and Spotify and its costly misjudgment of market timing in the broader SaaS sector, where it invested at 12x revenue multiples in 2020-2021 that later compressed to 4x.Mar 2026

Key themes

▶Concentrated, High-Conviction BettingMar 2026

Ashbrook's investment philosophy, as executed by G-Squared, rejects broad diversification in favor of a highly concentrated portfolio. The firm commits 80-90% of its investment risk into just 10 companies, exemplified by a single $152 million bet on Spotify which constituted 40% of its third fund.

This 'all-in' strategy creates a binary risk profile where fund performance is dictated by a few key outcomes, leading to spectacular wins like Spotify ($1B return) and Coursera ($800M return) but also devastating losses like Getir (est. $500M loss).

▶Critique of Traditional Venture Capital NormsMar 2026

Ashbrook openly criticizes the standard venture capital model, calling the 10-year fund lifecycle 'fundamentally broken.' He dismisses common performance metrics like TVPI and MOIC as 'fake numbers' that represent unrealized paper gains, urging LPs to focus exclusively on DPI, or actual cash returned.

This public stance positions G-Squared as a firm prioritizing tangible liquidity for its investors, which may be a compelling narrative for LPs frustrated with long lock-up periods and inflated paper valuations common in the venture industry.

▶Navigating Market Cycles and Costly Misjudgments

The claims reveal a history of navigating both bull and bear markets, including investing in SaaS at peak 12x multiples that later compressed to 4x. Ashbrook is candid about major losses on high-profile companies like Getir, Uber, and 23andMe, and even details personally paying millions to exit a bad secondary deal in Theranos.

Ashbrook's transparency about significant financial losses offers a rare look into the realities of late-stage investing, demonstrating that even experienced managers make costly errors and that portfolio construction must account for severe drawdowns.

▶Strategic Focus on Late-Stage and Secondary MarketsMar 2026

G-Squared's portfolio consists of mature companies with an average age of 15 years, reflecting a strategy adapted to the reality that companies now stay private longer. The firm actively uses secondary markets, exemplified by its acquisition of Anthropic shares through the FTX bankruptcy proceedings.

This focus allows G-Squared to access established, high-growth companies pre-IPO, but it also exposes the firm to unique risks of illiquidity and valuation disputes in less-transparent markets, as the near-miss with Theranos illustrates.

Source episodes

Sentiment over time

Not enough data for timeline

Changes over time

Pre-2010

Ashbrook references this period as a time when the average company took approximately three years to go from inception to IPO.

G-Squared Fund I

The firm's first fund, totaling $35 million, was established and primarily invested in four companies: Alibaba, Spotify, Palantir, and Twitter.

2010-2018

Ashbrook observes that the average time to IPO extended to seven or eight years, a market shift that informed G-Squared's late-stage investment strategy.

G-Squared Fund III

The firm made a defining concentrated bet, allocating 40% of its $380 million third fund into Spotify, a decision that ultimately returned $1 billion to LPs.

2020-2021

During a period of market exuberance, G-Squared invested in SaaS companies at a 12x last-twelve-months revenue multiple, a valuation that later compressed significantly to around 4x.

2022

G-Squared's 2022 vintage fund invested in the cybersecurity company Wiz, achieving a 3x return on the investment within 18 months.

Suggested prompts

How does Larry Ashbrook's concentrated investment strategy perform across different market cycles compared to more diversified growth equity funds? &nearr;What are the primary risks associated with G-Squared's reliance on secondary market transactions for deal flow, as exemplified by the Theranos and FTX/Anthropic cases? &nearr;To what extent does Ashbrook's public critique of traditional VC metrics (TVPI, MOIC) influence his firm's fundraising and LP relations? &nearr;Given the significant losses in Getir and 23andMe, what changes, if any, has G-Squared implemented in its due diligence process for high-valuation, late-stage companies? &nearr;

Key concepts

G-Squared 21 ep Investment Performance 6 ep Venture Capital Strategy 5 ep Artificial Intelligence (AI) 4 ep Spotify 3 ep Anthropic 3 ep Risk Management 3 ep Coursera 2 ep Market Cycles 2 ep Secondary Markets 2 ep

Notable quotes

“my guess is those decisions we made cost our partnership probably a half a billion dollars of capital between capital actually lost and investors that you can't bring back”

Larry Ashbrook · Larry Aschebrook, Founder & MP @GSquared: How We Lost Money on Uber and Made Millions on Lyft

“I agreed to settle where I would pay a fraction of the transaction cost, but I did it personally. So our LPs didn't have to go in. And I think that what that taught me was, before we signed that paper, we better be certain. Because it cost me a few million dollars at a time where I didn't have a lot of money.”

Larry Ashbrook · Larry Aschebrook, Founder & MP @GSquared: How We Lost Money on Uber and Made Millions on Lyft

“what's holding back the next generation of the LLMs to get to Anthropic and OpenAI scale? In three years, who's going to rival them? No one.”

Larry Ashbrook · Larry Aschebrook, Founder & MP @GSquared: How We Lost Money on Uber and Made Millions on Lyft

“They're searching for a solution to it because it's fundamentally broken.”

Larry Ashbrook · Larry Aschebrook, Founder & MP @GSquared: How We Lost Money on Uber and Made Millions on Lyft

Report last updated: Apr 21, 2026

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