20VC: Is Seed Investing Dead Without a $1BN Fund? | Does Ownership and Price Matter When Companies Can Be $1TRN Exits | Are AI Revenue Numbers Real and What to Watch Out For with Venky Ganesan, Menlo Ventures

In this in-depth conversation with Harry Stebbings, Venky Ganesan, a partner at Menlo Ventures, explores the current state of venture capital during the AI boom. He begins by sharing a personal lesson from losing 90% of his investment in Avonex early in his career, which taught him the importance of taking chips off the table—though he acknowledges this must be balanced against the danger of selling too early, using Salesforce as an example of a company that would have generated far greater returns if held longer.

Ganesan addresses the core question of whether seed investing still exists, noting that while traditional seed rounds of $3-5 million are largely gone, replaced by $10-20 million rounds or larger, seed investing as an option bet on finding outliers still exists—though the game has changed dramatically. He explains that Menlo's strategy involves buying seats at the table through seed investments with relatively indifference to valuation, aiming to double down significantly when companies demonstrate quantifiable traction.

On the subject of revenue metrics and accounting creativity, Ganesan emphasizes that any metric focused on by investors gets gamed, citing net revenue retention gaming in SaaS as a prime example. He stresses that the distinction between quality founders is whether they're focused on building real businesses and terminal value versus just achieving markups for the next round. He introduces Soros' concept of reflexivity to explain how successful companies attract capital, talent, and notoriety, creating a self-reinforcing cycle—until it stops, which is inevitable but impossible to predict.

Regarding valuation and ownership, Ganesan argues that ownership percentage matters less than opportunity size, willing to own less than 2% of Anthropic (a trillion-dollar opportunity) rather than 20% of a smaller company. However, he nuances this by noting that at the seed stage when companies are still proving themselves as outliers, ownership does matter as insurance against missing the big winners. He emphasizes the importance of laddering ownership through multiple rounds as data improves, rather than committing capital upfront at high ownership costs.

On the dilution challenge facing investors, Ganesan notes that Menlo expects roughly 60% dilution from seed round to exit, with companies scaling so fast that dilution varies dramatically. He argues that time horizon determines dilution outcomes—faster-growing companies have quicker exits and less dilution, while slower companies suffer both IRR and dilution penalties.

Ganesan makes a critical argument about IRR: in today's venture landscape, the focus must be on IRR rather than cash-on-cash returns because every venture company now benefits from (and competes against) the FAANG/Max 7 companies available to investors in public markets. To justify private market allocation, venture returns must significantly exceed what investors could achieve through index funds of public tech companies.

On competitive positioning and board seats, Menlo intentionally maintains exclusive relationships with founders when they take board seats and large checks, viewing the commitment as two-way. This led them to choose Anthropic over OpenAI despite opportunities in both. Ganesan argues that trust and mutual commitment matter more than portfolio diversification across similar companies.

The conversation explores multiple tranche financing, where founders open tranches at different valuations within days. While acknowledging the innovation behind the concept (distinguishing build-with-me capital from dumb money), Ganesan notes this has become gamed, with Menlo willing to participate in later tranches if the company is compelling, regardless of the ego hit of lower valuations.

Ganesan emphasizes the centrality of never letting ego interfere with making money for investors. His core philosophy is that personality matters in venture due to constrained supply of dealflow, but that personality should serve the purpose of capital returns, not personal validation. He shares instances where he's been caught in ego-driven negotiations and now consciously prioritizes returns over credit.

On the broader market cycle, Ganesan argues that debt defaults (not equity writedowns) typically trigger cycle breaks, as seen with Archegos. He cites historical examples of smart VCs who stepped out in 1996-97 and missed the later boom, emphasizing that timing market cycles is nearly impossible. Instead, he recommends managing portfolio composition and position sizing as risk mitigation tools.

Regarding founder quality and signals, Ganesan values what brings founding teams together, their self-awareness about strengths and weaknesses, and whether they're focused on building versus optics. He uses questions like "What would your five best friends say about you in three words?" to assess founders, and looks for alignment between self-perception and reference feedback as a sign of self-awareness.

On recent mega-acquisitions (AMD buying Xilinx, Meta acquiring Llama, Stripe buying OpenRouter), Ganesan contextualizes these within competitive dynamics and the small percentage these represent of trillion-dollar market caps. However, he cautions against assuming downside protection from strategic acquirers, noting that Nortel and Lucent's dot-com era acquisitions at billions of dollars didn't protect investors when the cycle turned.

Ganesan discusses LP concerns: they want smaller funds deployed quickly without coming back too soon, wants DPI returns before new fundraising, and increasingly need AI exposure to hedge their PE portfolios. He notes that Menlo's long history with Washington State Investment Board as an anchor tenant meant they never had to scale out of their natural LP base, though Menlo 9 and 10 (billion-plus dollar funds raised in 2001-2004) underperformed and caused LP churn.

On emerging managers in $30-100 million fund sizes, Ganesan acknowledges these are difficult market positions today, though exceptional investors like Sarah Guo and Dave Tisch have succeeded through outworking everyone else and strategic angel investing before their funds existed.

Finally, Ganesan addresses authenticity and privilege: he argues that morality becomes easier when you've already succeeded, and that being authentic costs money and people but aligns with true values. His foundational principle, borrowed from Reagan, is that there's no limit to what can be accomplished when you don't care who gets the credit—a philosophy he's applied throughout his career.