Sep 16, 2024, 10:19 AM ETInterview, Fireside Chat

Shardul Shah: How Index Makes Decisions & Why Benchmarks & Averages in VC are BS | E1202

Reject "Cute" Pricing: Avoid being clever or strategic on valuation; high conviction should drive pricing decisions regardless of initial cost basis.
TAM is a Trap: Founders often underestimate market potential; the largest public companies often grew beyond their initial Total Addressable Market (TAM) estimates.
Power Law Dominance: Investment returns are concentrated in a few outliers; the primary business goal is finding "fund returners" (companies capable of $10B–$100B valuations).
Founders First: The team is the most critical selection criterion across all stages, as exceptional founders will find and expand adjacent market opportunities.
Sins of Omission: Missing generational founders or underestimating them is more costly than making a wrong investment ("sins of commission").
Intentionality & Focus: Success requires deep focus on the "main thing," prioritizing high-conviction opportunities over broad diversification.

Intuition vs. Analysis: Decisions rely on a blend of evolved intuition (a "feeling" of conviction) and rigorous analytical frameworks (imagination, operational excellence, high-quality decision-making).
Re-investment Process: Doubling down on winners requires rebuilding the investment case from scratch (new financial models, customer calls, competitive analysis) to distinguish conviction from delusion.
Stage Agnosticism: Unlike most firms, the strategy invests across seed, venture, and growth stages, requiring mental plasticity to evaluate high-conviction bets with varying data maturity.
Price Elasticity: Early-stage prices are elastic based on team conviction; late-stage prices must represent future expected free cash flows and are rarely "wrong" if the underlying investment thesis holds.
Risk Tolerance: The firm accepts market timing and sizing risks but prioritizes execution risk and team capability; they do not seek average returns or "safe" 2x outcomes.
Data vs. Founder Quality: Even at late stages, the core thesis relies on the team's ability to navigate uncertainty rather than static market data.

Authenticity Over Assimilation: Employees should not adapt to firm norms to climb the ladder; the goal is for individuals to be their best selves within a culture of belonging.
Mentorship & Apprenticeship: Career progression is driven by mentorship and solving problems (e.g., "plate removing" via diligence) rather than political maneuvering.
Conviction Building: A culture of "agreeable disagreements" is essential; partners must challenge each other vigorously while maintaining mutual respect and trust.
Meeting Efficiency: Default meeting times are reduced (30 mins) to force preparation and leverage team time; meetings typically require two attendees to justify the time commitment.
Global Collaboration: Hybrid/remote decision-making allows for unique perspectives (e.g., reading body language on Zoom) but requires managing time zone logistics (e.g., 10-hour difference between NY and London).
Boardroom Dynamics: Effective board service involves "holding up a mirror" to founders to reflect their own conclusions, rather than offering unsolicited advice or ego-driven interventions.

Datadog & Wiz: Both companies were invested in at high prices early on; the firm maintained conviction despite skepticism, resulting in significant returns.
CrowdStrike Miss: The firm missed CrowdStrike due to overthinking the endpoint security market (predicting commoditization by Chromebooks/MacBooks), a mistake attributed to dismissing the founder as a phenom.
Cybersecurity Market: The firm acknowledges the category as a trillion-dollar opportunity driven by AI and cloud spend, with security expected to represent 5–10% of total cloud spend.
Biotech Exclusion: The firm avoids binary, highly capital-intensive biotech drug discovery due to the risk profile and lack of control over scientific outcomes.
Public Market Dynamics: Despite revenue multiple compression and higher Series B entry prices, the firm argues that the best companies still command premium multiples and represent the only viable path to outsized returns.

Retail vs. Institutional: The industry is bifurcating between "Chanel/Walmart" (highly constrained, boutique funds) and "Walmart" (massive capital pools like Andreessen Horowitz, Sequoia, Index).
Sector Shifts: Venture capital is increasingly moving into defense, healthcare (25% of Series A in NY), and physical infrastructure, distinct from the SaaS dominance of San Francisco.
AI as Catalyst: Artificial Intelligence is acting as a draft that accelerates existing market trends and enables investment in new verticals.
Founder Capital Needs: The firm acknowledges that some founders cannot raise capital or grow fast enough to overcome capital intensity, leading to potential failures despite strong initial convictions.

Signaling Strategy: Multi-stage funds should offer to underwrite the entire round but split it into sleeves (fund, seed, angel/operator) to provide value and optionality without signaling constraints.
Angel/Operator Composition: Angel sleeves should prioritize functional expertise (distribution, product engineering) over mere capital, avoiding "party rounds" and limiting the number of members to prevent "herding cats."
Fundraising Evolution: Being a great fundraiser is often a learned skill that evolves post-Series A; the best founders do not necessarily begin as top fundraisers.
Exit Timing: The firm generally adheres to a "buy and hold" strategy for power-law contributors, distributing proceeds to LPs once the investment thesis is realized or if the founder becomes unethical/incompetent.
Avoiding BS: The most frustrating phrase in venture is "exceptional founder" without specific, substantiated evidence of why.