What Does it Take to Be Good at Series A and B Today?

Current Market Dynamics:

• The venture sector is currently in an "AI bubble" where capital deployment has doubled from Q1 to Q4 2023, with AI receiving the vast majority of funding while other categories face neglect.
• Venture is simultaneously the most expensive time to invest (high valuations) and the hardest time to exit (IPO window is closed, M&A spigot is frozen), creating a "low/low" quadrant where liquidity is constrained.
• Some investors describe the current environment as a "gold rush" surpassing the intensity of 2021, characterized by rapid valuation jumps, high-speed revenue scaling, and entry by non-traditional players (e.g., high school students).
• Conversely, other investors view the current pace of deals with skepticism, noting that "shocks" from market downturns no longer last more than a few days due to the overwhelming momentum of the AI trend.

Investment Strategy & Risk Assessment:

• A divergence exists between "megatrend" investing (AI, defense) and "deep value" investing (digitizing B2B sectors like petrochemicals or concrete, where penetration remains under 1%).
• Investors express concern over "orthogonal risk," where model companies (e.g., OpenAI) could rapidly disrupt startup stacks, rendering specialized AI tools obsolete overnight.
• The "Series B price for Series A risk" dynamic has migrated to the Seed and Series A stages, significantly narrowing the margin for error in deal selection.
• One strategy to manage IRR degradation involves selling winners via secondary markets before they reach maximum valuation, effectively "anti-VCing" by taking profits early rather than holding for long-term multiples.
• Another view holds that holding winners longer is superior, as compounding over time (even with delayed exits) is the only way early-stage portfolios generate sufficient returns to offset failures.

Founder & Leadership Trends:

• There is a growing recognition among founders that the 15-20 year private holding period is unsustainable, leading to earlier CEO transitions post-IPO (or pre-IPO) to manage the "terminal decay" associated with longer public company tenures.
• The "20% growth club" mentality is viewed negatively; investors are actively seeking "deranged," obsessive founders who reject incremental growth targets in favor of exponential scaling.
• Incumbents (e.g., ServiceNow, Box) are leveraging AI to re-accelerate growth, with the market favoring deep vertical solutions over horizontal platforms that lack specific domain expertise.
• A potential structural shift is anticipated where the lifecycle of a software company (technological obsolescence) becomes shorter than the average holding period of a privately held company, forcing existential reinvention cycles every 5-7 years.

Geopolitical & Ethical Considerations:

• Investing in Chinese AI companies presents significant political, regulatory, and liquidity risks, leading many firms to decline such deals despite high potential financial returns.
• Defense technology is emerging as a "megatrend" with existential urgency, particularly regarding cost-per-kill (CPK) metrics and the need for scalable, low-cost manufacturing capabilities in the West.
• A consensus exists that Ukraine's defense startups are critical for building a cost-effective manufacturing base to deter potential conflicts with Russia or China.

Global Talent & Operational Pace:

• A sharp debate highlights the performance gap between US-based teams and European teams, with investors arguing that the 100x productivity multiplier of AI favors hyper-aggressive, office-centric cultures over the "baguette culture" of slower-paced European workweeks.
• Investors predict that AI will eliminate 50% of current sales and customer success roles while simultaneously increasing the value of top-tier engineering talent (from 10x to 100x).
• While European engineering talent is cheaper and retains better, investors contend that the pace of innovation in the US remains unmatched, making the US the only viable location for scaling to $100M+ revenue.

Future Outlook & Valuations:

• The consensus among LPs is that if the lack of liquidity is a permanent structural shift, capital will eventually withdraw from private markets, forcing companies to IPO earlier than they currently choose.
• Valuation inflation in the AI sector has decoupled traction from pricing, with some companies raising funds at $300B valuations despite burning significant cash, creating a risk of value destruction if dominant winners fail to emerge.
• Investors are adopting a "wait for the winner" approach in crowded AI categories, preferring to pay up only when a clear market leader emerges rather than betting on the "next best thing" in a saturated field.
• The "cost of capital" arbitrage between public and private markets is expected to normalize only when private capital becomes expensive enough to force companies toward IPOs.