Many tech stocks appear cheaper after market corrections, but massive stock-based compensation (SBC) creates significant, ongoing shareholder dilution. This hidden cost means the underlying businesses are not as inexpensive on a fundamental basis as their stock prices suggest.
The 2024 SaaS sell-off was driven by sell-side analysts setting unrealistically high growth forecasts for large incumbents. When companies inevitably decelerated, analysts lowered numbers, causing a sell-off. The cycle will reverse as companies beat these lowered expectations.
Companies with significant debt lack the cash flow to invest in transformational technologies like AI. This makes them highly vulnerable to disruption, similar to how leveraged retailers like Sears failed against innovators like Walmart during the e-commerce boom.
While investing (buying) gets the attention, the actual job of a VC is disciplined selling to return capital to LPs. This requires constantly re-underwriting positions to determine if they can still meet the fund's target returns from their current valuation, rather than holding on indefinitely.
Emerging VC funds can sell small portions of their winning investments without creating the negative market signals a large fund like Sequoia would. This allows them to return capital (DPI) to LPs sooner, a crucial factor in securing their next fund in a DPI-focused environment.
An estimated 60% of VCs harm their portfolio companies by pushing a 'burn at all costs' mentality or pretending to know how to run the business. The best VCs are humble connectors who link founders with people who have successfully navigated similar growth stages before.
A major second-order risk of the AI boom is local community backlash. Towns hosting data centers may revolt against tripled power prices and environmental concerns, especially when the facilities provide few long-term local jobs while creating billions in wealth for coastal elites.
The key indicator of a healthy SaaS business is Gross Dollar Retention (GDR), which measures retained revenue from a customer cohort before upsells. Companies with 95%+ GDR can grow efficiently, while those below 90% become 'living dead' as they constantly spend to replace churned customers.
While the US faces power constraints, China can build new energy sources like nuclear power plants in just a few years. This ability to rapidly scale power gives it a fundamental, underappreciated advantage in the energy-intensive AI war, alongside its talent pool and government support.
Extreme volatility in public tech stocks, where market caps can swing wildly disconnected from performance, incentivizes successful late-stage companies like Canva and Stripe to delay IPOs. This directly worsens the VC industry's liquidity crisis by trapping capital for longer.
The most significant, world-changing AI companies have likely not been founded yet. Similar to how social media was an unknown concept during the dot-com boom, the true AI giants will emerge over the next 2-5 years, capitalizing on second-order effects and new platforms.