Successful investing is a psychological tightrope. It demands the arrogance to believe you can outperform the market, which fuels conviction. Simultaneously, it requires the humility to change your mind, cut losses, and avoid the catastrophic blow-ups that unchecked arrogance can cause.
Unlike past panics in sectors with tangible assets like banking, the SaaS panic is unique. AI can quickly erode the intangible value (code, contracts) of software companies, potentially leaving equity holders with nothing. This makes "buying the dip" exceptionally risky.
Dismissing AI's current capabilities is a mistake due to its exponential improvement rate, evidenced by rapid advances in video generation. Markets selling off established companies based on nascent AI competitors are rationally pricing in this non-linear progress, rather than overreacting.
To gauge AI's true impact on SaaS giants, ignore their slow-to-change enterprise customers. Instead, analyze the adoption patterns of new, small companies. If startups are skipping established SaaS platforms for AI tools, it signals a bottom-up disruption that will eventually reach the enterprise.
Investors fleeing to hard assets like energy for safety from AI are ignoring second-order effects. AI's problem-solving capabilities could lead to breakthroughs, such as in battery technology, which would disrupt the very "safe" assets investors are buying by making renewables more viable.
Just as YouTube lowered media distribution costs, AI is lowering software development costs. This could shift the SaaS market away from large, one-size-fits-all platforms toward a model where small, elite teams deliver highly customized software solutions directly to enterprise clients.