In the AI ​​era, a single seed can grow into a forest: Silicon Valley investment observation series

In the past, similar small companies, small tools, and long-lasting paid software were not entirely absent. Throughout internet history, there has always existed a group of "small but beautiful" software companies: they serve clearly defined users, solve specific problems, charge low fees, but survive for a long time. They may not enter the mainstream narrative or become stars chased by the funding market, but they are commercially viable. Why didn't this path become mainstream in the past? Because it demands too much from the founder's abilities, and external conditions don't support it. You need to understand the product, the technology, and the users, and be able to compress almost all functions into a very small team. In the past, this was more of a high-performing model than a replicable path for most startups. AI is changing precisely this. It doesn't replace the founder's judgment, but it greatly amplifies the founder's effective bandwidth. It makes "high-density entrepreneurship," which was previously only achievable by a select few, something more capable teams can do. Thus, for the first time, those small but powerful companies that relied on exceptionally strong individual abilities have the potential to become a more widespread entrepreneurial paradigm. More importantly, these companies have a new foundation in the AI ​​era: the cost of product development has dropped significantly, the cost of validating requirements has dropped significantly, the cost of operation and delivery has been significantly reduced, and small teams have, for the first time, the opportunity to have the driving force of large organizations. Because of these combined changes, we can say that Seed-Strapping is not a marginal alternative, but rather is very likely becoming the default path for a large number of startups in the AI ​​era. Not all companies will take this path, but more and more companies can. What kind of companies are more suitable for this path? This does not mean that "as long as it is an AI company" Seed-Strapping is a natural fit. On the contrary, while many companies can leverage AI to achieve results faster, they are not necessarily sustainable in the long run. Companies truly suited to this path typically share several common characteristics: they often serve a very specific type of user and a very clear set of needs; they don't focus on short-term novelty, but rather on highly engaging workflow products or services; their value isn't just about packaging model capabilities, but is built upon workflows, data, deliverables, and user relationships; and they have the opportunity to establish a preliminary paid loop and revenue quality very early on. In other words, these companies don't survive on grand narratives, but on stronger conviction. How long can these types of companies survive? This is a question that must be answered directly. The existence of Seed-Strapping does not automatically mean that these types of companies will all survive for a long time. On the contrary, we believe that these companies will undergo a very significant differentiation in the future. One type will disappear very quickly. These often remain at a shallow functional level, merely a lightweight wrapper around the underlying model capabilities. They appear to launch quickly and grow rapidly, but user relationships are shallow, substitutable, and revenue quality is weak. Once the model itself iterates, the platform entry point changes, or a stronger distribution party enters, the lifespan of these products is usually very short. Another type, however, may outlive many traditionally funding-driven companies. Because they serve long-standing needs, embed specific workflows, and sell results, not features; they don't rely on high growth for profit, but on low growth for survival; they don't prioritize scale before considering a closed-loop business model, but establish a foundation for sustainable operation from the outset. Therefore, the key to how long such companies can survive is not whether they are AI companies, but whether they have truly crossed the “model wrapping layer” and entered the “model wrapping layer”. text="">"Requirement rigidity + Workflow embeddingContinuous iteration