AI Founder's Bitter Lesson. Chapter 2 - No Power

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2025-01-15 17:30:35

AI history teaches us a clear pattern: solutions that try to overcome model limitations through domain knowledge eventually lose to more general approaches that leverage compute power. In chapter 1, we saw this pattern emerging again as companies build vertical products with constrained AI, rather than embracing more flexible solutions that improve with each model release. But having better performance isn’t enough to win markets. This chapter examines the adoption of vertical and horizontal products through the lens of Hamilton Helmer’s 7 Powers framework. We’ll see that products built as vertical workflows lack the strategic advantages needed to maintain their market position once horizontal alternatives become viable. However, there’s one critical exception that suggests a clear strategy for founders building in the AI application layer.

As chapter 1 showed, products that use more capable models with fewer constraints will eventually achieve better performance. Yet solutions based on current models (which use engineering effort to reduce mistakes by introducing human bias) will likely reach the market first. To be clear, this post discusses the scenario where we enter the green area of Figure 1 and whether AI verticals can maintain their market share as more performant horizontal agents become available.