Blind constraints, not blind spots (gmays.com)

The recent discussion on AI application startups highlights a crucial decision point for founders: what type of projects to pursue. One viewpoint suggests that startups should "accept fate" and rely on luck, creating transient applications that may serve as acquisition targets, while the alternative emphasizes focusing on less attractive research problems overlooked by larger labs. However, the latter approach risks being unsustainable due to the rapid evolution of AI capabilities and shifting research priorities. Instead, the article advocates for addressing "blind constraints" rather than merely "blind spots." It suggests that founders should develop applications that leverage opportunities where foundational model providers have less incentive to innovate, such as scalable solutions that work across different models. An example given is Cursor, which navigates these gaps effectively. This approach not only fosters sustainable growth but also encourages innovation in a rapidly evolving AI landscape, underscoring the need for strategic foresight in a time of extensive technological possibilities.