The Big Y #301
Specialization in trouble
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While we have the AI giants, there has also been a flood of successful AI startups who have worked to find their niches within a crowded space. But what happens as LLMs become increasingly capable generalists? With the improvements of connectors, MCP, and agents, specialized startups are on edge as their moats could be drying up while competing against AI platforms that are connected to enterprise data. A lot of startups need to figure out whether or not their entire business is just a feature or if it’s an actual product.
For a while, specialized startups could rely on proprietary data giving them an edge. Now, the combination of synthetic data, context window expansion, and the fact that large models can “reason” their way through a medical or legal document using general logic, makes the proprietary data moat weaken immensely. Updated integrations coupled with general model improvements creates a rough environment for the startup world.
Right now, my inbox, calendar, and docs are connected with my favorite AI, meaning that I don’t need any startup products for e.g., calendaring. These specialized companies need to remain a step ahead, and for now, I think that means integrating into complex, legacy systems. It’ll be important for them to get deeply integrated into existing systems so it’s not a quick rip-and-replace motion when the generalized AI models creep into their space.
The Tidbit: Moltbook, an AI agents only social forum, took the internet by storm. Turns out even though humans were restricted to be observers only, most of the agents on the forum were puppeted by human users with a small number of people actually running most of the viral gimmick. While the idea of an AI agent only forum will likely come to fruition at some point, it wasn’t quite there this time around.
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