AI Startup Trends: Insights from Y Combinator’s Latest Batch

Disruption Theory & risk-aversion don’t apply

Incumbents typically cede market space to startups wherever there’s new, unproven technology or a new, unproven market, especially in spaces where they can’t use past data to predict the future. But in AI, they’re rushing to embrace new technology and uncertain markets, spending historic amounts of ... See more

Sobriety source #2: AI as the next platform shift. Every wave of new companies that transforms their respective industries is fueled by a major platform or technology shift. The advent of the web did this. The smartphone and mobile applications did this. And there is no doubt that AI is our next wave. But does every new wave always necessarily favo... See more

The moats are in the customers, not the data. We predicted that the best generative AI companies could generate a sustainable competitive advantage through a data flywheel: more usage → more data → better model → more usage. While this is still somewhat true, especially in domains with very specialized and hard-to-get data, the “data moats” are on

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Many of the largest scale uses of AI to date have been at consumer-centric companies that have large data sets to train on (Google, Facebook, Uber, etc). Perhaps incumbents won due to a data advantage that is now going away as companies use the broader internet as an initial training set + are switching to models that work more robustly against sma... See more

Workflow+model startups will win by combining a fine-tuned model with deep customer insight to build an AI-native workflow. These startups will be particularly well-positioned to win in one of the following 3 scenarios:

1. Incumbent saas players do not have legacy workflow dominance in that vertical


2. An AI-native workflow solves the most critical creativ

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