Why so many AI startups look the same in investors' eyes - Economyup
Summary
The article explains why many AI startups look similar to investors because they build on the same foundation models, interfaces, and go-to-market patterns. It argues that wrapper-style products face growing pressure as model vendors improve their own offerings and absorb adjacent use cases. The piece highlights which AI companies still stand out: those with narrow workflows, deep enterprise relationships, proprietary data, or operational trust in regulated environments. It also says the classic SaaS moat from code volume has weakened because small teams can now recreate products much faster. For founders and investors, the key question is no longer how much software exists, but what proprietary context, data, and workflow value the product accumulates over time.
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