The AI Hype Filter: What’s Real, What’s Investable, What’s Noise?

Your code and data are no longer defensible moats. Venture capitalists explain what truly creates a competitive advantage in the age of AI.

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How venture capitalists use AI for deal sourcing

VCs leverage AI to analyze diverse data sources like company registries, GitHub, and LinkedIn to identify promising investment opportunities earlier.

#2about 4 minutes

Finding defensible business models beyond software

As AI commoditizes software, defensibility shifts from code to moats like open source communities, strong brands, and rapid go-to-market execution.

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The strategic value of vertical AI solutions

Verticalization in AI allows for superior user experience and deep domain context, creating stickier products than broad horizontal platforms.

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How AI forces portfolio companies to adapt

AI acts as both an accelerator for new companies and a disruptive force for established ones, requiring them to reinvent business models to survive.

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Looking past the hype to find real AI opportunities

Investors are focusing on startups that solve tangible business problems rather than chasing fleeting trends and buzzwords in the rapidly changing AI landscape.

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Navigating AI regulation and open source

While regulation like the EU AI Act is debated, Europe's strength in open source AI models offers a path to building foundational infrastructure.

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The most critical metrics for investing in AI

Beyond revenue, investors evaluate AI startups on commercial traction, user adoption rates, and the founding team's ability to build trust with customers.

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Common red flags in an AI startup pitch

Investors are wary of pitches that promise a one-size-fits-all solution, lack a clear defensible moat, or hide behind abstract promises instead of pragmatic plans.