I’ve been thinking a lot lately about how picking startups is getting harder and harder as a VC in the AI era, especially in the learning space. The high volume of AI-powered education solutions is mind-blowing.
So what really matters now?
Disclaimer, I don’t have the perfect answer as I’m trying to figure things out but in a world where everyone’s using the same models, surfing the same wave and building with the same tools, you need to look for other signals.
– Not the tech.
– Not the prompt engineering.
– Not the fancy wrapper.
In the learning space, what *might* help win is:
1. Trust + brand: Institutions don’t adopt “AI” -> they adopt companies they trust. This is especially critical when dealing with sensitive student data.
2. Distribution: Embedded in the LMS? Default in the school/uni/companies workflows? That’s potentially gold. Think seamless integration, not another add-on.
3. UI/UX: The interface IS the product. If it’s not intuitive and engaging, even the smartest AI will see low engagement.
4. Vertical specialisation: AI that understands the job (trainer, teacher, tutor) beats generic copilots every time (for now). Deep domain expertise matters.
5. Shipping velocity: Generally speaking, we’re past the model wars. We’re in the execution era and the teams need to ship on a daily basis. Iterate, improve, repeat.
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