GenAI Secret Sauce

Note to the reader: This is a repost from LinkedIn

The real secret sauce in AI startups and products? Not code, but gold-standard evaluation data.

Just listened to YC’s Lightcone podcast where YC folks gathered insights about the AI revolution.

One founder revealed that might seem counterintuitive (around 8-minute mark): the most valuable asset his company built wasn’t their codebase—it was their evaluation dataset. The carefully labeled “gold standard” that defines what correct AI outputs should look like.

This resonates deeply with me. In a world where models are becoming increasingly commoditized and accessible, competitive advantage isn’t just about which model you use, but how impactful your use case is and how you’re applying these models to solve that use case. The secret sauce to creating the best application is how well you can measure and improve its performance for your specific use case.

“Anybody has access to the models, but nobody has the eval set.” That’s the moat many aren’t seeing.

Building AI products is more about creating these proprietary datasets to guide your systems to deliver tangible value.

https://www.youtube.com/watch?v=0LMK5JYkB94