The Recommendation Engine for Commodity Traders — Anekha Sokhal, Moshi

When Anekha Sokhal traded energy derivatives, staying on top of the market meant tracking more information than any person could read. Now, as CEO of Moshi, she is building the tool she wished she had: a recommendation engine that connects market information to what matters for a trader’s book. At AI Engineer New York, Anekha joins swyx to discuss her path from mathematics and JPMorgan to founding Moshi, and why useful AI needs to fit the way people actually work. She describes Moshi as what might happen if Bloomberg, Claude and Netflix had a baby: market data, an interface for working with it, and recommendations tailored to the trader. They also talk about trusted sources, document extraction, building versus buying models, and the pressure on AI engineers who are told, “you are the team.” Anekha shares what she learned from customer conversations at the conference and why meeting users comes before hiring. Automated transcript; wording may contain errors. Speaker labels are omitted. 0:00 So I’ve actually extended my stay in New York, because we’ve like now, I was meant to leave today. We’ve now got meetings on Thursday, extended it another day, Friday, extended it another day, Monday. And then…