The Recommendation Engine for Commodity Traders — Anekha Sokhal, Moshi
Former commodities trader and Moshi founder Anekha Sokhal sits down with swyx at AI Engineer NYC to explore how AI-native systems are modernizing commodity trading. They discuss combining the strengths of Bloomberg, Claude, and Netflix-style recommendation engines, resolving conflicting market intelligence, and the mounting organizational pressures on AI engineers.
- Former commodities trader Anekha Sokhal built Moshi by pairing Bloomberg market data depth with Claude text comprehension and a Netflix-style recommendation engine. Read →
- Executive teams are cutting engineering allocations under the assumption that AI tools allow one developer to build systems that previously required ten people. Read →
- Most software pipelines average conflicting data feeds into a single consensus number, which hides real market risk. Read →
- Commodities trading desks make decisions by pairing public pricing feeds with strictly private operational data, such as tracking LNG tankers through the Strait of Hormuz. Read →