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18:56EN
AI Engineer· 27 oct 2026John Feminella: Five Controls for AI Agents, and the $900 Million Bank ErrorJohn Feminella · Two SigmaA payment mistake shows why good intentions and approval prompts are not enough. Feminella describes practical controls for giving agents useful autonomy.
23:22ENAI Engineer· 27 oct 2026Noyan Tokgozoglu: How Optiver Builds an AI Platform for Fast, Measurable DecisionsNoyan Tokgozoglu · OptiverThe trading firm’s AI engineering lead explains same-day model adoption, on-premises infrastructure, cost controls and the limits of replaying agent evaluations.
20:58ENAI Engineer· 25 oct 2026Vinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.
18:31ENAI Engineer· 25 oct 2026Janie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.
26:41EN
Latent Space· 22 oct 2026Pódcast · 2 vocesAnekha Sokhal on Moshi, a Recommendation Engine for Commodity TradersInvitado: Anekha Sokhal · Presenta: swyxThe Moshi founder tells swyx how she would rebuild a trader’s workflow: connect market data, private files and conflicting sources, then push the second-order effects people would otherwise miss. The hard part is not the dashboard. It is getting someone to actually use it.