Daniel Kronovet is a 📝New York City, NY-based 🏷️#software-engineer working in 📝Machine Learning (ML). He works at Thesis Driven: a colleague's post calls him the company's CTO, and another describes him as a senior machine learning engineer helping lead Corollary, Thesis Driven's media-led capital markets arm. His profile sums up his work as building "the technical and governance systems that make organizations work."

Kronovet earned a Master of Arts in Quantitative Methods in the Social Sciences from Columbia University (2014–2016), focusing on statistical methods and machine learning, with a thesis titled "An Analysis of Pairwise Preference." His profile also lists Phi Beta Kappa induction at UC Berkeley. Before Thesis Driven he worked at Cartridge, where recommendations credit him with developer-facing content, hackathons, and an AI-powered documentation pipeline. He founded Sage House, a nine-bedroom coliving house in 📝Highland Park, CA founded in September 2022 as the first of 📝Zaratan's planned community houses. He has presented Chore Wheel, the house's suite of governance mechanisms for chores, reputation, and shared purchases, at Metagov seminars. With Seth Frey and Joseph DeSimone he co-authored 📝Cybernetic Governance in a Coliving House (2024), an 18-month field experiment in running a Los Angeles coliving house without managers.

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