Kumar Garg is President of Renaissance Philanthropy, the science-and-technology philanthropy he co-founded with Tom Kalil in 2024 to help donors invest in high-impact research across AI, climate, and education. He holds a BA from Dartmouth and a JD from Yale Law School, and cut his teeth over eight years in the Obama White House Office of Science and Technology Policy, where he led the administration's STEM-education agenda — including the "Educate to Innovate" campaign that mobilized more than $1 billion in philanthropic and in-kind investment, and the White House Science Fair.

Before Renaissance, he spent nearly six years (2018–2024) as Vice President and Managing Director at Schmidt Futures, the philanthropic initiative of Eric and Wendy Schmidt, where he built much of its science, talent, and education portfolio and launched the Learning Engineering Virtual Institute (LEVI). He is one of the principal architects and evangelists of "learning engineering" — the idea that instruction should be treated as a systems-level engineering and data challenge — and delivered Carnegie Mellon's 2022 Simon Initiative Distinguished Lecture, "Shaping the Field of Learning Engineering." Today, Renaissance runs a DARPA-inspired "fund model" that raises capital against well-scoped three-to-five-year technical bets, from doubling middle-school math outcomes for low-income students to catching early-reading difficulties before third grade.

In this episode, Kumar talks with Svenia Busson about:

  • The Renaissance "fund model" — how naming a bottleneck, recruiting a technical lead, and raising from donors like an investor raises from LPs unlocks three-to-five-year breakthroughs
  • Why environmental factors like lead poisoning and classroom air quality may drive learning outcomes as much as pedagogy — and can move a child 10+ IQ points
  • Learning engineering explained in plain language — the four always-running loops of learning science, design, instruction, and the individual learner
  • LEVI Math's north star — doubling the rate of middle-school math gains for low-income kids at under $1,000 per student, down from the $4,000 high-dosage tutoring benchmark
  • The LEVI Literacy Initiative — using AI as a diagnostic screener, not a teacher, to flag dyslexia and speech errors in the K–2 window
  • "Dynamic dosing" and the human + AI tutoring triangle — why teachers and tutors enhance, rather than compete with, AI tools
  • Building rigor into edtech — the Tools Competition's research-partner requirement and ending moonshots with published RCTs
  • Why the advanced AI-and-education world is "shockingly small," and how DARPA-style active program management grows it


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