Math might be the last programming language AI hasn't conquered.

In this episode of First Commit, Eliya Elon and Laura Hamilton sit down with Carina Hong, founder and CEO of Axiom, the company building an AI mathematician — and, fresh off a $200M Series A at a $1.6B valuation led by Menlo Ventures, one of the most-watched bets on "verified AI." Hong leaves a Stanford PhD in March 2025 to chase a specific window: reasoning models maturing, coding capability compounding, and the formal-proof language Lean finally becoming robust enough for industry-scale work. While frontier labs skip formal math as too data-scarce to bother with, she bets the opposite — that math is special, that it transfers the way code does, and that a system which proves its own work is worth building long before anyone is paying attention.

Join us as we explore:

Formal vs. informal AI: A model that answers in Lean can be verified by simply running the program — Hong explains why that guarantee changes everything you can build on top of it.
Where proofs pay off: Chip design, software verification, and cryptography get tractable the moment a plain-English spec becomes something you can actually prove.
Research taste as strategy: Hong hires across mathematicians, formal-methods veterans, and young high-agency engineers, and makes the case that taste is the one thing a research org can't get wrong.
The founder's obsession: The "I couldn't do anything else" moment, plus her theory on why cheap capital fragments a field instead of cracking it.

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