In finance, 95% accurate means 100% wrong.
Apoorv Saxena has built AI at three of the most consequential institutions in technology and finance: at Google (under Fei-Fei Li), JPMorgan under Jamie Dimon, and Silver Lake alongside Egon Durban.
Each experience taught him something about where the technology actually breaks - and works.
In this amazing conversation, Apoorv shares lessons from some of the great modern leaders in business on how to actually put AI to work. And his own vision for why agentic AI is so important to what comes next.
At JPMorgan, Dimon personally spent three hours in a room questioning first principles. Not testing anyone - genuinely probing where it falls apart. At Silver Lake, Apoorv ignored the playbook entirely and bet everything on one portfolio company before hiring a single person.
That experience is what Obin AI was built on.
This week they came out of stealth, backed by Motive Partners with Fei-Fei Li as advisor:
In this episode of the Modern Capital podcast, Apoorv and Marc cover:
What JPMorgan taught him about the difference between AI that delights and AI that can be trusted with a $200M decision
Why the peanut butter approach (50 use cases, 10% productivity gains, great slide) destroys value instead of creating it
The Silver Lake playbook: one portfolio company, no hires, prove it works first
Data readiness: why the buried knowledge in your deal rooms, IC memos and credit agreements has to be unlocked before any agent can work
The agentic workforce: not tools, not chatbots - agents that understand how your firm makes decisions and manages risk
Why the firms that win won't be the ones that move fastest, but the ones that build the right foundations in the right order
"When you have transformational technology, incrementalism is a death spiral."
Listen to the full conversation here, on Spotify or Apple Podcasts.
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