Eric Woo, CFA
The future will be powered by skill libraries and AI agents that run businesses while you sleep. So how does a quarter-century of lived work experience fit into this new paradigm?
The AI-native world, in three layers · core to crust
I've spent over a quarter-century collecting tough lessons across venture capital, capital markets, and startups, now mapped onto the three layers of a world that runs on AI. Pick a layer of the sphere to see how the pieces translate.
The long version
An engineer's systems mindset: interfaces, constraints, and failure modes. I never practiced engineering formally, but it is the habit of thought underneath everything that came after.
Primary and secondary research on startups and venture firms. I called around 50 companies a day to extract information by hand. The research-and-extraction problem AI now automates, lived firsthand, so I know exactly where it breaks.
Pricing models for insurance, and the risk and valuation of CDOs. Financial engineering at its best and worst: modeling in practical language with real-dollar stakes. The closest thing to coding without software.
The bridge between pricing search keywords and writing the ad copy. Campaigns, digital marketing, and measured ROI. Where my brand and design sensibility come from, and the measure-iterate-prove loop that every AI deployment needs.
Back office first: fund accounting, auditors, and option-pricing valuations. Then an investing role focused on emerging managers, where I helped deploy $50M across funds and co-investments, plus fundraising, and I hired my first analyst. Front office and back office, both learned in full.
My first run at building my own firm. An intended emerging-manager fund-of-funds I worked to stand up between Northgate and Top Tier: sourcing managers, shaping the strategy, and raising the vehicle. The formative lesson in what it takes to launch a fund from zero.
Senior roles: portfolio manager, and ran the entire analyst program. Helped deploy $100M in fund commitments, was active in fundraising, and closed a large Korean pension fund as an LP. Learned to think like an owner and to see capital flows end to end.
Product and data lead for the family-office network and community, with a firsthand view of data across thousands of positions. Product management and database thinking at scale, for the exact audience I serve now.
Built a venture-data and ratings company. Started with rating reports, then moved into portfolio management. Six years in the trenches, a dozen people at peak, raised venture capital, and exited via M&A. I ran every function by hand. Agent orchestration is that same one-person setup, automated.
Now
A few things I'm digging into right now. Nothing here is set in stone.