Active Theses

Thesis 01
Defense Tech Is Entering Its Growth Phase

Anduril was the spearhead. They beat the legacy primes in an open market on price and speed without a government carve-out, and that's the piece you can actually replicate. Ukraine did the other half. When a $500 FPV drone can take out a $5M platform, the cost curve of warfare has flipped, and the DoD can't outspend that asymmetry. They have to out-build it. The culture moved last. Defense went from career-ending to fundable almost overnight, and the best engineers are actually in the room now. I spend most of my time on two things: autonomous systems, where hardware and software are really one problem, and the mission software that turns raw sensor feeds into decisions while they still matter.

Defense Autonomy Mission Software
Thesis 02
Longevity Hasn't Started Yet

Longevity has spent the last decade as a fringe topic for centenarians and biohackers, and the real product category — proactive medicine for healthy people — barely exists. GLP-1s cracked it open. For the first time the public watched a drug move the aging curve instead of just treating a symptom, and the cultural permission to spend on staying biologically younger went from vanity to legitimate almost overnight. Continuous biomarker tracking is getting cheap, AI is compressing the discovery cycle for compounds that target aging mechanisms directly, and the consumer is finally willing to pay for healthspan instead of waiting to be sick. Pharma's century-old loop — wait for disease, sell treatment — is the wrong shape for this market. I spend most of my time on two pieces: the data layer, where continuous biomarkers and AI interpretation turn a single user into a longitudinal trial, and the consumer health companies that own the patient relationship before the legacy system knows the patient is there. The TAM isn't a vertical, it's every human who ages — that's the trillion-dollar piece nobody has priced in yet.

Longevity Healthspan Consumer Health
Thesis 03
The Margin Moves to the Edges of the AI Stack

The AI conversation is stuck on the model layer, on the assumption that whoever trains the biggest model wins. That assumption breaks. Foundation model performance is converging, and the cost of serving a token drops every quarter. Capital floods the middle. Margins compress. The interesting positions are at the edges. Below the model, the constraint is physics. I've been tracking silicon photonics for years, well before the AI cycle pulled focus to it — at 800G interconnect speeds, the rack becomes the bottleneck before the GPU does. Above the model, the constraint is integration. A probabilistic system needs an ontology and an evaluation layer that takes a decade to build, and the companies that have it sit in the wrong analyst bucket today. I spend most of my time on two pieces: the physical-layer companies solving interconnect and packaging, and the system-layer companies that own the data on top of whatever foundation model wins. The model is the visible piece. The business is everything around it.

AI Infrastructure Photonics Enterprise AI
Thesis 04
Stablecoins and Agents Are the New Payment Stack

The fintech infrastructure cycle was waiting on two things: regulatory clarity and a payments primitive built for software instead of humans. Both arrived in 2025. The GENIUS Act gave payment stablecoins a federal framework, and the CLARITY Act finally drew the line between what's a security and what isn't — the ambiguity that kept institutional capital on the sidelines for the better part of a decade. Stablecoins are no longer a workaround. They're a sanctioned settlement layer that clears in seconds and costs basis points instead of percentage points. The other half is what gets built on top. Coinbase's x402 protocol revives the dormant HTTP 402 status code so an AI agent can pay for an API call, a piece of data, or a service the same way it makes any other request. That's the missing primitive for agentic commerce. Card networks and ACH were designed around a human pressing a button — they break the moment the buyer is software making thousands of micro-decisions a second. I spend most of my time on two pieces: the issuance and orchestration layer for stablecoins moving between enterprises, and the protocols that let agents transact natively without a human in the loop. The first fintech wave digitized banks. This one builds the rails for a buyer that doesn't have hands.

Stablecoins Agentic Payments Fintech Infrastructure

Conviction Bets

Before I had access to private markets, I used public equities as my research lab. Every position started with a thesis — these are some of the bets I've made.

Company
Entry
Status
Thesis
Palantir
~$20 (Jun 2024)
Held
NVIDIA was running and I kept asking who the software equivalent would be. Palantir's Ontology layer is basically the OS for enterprise AI agents, and nobody else has it. Every analyst report I read grouped them with Zscaler and Cloudflare, which makes no sense — those are cybersecurity companies. Watched AIPCon 4 and 5 on YouTube and saw real enterprise adoption, not demos.
Rigetti Computing
~$2 (Nov 2024) → ~$32 (Sep 2025)
+16x (Exited)
Went through every public quantum computing company over a few weeks. Rigetti had the best team, all Bay Area, strong scientific founders, and a vertically integrated architecture most competitors don't have. Stock was cheap at $2 so I bought. When Google dropped the Willow chip, I doubled down, figuring sector attention would lift all boats.
POET Technologies
~$7 (current)
Held
I kept reading about GPU scaling and couldn't figure out why nobody talked about what connects them. At 800G the transceivers hit physics problems that discrete lasers and modulators can't solve. POET integrates the whole engine onto one chip, and a couple hyperscalers are already piloting them. Analyst reports still bucket POET with generic semi names that don't describe what the company actually does. Bought at $7. Small cap and illiquid, but the interconnect layer is real and nobody's priced it in.
HIMS & Hers
Researching
I keep coming back to longevity, and HIMS is the part I'm stuck on. Pharma's moat used to be discovery and patents. If AI compresses discovery timelines the way I think it will, the patents matter less and the patient relationship matters more. HIMS is the only DTC health brand I can name with a real install base at that kind of scale. Still diligencing. Two things I can't answer yet. Whether the retention numbers are actual network effects or just subscription stickiness with a good story on top. And what HIMS has in five years that Amazon Pharmacy or a pharma-owned telehealth arm can't just build. No position yet.