For Crypto Product Teams
I ship products end-to-end.
I combine product sense, technical depth, and crypto-native operating context. At GG Labs, I led onboarding around Steam integration and a domain-driven architecture built to support feature layering without breaking the core flow. I've also shipped onchain products and contracts and built an LLM-driven trading system with a separate Rust risk engine because guardrails matter as much as ideas.
to Web3 at GG Labs
product and GTM
shipped from 0→1
How I help product teams
0→1 product shaping. I can help turn an idea into a clearer product surface, sharper scope, and a technical plan that respects how crypto systems actually behave.
Spec-to-shipping translation. I work comfortably with engineers because I can get specific about architecture, tradeoffs, and failure modes without pretending every problem is solved by more process.
GTM and growth context. I have onboarded users, built communities, handled partnerships, and raised capital, so product choices stay connected to the real adoption loop.
Proof of range
Rialto. LLM reasoning pipeline for crypto trading, separated from deterministic execution and risk controls.
GG Labs. Product-led onboarding for 20K gamers entering web3, including Steam integration, wallet abstraction, and a DDD-style architecture for layering new features.
Warpacks and Vara Arena. Founder-led product work across game design, smart contracts, grants, and shipping.
How I think about AI products
For me, the hard part is rarely "use an LLM here." It is deciding what context the model sees, what should persist, what must stay deterministic, and where a human still needs to stay in the loop.
That is the same logic behind Rialto's split between model reasoning and Rust risk controls. I applied it in internal tools too: building agent-memory systems so context could persist usefully over time, and graph-backed knowledge infrastructure so relationships across notes, entities, and ideas stayed structured instead of disappearing into loose text.
Featured Work
Rialto
A production trading system built around a simple split: let models handle noisy signal interpretation, and keep risk controls in deterministic software where precision matters.
Read the full case study →Free product teardown
Happy to do a free teardown of one of your product flows after our call. The fastest way to evaluate fit is usually to look at a real problem together.
Let's talk
If you're hiring for product, research, or a builder-analyst role, book 30 minutes and I'll come prepared.