About

I split my time between research and shipping. The thread tying everything together right now is the same one I've been pulling on since 2017: how do you build systems where software can hold assets, reason over private state, and act with real economic agency — without a human in the loop and without a centralized referee?

That's where zkStash came from. Agents need memory the same way humans do, but the mainstream answer — dump everything into a vector DB owned by the model provider — collapses the moment two agents need to coordinate, or one of them needs to forget. zkStash is a decentralized memory layer for that.

I'd been shipping ML in production since the Oony days, and watching the language-model space closely since GPT-3 — but it wasn't until late 2023 that the agentic side started feeling like 1995-vintage internet again: primitive, but obviously load-bearing. I went all in. Production work with LangChain and LangGraph, a lot of time on retrieval and evaluation, and a growing conviction that agents and Web3 wallets are the same problem viewed from two angles.

That conviction shows up in what I'm shipping now — Degentics for on-chain analysis, Perpy for perpetuals signals, x402list for agent-payable services.

I joined Hiero as founding engineer and CTO during the AI-agent-token wave. The product was a Web3 agent terminal spanning Solana and Base — users could spin up token-attached agents, give them a toolbox covering both chains (token launches, swaps, transfers, on-chain lookups, market research, autonomous Twitter), and let them run.

The fun, hard part was the agent runtime. Built on LangChain, LangGraph, and LangSmith, with multi-step research-and-execution graphs that planned across chains, called the right tool, and stayed observable. We shipped the platform and the HTERM token. The broader agent-token cycle cooled and the project eventually wound down — but it was the deepest stress test I've run on what production agents can actually do once you hand them a wallet, a toolbox, and an audience.

I founded TradeStars to test a thesis: sports fandom is already a market — fans value players, argue about price discovery, and trade reputations on group chats every weekend. What if that market were real?

We built it. Each athlete became a fractional NFT — an ERC-20-backed share of an NFT, priced by an automated market maker that responded to real-world performance. We launched the public exchange in January 2020, ran it on Polygon for the L2 economics, raised $2.2M+ across rounds, and shipped the TSX token. The fractional-NFT primitive we designed showed up in a lot of places afterwards.

Before TradeStars I spent time inside Decentraland in its early days, contributing while the protocol and the marketplace were still being shaped. It's where I first saw NFTs as a primitive worth building real applications on, not just a collectible format. I left to start TradeStars, but the conviction I picked up there — that on-chain ownership of digital things would matter — set the next decade of work.

With my long-time co-founder Ariel Barmat I built Weegoh, one of the first location-based social networks in Latin America, and then Oony, a shopping recommendation platform that grew to a catalog of several million products across fifteen countries. Oony is also where I first shipped machine learning in production — classifiers for deal quality and ranking, back when "ML" still meant scikit-learn and feature engineering. The thread that started there runs straight through to what I'm building now.

I came up writing C, working close to the metal — networks, routers, packet handling. In 2005 I wrote the SIP connection-tracking and NAT helpers for the Linux kernel's netfilter subsystem — nf_conntrack_sip.c and nf_nat_sip.c. They handle the awkward parts of routing SIP signaling and media through NAT, where addressing information is buried inside the protocol payload itself. That code shipped into the mainline kernel and is still in every machine running Linux today. There's a short design write-up on the netfilter site from when it landed.

Conversations with founders building agentic products, infra teams working on agent identity / payments / memory, and operators who need a technical co-founder or architect-level partner for the next stretch. If that's you, say hi.