About

The last few years of my work have been at the intersection of Web3 and AI, with agentic AI becoming the main thread. I've been building products and infrastructure for agents that can use tools, reason over context, touch on-chain systems, and take real actions inside real products.

That shows up in different ways across my projects: on-chain products, markets, AI agents, memory, evaluation, and the runtime layer around modern LLMs. zkStash is one piece of that work: decentralized memory for AI agents.

I'd been shipping ML in production since the Oony days, and watching the language-model space closely from early on — 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.

I joined Hiero as founding engineer and CTO, leading product and the early team. The premise was a complete AI agent terminal with real blockchain access across Solana and Base — and we started building it before "agentic" had become the term of art.

The surface was wide: agents that could actually act on-chain — access DeFi primitives, create and launch tokens, buy, trade, and analyze tokens and NFTs, run deep price research, and chain those actions into recurring tasks the agent executed on its own schedule. The fun, hard part was the runtime — multi-step research-and-execution graphs on LangChain, LangGraph, and LangSmith 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.

My route into crypto started with provably fair gaming and state channels: games where the important question was whether two parties could move fast off-chain while keeping settlement honest on-chain. It felt like a natural continuation of the systems work I had always liked — protocol design, adversarial edges, and software that could enforce rules without asking a platform to be trusted.

I joined Decentraland in its early days, 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 created the SIP connection-tracking and NAT modules 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 remains the canonical SIP conntrack/NAT implementation in Linux. SIP itself remains the signaling backbone of much of the world's voice and video calling, from VoIP services to modern carrier networks. 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.