Interview: Albert Castellana, Co-Founder and CEO of GenLayer Labs, on Building the Adjudication Layer for AI Agents

As autonomous AI agents take on more of the negotiating, buying, and selling in digital commerce, a fundamental question remains unresolved: who adjudicates when the parties disagree? Albert Castellana, Co-Founder and CEO of GenLayer Labs, has built financial and blockchain infrastructure throughout his career — including at StakeHound and Radix — and is now applying that experience to what he calls the “adjudication layer for the agentic economy.” GenLayer’s Intelligent Contracts allow agreements to incorporate natural language and real-world context, with a decentralized network of AI validators reaching consensus on outcomes through a model the company calls Optimistic Democracy. In this interview, Castellana explains why traditional smart contracts can’t handle ambiguity, how GenLayer’s validator and appeals process works, and where he sees the technology heading as AI agents become active participants in the economy. Q1. Looking at your experience building projects like StakeHound, Radix, and others, what key challenges in traditional dispute resolution urged you to create GenLayer as infrastructure for the agentic economy I’ve spent most of my career building financial and blockchain infrastructure, and one thing kept coming up: the technology could make transactions dramatically faster, but the moment something went wrong, we were still relying on systems that were built for humans. That problem becomes much more obvious when you look at autonomous agents. In traditional commerce, if two parties disagree, you can call a lawyer, go to court, or negotiate. That can already be painfully slow and expensive. If millions of software agents are transacting with each other at machine speed, you can’t send every disagreement to a human process, it would be unthinkable. That was the insight behind GenLayer… We needed an infrastructure layer for the part of a transaction that happens after the happy path, when the parties disagree about what was promised, what happened, or what the evidence means. GenLayer is our attempt to build that adjudication layer for the agentic economy. Q2. As AI agents have started transacting autonomously at scale, who resolves disputes when something goes wrong, and why is this becoming a critical bottleneck? Today, ultimately, a human does, and in our view that can be part of the problem. An agent can negotiate a transaction, make a payment and execute an agreement without a person involved. But when something goes wrong, we’re generally pushed back into human arbitration, customer support, legal processes or centralized platform decisions. That model doesn’t scale to an economy where software agents could be conducting millions of transactions continuously. The individual disputes may be small, but collectively they become a huge infrastructure problem. A large share of digital disagreements simply aren’t worth pursuing because the cost and time of resolving them exceed the value of the transaction.