Books

One argument runs through the work: durable rules are not the most carefully drafted rules but the ones engineered to revise themselves in light of what they learn. Three books now under contract carry that argument from law to architecture to evidence.

Advanced Introduction to Blockchain and the Law

Edward Elgar Publishing, Elgar Advanced Introductions series. Forthcoming.

Blockchain law has crystallized. The EU’s Markets in Crypto-Assets Regulation is at full application, the United States has its first federal digital-asset statute, and a decade of case law now governs tokens, smart contracts, and DAOs. This Advanced Introduction takes the reader through the law that exists rather than the law that was anticipated: crypto-asset characterization, smart contracts, DAOs and entity law, DeFi, securities regulation, stablecoins, privacy and anti-money-laundering, property and intellectual property, in a structured US, EU, and UK comparison. Its organizing claim is the pacing problem: code executes faster than law interprets, so regulation drafted as a static rulebook is obsolete on arrival. Every doctrinal area is read through dynamic regulation, rulemaking built on feedback, and the book closes at the agentic frontier, where autonomous systems become the next regulatory subject.

Governing the Agentic Economy

World Scientific Publishing. Forthcoming.

The diagnosis is measured, not asserted: scored against a thirteen-category institutional rubric, forty operating DAOs have built roughly half of the institutional architecture they require. The deficit is structural. Arrow’s Impossibility Theorem, the Folk Theorems, and incomplete contract theory jointly establish that no fixed rule set remains optimal, so better drafting cannot repair decentralized governance. What can is an architecture that governs its own evolution: reputation treated as capital rather than a score, carried on a weighted directed acyclic graph, adjudicated by staked validation pools, and executed as protocol rather than administered as institution. The book then generalizes the machine into Computative Economics, an economics for the condition in which the binding constraint on production is computational rather than physical, and follows it to the frontier: alignment that emerges from consequence, the governance of self-modifying systems, and a candid account of the attacks the mechanism defeats and the ones it does not.

Predictive Analytics in Law: From Supervised Pipelines to Reputation-Governed Multi-Agent Systems

Cambridge Scholars Publishing. Forthcoming.

The volume is organized around a single experiment. The strongest supervised system for predicting European Court of Human Rights outcomes is a purpose-built pipeline: a fine-tuned legal language model, precedent retrieval, and explicit temporal-drift correction. Against it stands a population of one hundred unmodified open-weight models coordinated by nothing but reputation governance: calibration-initialized reputation, reputation-weighted consensus, confidence-proportional staking, and zero-sum redistribution. The question is whether coordination can do the work of engineering. If governance-based prediction matches purpose-built supervision, the design philosophy of legal AI shifts from supervised learning and domain adaptation to mechanism design and incentive alignment. Ten chapters develop the experiment and its consequences for prediction markets, temporal drift, professional responsibility, and regulation.

How the Three Books Build on Each Other

The Elgar book supplies the lens: law cannot pace code unless rules are designed to learn. The World Scientific book builds what the lens demands: the institutional architecture in which rules revise themselves, and the economics that emerges once they do. The Cambridge Scholars volume puts that architecture to its hardest test inside law itself: whether reputation-governed coordination can match the best purpose-built engineering at predicting what courts will do. Diagnosis, architecture, evidence. Each book stands alone; together they are one program, the dynamic-regulation argument developed across two decades of scholarship, carried from financial-market rulemaking to the governance of autonomous agents.

The Foundation: Decentralization

Decentralization: Technology’s Impact on Organizational and Societal Structure (with mathematics professor Craig Calcaterra), De Gruyter, 2021. The framework all three books extend: why centralized hierarchies excel at the problems they were designed for and fail at the ones that came after, and what the core infrastructure of a decentralized economy requires, from legal environment and underwriting to scaling, security, and governance. Available on Amazon.

“Decentralization – Technology’s Impact on Business and Society” – Forthcoming in DeGruyter Publishers (2020) – Available on Amazon.