Bommarito, Katz, & Bommarito on AI Agents for Law and Finance

Michael James Bommarito (273 Ventures; ALEA Institute; Stanford Center for Legal Informatics; Michigan State College of Law; Bommarito Consulting, LLC), Daniel Martin Katz (Illinois Tech – Chicago Kent College of Law; Bucerius Center for Legal Technology & Data Science; Stanford CodeX – The Center for Legal Informatics; 273 Ventures; ALEA Institute), & Jillian Bommarito (273 Ventures; ALEA Institute) have posted How to Design an AI Agent: Architectures, Protocols, and Technical Evaluation of Agentic AI Systems for Law & Finance on SSRN. Here is the abstract:

Agents are not magic; they are architecture. In high-stakes domains like law and finance, the difference between a reliable tool and a runaway process lies in design. This chapter focuses on the architectural principles required to allow agents to function as cognitive work systems analogous to, and in concert with, professional teams. We organize our analysis around ten fundamental questions that shape an agent’s operational reality. These range from input mechanisms (triggers, intent, perception, and memory) to execution strategies (planning, delegation, and action tools). Crucially, we examine the safety layers required for professional deployment: termination conditions, human escalation protocols, and governance. Behind each of these ten questions lies a design decision with real tradeoffs. These choices determine what a system can do, how reliably it performs, and how it fails. Ultimately, this chapter argues that robust design requires architectural literacy—a necessary bridge between technical implementation and professional obligation.