Enterprise Agent Architecture

All research

Production engineering of multi-discipline AI agent systems for enterprise environments. Orchestration design, deterministic-first architectures for financial systems, and the data architecture that lets agents reason against complex organizational data.

Series

Each series is a coherent sequence of papers on a single topic within this subject area.

01 Agent Orchestration (3 papers) How orchestration of enterprise agent systems should be designed. Where language-model-driven orchestration fails, the five canonical patterns, and the deterministic-first discipline required when agents touch financial systems.
02 Data Architecture for Enterprise Agents (4 papers) The data architecture that enterprise agents require in order to reason reliably. Each paper treats a separable component of the substrate the model consumes.
03 Self-Learning in Enterprise Agents (3 papers) When a self-learning agent is safe in a financial system. What it should learn, how its rules inherit through the business's own hierarchies, and why most of what it learns is deferred work.