Opening — Why this matters now The AI industry has a small addiction to the word agent. Add another agent, then another, then a few hundred more, and the slide deck begins to smell faintly of civilization. Somewhere between “workflow automation” and “digital society,” we are invited to believe that scale itself becomes intelligence. ...
TL;DR for operators Enterprise AI will not become useful merely because someone bolts a chatbot onto a database and calls the result an “agent”. That is theatre with API keys. The paper behind this article proposes something more sober: a blueprint architecture for compound AI systems in the enterprise, where LLMs are important but not sovereign.1 The core idea is that enterprise AI should be built as a distributed system, not as a heroic model prompt. Streams carry data and control messages. Registries expose existing APIs, models, and datasets as searchable assets. Task planners convert user intent into executable workflows. Data planners work out which databases, documents, models, or transformations are needed. Coordinators execute plans while tracking cost, latency, and quality budgets. ...