When Agents Decide
Continuous Decision Intelligence and the Substrate Beneath It
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It is 5:47 on a Tuesday morning and the CIO's phone will not stop. Overnight tariffs, a supplier gone dark, and a state-of-the-art agentic forecasting platform that is, in a very real sense, a museum: confident to two decimal places and answering last week's question. The paper opens with that forty-eight hours and the decision that saved the company, which was not better AI but a way to keep changing the AI as fast as the world changed.
From that story the authors define Continuous Decision Intelligence: evaluation, decision tracking, and policy enforcement bound into systems that improve decisions over time. They describe the substrate an organization needs beneath its agents so that models can be swapped on a Tuesday afternoon, decisions can be reconstructed and learned from, and humans stay in the loop where the stakes are high and out of it where they are low.
What's inside
- A Story You Will Recognize — A narrative case of an enterprise whose agents could not see the storm, and the shift from a forecast published on Mondays to a loop that never stops running.
- What CDI Is and Why Now — Why models drift under you, why deprecations arrive on the vendor's schedule, and how continuous evaluation, decision tracking, and policy enforcement close that gap.
- The Substrate Beneath the Agents — The platform properties that make a mesh of small, disposable, auditable agents possible in production.
- Human in the Loop by Design — How to calibrate autonomy to stakes so that oversight lands where it matters and does not slow everything else.
- Topics
- AI · Software Delivery & Architecture
- Formats
- epub · pdf
- License
- Creative Commons BY-NC-SA
