Data Architecture for Enterprise Agents

What the series argues

An agent reasons over what you put in front of it. Get that wrong and no amount of model quality recovers the answer, because the model is working from the wrong ground.

Four papers treat four separable parts. Dynamic context assembly is the discipline that keeps what the agent sees minimal, grounded and sufficient, and makes sufficiency something you can defend. Semantic layers bridge what a model natively understands and what the domain requires it to understand. The maturity-curve paper explains why retrieval gets easier as semantic layers mature while execution gets harder with every business process added. Governance as middleware argues that governance expressed as information for the model to consider is not governance at all, then shows the architecture that enforces it deterministically.

Each paper stands alone. Read together they describe the data layer an agent needs before it is trusted with anything that matters.