Agent reliability is a property of the stack the model sits on. Five layers with distinct owners and failure modes turn the agent is unreliable into a specific diagnosis.
A lakehouse cannot serve sub-second queries over seconds-old data. A hot tier in front solves it, with consequences for consistency, governance, and operational surface.
Federate first so analytics work now, migrate what benefits from migrating, and leave the rest where it is indefinitely. Here's how pushdown and view layers make it work.
A large share of production transformations fit comfortably on one machine. PyIceberg, DuckDB, and branch isolation give you a production path that debugs in an IDE.
