Building AI agents as conversational chatbots with tools works for a demo, but shatters in production when a process spans multiple sessions. Relying on chat logs to track business milestones causes context rot, high token bills, and cascading failures. For a system to succeed at scale, engineers must treat agents like mini-operating systems: decoupling the model's reasoning from the business state. The workflow progress must be managed by a deterministic database state machine, using the LLM st...