Field Notes

AI systems in critical operations are not designed around model capability alone. They are designed around boundaries: where data lives, who can access it, what must be audited, and where human approval remains part of the workflow.

Model selection is downstream from the data architecture. If context, permissions, provenance, and retention are weak, a stronger model only makes weak foundations move faster.

A prototype proves that a workflow can be made intelligent. Production proves that it can keep working under load, policy, audit, exception handling, and changing institutional reality.