Dr. Neil's Notes
Software > Development > AI in Delivery Systems
Reliability guardrails
Introduction
AI-assisted delivery can fail in subtle ways, confident mistakes, stale context, and quiet drift over time. Guardrails are the design choices that keep those failures bounded and recoverable.
Contain blast radius
Start with low-risk domains and constrained permissions. Separate advisory behavior from autonomous action until evidence supports expansion. A small blast area makes learning safe.
Detect drift early
Use recurring evaluation tasks against known scenarios so quality regressions are visible. Drift is not a one-time event, it is a persistent operating condition that exists in all software over time. This is not a new phenomena, it is amplified by the tools being used without care.
Design for rollback
Every AI-enabled change should be reversible with clear rollback procedures. Reliability is not only about preventing failure, but about recovering cleanly when failure occurs.
Part of the AI in Delivery Systems series.