How to build a 45-minute Model Kill Switch before your next outage

If your team depends on AI agents, your architecture already has a hidden single point of failure. This is a short blueprint you can implement today. No redesign. No big migration. The goal In 45 minutes, you can have a model kill switch that keeps critical flows moving. Step 1: baseline your AI routes Write down every place with model calls: repo bots, PR reviewers, support triage, content generators, internal docs agents. Step 2: classify by criticality Red: if broken, releases stop Yellow: delayed output is acceptable Green: can wait or go manual Step 3: add deterministic fallback policy For each red/yellow path, define primary -> fallback. Step 4: enforce retry budget If primary fails 3x in 60 seconds, auto-switch to fallback for the next N calls. Step 5: keep logs honest Add one metric: provider_failover_count by workflow. If this spikes, it is a decision-to-fix signal, not a random warning. Step 6: run a weekly drill If you can’t recover from this in 15 minutes, you don’t have