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 a kill switch — you have a manual script and a prayer.
The test
Create one non-critical workflow and fail over once a week. If your team can do this calmly, you’re building real resilience.
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