Field note
2026 AI reliability playbook
A 26-page manual for turning an AI demo into a system you can evaluate, control, observe and recover, ending in a go, conditional-go or no-go decision.
- Who it is for
- Founders, product leaders and engineers who need a release decision they can defend.
- How to use it
- Work through it in order on one workflow with a named owner.
- Format
- Field note, PDF, 26 pages.
What is inside
- Why a 200 OK response is not a successful workflow
- Evaluate evidence, control authority and design the recovery path
- A go, conditional-go or no-go decision with a fix-first path
Goes with the article Agent reliability engineering: an operating model for production AI.
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