60 Days of Production AI Systems · chapter 10 of 10
Production AI Readiness
Observability, evaluation, untrusted content, governance and infrastructure: what production asks of the whole system.
6 of 6 published
Chapter guide · 6 min readEvery question your AI readiness review asks was answered months agoThe whole chapter in one read. Then go part by part below.- 01
Day 55 · Explainer · 1 min read
Why observability is not optional for AI systems
Why production AI needs traces across prompts, context, retrieval, tools, costs, and decisions.
On the map: Observability - 02
Day 56 · Explainer · 1 min read
Why evaluating the model is not enough
Why evaluating agents means measuring the whole workflow users experience.
On the map: Observability - 03
Day 57 · Explainer · 2 min read
Why retrieved content must stay untrusted
Why retrieved content must stay data, not become authority over the system.
- 04
Day 58 · Explainer · 1 min read
Why governance belongs in the architecture
Why governance belongs in the architecture, not in a document after launch.
On the map: Audit - 05
Day 59 · Article · 1 min read
Why production AI is coordinated infrastructure
Why production AI is the coordination of data, models, tools, controls, evaluation, and people.
On the map: Agent - 06
Day 60 · Article · 2 min read
From model demos to mission-ready AI systems
A practical map for moving from impressive AI demos to systems people can trust.
On the map: Agent