Day 55: Why observability is not optional for AI systems
Why production AI needs traces across prompts, context, retrieval, tools, costs, and decisions.
Jul 18, 20263 min read
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Series
Production AI Readiness
A closing series for moving from AI demos to systems people can trust. It covers observability, workflow evaluation, prompt injection and data leakage risk, governance, end-to-end production architecture, and the complete AI ecosystem map.
Day 56: Why evaluating the model is not enough
Why evaluating agents means measuring the whole workflow users experience.
Jul 18, 20263 min read
Day 57: Why retrieved content must stay untrusted
Why retrieved content must stay data, not become authority over the system.
Jul 18, 20263 min read
Day 58: Why governance belongs in the architecture
Why governance belongs in the architecture, not in a document after launch.
Jul 19, 20263 min read
Day 59: Why production AI is coordinated infrastructure
Why production AI is the coordination of data, models, tools, controls, evaluation, and people.
Jul 19, 20263 min read
Day 60: From model demos to mission-ready AI systems
A practical map for moving from impressive AI demos to systems people can trust.
Jul 20, 20263 min read