Tag

AI Observability

Observability and Auditability in AI-First Workflows

AI workflows need observability beyond normal application logs. This essay explains what should be traced: prompts, model versions, tools, workflow nodes, tenant context, approvals, quality scores, and failures.

AI Architecture

Designing a Model-Agnostic AI Architecture

A model-agnostic architecture allows teams to test and switch providers without rewriting product workflows. This essay explains the components needed for practical model flexibility.