
Produce aggregate product-friction evidence instead of individualized sentiment scores.

Design execution traces that explain tool use, approvals, failures and verified outcomes while protecting sensitive data.

Use schemas for reliable interfaces while separately checking business meaning, authorization and safe downstream handling.

Preserve chronology, failed attempts and unresolved questions so customers need not repeat themselves.
Explore sourced guides to AI agents, practical workflows and business models. Understand implementation choices, operating costs and limitations. Hypothetical examples are labeled; commercial claims are attributed, not promises of income.