
Build revisable agent plans around prerequisites, evidence-producing milestones, explicit authority and meaningful stop conditions.

Give an agent the right evidence at the right step, with clear provenance, scoped instructions and summaries that preserve uncertainty.

Separate working context, conversation history, preferences and task state so useful continuity does not turn into stale assumptions or data leakage.

Build a maintained knowledge supply chain before asking a retrieval assistant to answer questions about company policy.
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.