Notes: Grow Your AI Workflows (Client Work and Local Files)

Section 11 adds one useful handoff, explains the scope of client builds, provides an accessible local-file practice task, and closes with a comparison between the learner's first and new explanations.

Lecture	Understanding developed
How Do You Turn 1 AI Agent Task Into a Workflow?	A useful result remains valuable by itself. One checked handoff can connect it to a next person or task while preserving unresolved evidence and the original requirement.
What Does Building AI Agents for Clients Involve? (Scope and Testing)	A bounded demonstration separates buyer knowledge, builder work, sample scope and checks from live connections, wider exceptions, training, maintenance and support.
How Does an AI Agent Read and Write Your Files? (Local File Practice)	Three fictional quote files, an exact request and a separate answer key make a fresh file-writing run inspectable without treating the supplied answer as model output.
Your New Explanation (What Changed Since Lecture 1)	Compare your first explanation with a new account grounded in your own task, observed actions and checks. A stopped run can name what remains needed.
Bonus: What Will You Try Next With AI?	Choose a useful next task, assess any paid-plan need against actual work, and consider optional guided practice.

The supplier quotes are fictional practice files. Keep the supplied answer separate while running your own comparison. The Claude Code continuation is optional.