Lesson Content

This course is not complete if the student only reads about Any AI assistant account or practice demo.. The student needs to practice how the workflow behaves when the first output is imperfect, incomplete, stale, or too broad. Good AI training includes recovery, review, and reuse.

Professional Use Case: A student uses Any AI assistant account or practice demo. for a real but low-risk task and receives an output that is incomplete, generic, or based on an unavailable feature. The student diagnoses the issue, rewrites the request, and records what changed.

Student task: Run a small troubleshooting drill. Start with a weak prompt for this course topic, save the first answer in a notes file, then write a follow-up prompt that fixes one missing input, one unclear constraint, and one verification step. Student task help: Use pretend, public, or low-risk material. Copy outputs into Notepad, Word, or another notes file so you can compare versions. A useful follow-up prompt tells the AI what to fix, add, remove, or explain.

Troubleshooting: If the tool or command is unavailable, check plan access, workspace context, enabled features, file type, and current product behavior. If the output contains claims, verify them against appropriate sources before using them. If the workflow affects customers, money, publishing, rights, code, health, law, safety, or reputation, add a human approval gate.

Quality Rubric:

• The student names the likely cause of the weak result.
• The revision adds context, constraints, and a definition of done.
• The final output includes at least one verification note.
• The student can explain what should not be trusted automatically.