Lesson Content

Claude is often strongest when the student uses clear conversational commands around context windows, artifacts, revision passes, and careful reasoning. Command quality comes from separating source review, artifact creation, critique, and final polishing into deliberate phases.

Professional Use Case: A course creator uses Claude to transform a rough training outline into an artifact, then asks for gap analysis before publishing.

Student task: Use Claude / Anthropic with practice material you are comfortable sharing. Perform the use scenario below. Copy the first answer into a text editor or notes document. Then write one clarification prompt that tells the AI exactly what to improve. Student task help: Use pretend, public, or low-risk practice material. Copying the first AI answer into a text editor means pasting it into Notepad, Word, Google Docs, or another notes file so you can compare it with your revised answer. A clarification prompt is a short follow-up that tells the AI what to fix, add, remove, or explain. Example clarification prompt: "Make this easier for a beginner, add one concrete example, and show the next three steps as a checklist."

Starter scenario: Use a command-style sequence: review this source, identify gaps, create an artifact draft, then wait for my approval before polishing.

Troubleshooting: If the command is unavailable, check whether it depends on a workspace, paid plan, enabled tool, file type, browser/app context, or region. If the output is shallow, add source material, examples, exclusion rules, and a definition of done. If the output contains claims, verify against an authoritative source before using it.

Quality Rubric:

• The command includes enough context to prevent generic output.
• The result is tied to a real deliverable.
• The student records at least one verification step.
• Sensitive data is removed or minimized.