daBongo LMS AI Training Courses

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 completes a Any AI assistant account or practice demo. workflow and needs to show what was requested, what changed, what was checked, and what a human should approve before reuse.

Student task: Build a workflow evidence package. Save the original request, first output, revision prompt, improved output, and a short note explaining what you verified and what still requires human judgment. 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 evidence package includes input, output, revision, and verification notes.
• The reusable pattern is specific enough to run again without becoming generic.
• The final output includes at least one verification note.
• The student can explain what should not be trusted automatically.