Start with purpose, not line-by-line translation
When learners ask an AI assistant to explain code, they often get a wall of detail. A more useful first question is: what is this code trying to accomplish? Once the purpose is clear, the syntax has somewhere to attach.
Ask the learner to predict the purpose before seeing the explanation. Even an imperfect prediction creates something to compare.
Find the important pieces
Ask AI to identify the few functions, variables, conditions, data structures, or components that carry most of the behavior. Then trace one input through the program to its output.
This is usually more useful than giving equal attention to every bracket, import, and style rule.
Ask what could fail
A good explanation should include assumptions. What happens if the input is empty? What if a request fails? What if a value is the wrong type? What if the user clicks twice?
Thinking about failure turns reading code into engineering rather than memorization.
Finish with questions
Ask the AI tutor to quiz the learner without revealing answers immediately. Useful questions include: What does this function return? Why is this condition needed? What would you change to produce a different result?
If the learner can answer and then make one intentional change, the explanation has probably done its job.
A prompt you can reuse
Try: “Act as a patient coding tutor. First summarize what this code does in plain language. Then explain the important parts in order, identify inputs and outputs, point out one thing that could fail, and ask me three comprehension questions. Do not rewrite the code unless I ask.”
CodeTeachers’ Explain My Code tool builds this structure for you and reminds learners not to paste passwords, API keys, private URLs, or personal information.