How to Summarise Lecture Notes With AI (And Actually Remember Them)

A summary you did not make is a summary you will not remember. That is the central problem with asking AI to condense your lectures: the work of compressing material is most of what makes it stick.

The way around it is to use AI to check and structure your compression, rather than to do it for you.

Summarise first, then compare

Write your own summary from memory, badly and quickly. Then give the AI your notes and ask for its summary. The gap between the two is your revision list — it shows you precisely what you failed to encode.

Turn notes into questions, not prose

Ask for questions rather than a summary: “Generate fifteen questions this lecture should have made me able to answer.” Answering questions builds recall in a way that rereading a paragraph does not.

Anchor it to your own material

Paste in your actual notes or slides rather than asking about the topic in general. Your course has a particular emphasis, particular terminology and a particular examiner. A generic summary of the topic will not match any of them.

Keep the terminology your course uses

Ask it to preserve the exact terms from your notes. Models tend to paraphrase into more common vocabulary, and reproducing a definition in the wrong words is a reliable way to lose marks in a subject where the words are the point.

Check anything that looks new

If a summary of your own notes contains a fact you do not recognise, it did not come from your notes. Find where it came from before you revise it as though your lecturer said it.