Fabric for computer science students

Documentation, code snippets, lecture notes, project specs, research papers, tutorial worksheets, lab exercises. CS students work across more content types than most, and the material straddles theory and practice in a way that makes it hard to organise. The algorithm lecture is in one place, the implementation is in another, the paper that introduced the concept is in a third. When you're debugging at 2am and need to remember how your professor explained a specific data structure, scrolling through slides isn't fast enough.

Upload your lecture notes, documentation, and project specs to Fabric. The AI assistant understands your course materials alongside your code. "Explain Big O notation using the examples from this week's lecture." "What sorting algorithm did we cover in the complexity analysis module?" Every answer from your actual course, not Stack Overflow.

An AI tutor that knows your course and your code

The AI assistant works from your uploaded materials: lecture slides, textbook chapters, documentation, code snippets, project specs, and your own notes. Ask it to explain a concept using the examples from your lectures. Ask it to connect the theory from a lecture to the implementation in your project. Ask it to walk through an algorithm using your professor's specific approach rather than a generic textbook version.

The assistant has memory across sessions. It remembers the project you're working on and can reference your course materials when helping you debug or understand a concept.

Search across everything by meaning

AI search reads inside lecture slides, PDFs, code files, documentation, and notes. Ask "the lecture about dynamic programming" or "every problem we covered involving recursion" and find the material by concept. The search connects your lecture notes to your lab exercises to the papers you've read.

Record lectures and tutorials

AI voice notes record and transcribe lectures and tutorials. The lecturer's walkthrough of a proof, the TA's explanation during office hours, the guest speaker's industry perspective, all transcribed and searchable. See lecture notes.

Annotate documentation and papers

Annotations let you highlight and comment on research papers, documentation, and lecture slides. Mark the key theorem. Note the edge case. Flag the implementation detail. Your annotations are searchable across your full library.

Write alongside your research

Draft reports, project documentation, and dissertations in notes and docs with your course materials searchable alongside. The canvas helps you map system architectures and project structures visually.

Get started

Upload your course materials and get a tutor that knows your lectures and your code. Try Fabric free.

See also: Fabric for students. Studying and exam prep. Fabric for developers. Research papers.

Comparing tools? See the best AI study app and how Fabric compares to NotebookLM.

FAQs

Can the AI explain concepts using my lecture examples?

Yes. The AI assistant answers from your uploaded materials. It uses the examples, notation, and approach from your specific course.

Can I search across code and lecture notes together?

Yes. AI search works across every content type. Code, slides, PDFs, and notes are all searchable in the same query.

Can it help me debug using my course materials?

Yes. The assistant understands your project specs and course materials together. It can reference relevant lecture content when helping you work through a problem.

Can I record lectures?

Yes. AI voice notes record and transcribe any lecture with timestamps.

Is my data private?

Yes. Fabric uses AES-256 encryption and is CASA Tier 2 compliant. Your data is never used to train AI models.