Internal AI · Academic operations
Academic operations workspace
The problem
The academic team had a large library of source material, and turning exemplar content into exam-ready MCQs took two weeks. The bottleneck was faculty time.
What I built
I prototyped an AI workspace with AI-assisted tools, using 103 source PDFs (textbooks, past papers, chapter importance, question-quality rules, source attribution). There is a companion workflow that takes exemplar content through to MCQs. The academic team uses it as a workflow. I did not write production software here.
What changed
Team velocity went up by roughly 3x. The whole academic team ended up using it, which I did not assume would happen. The exemplar-to-MCQ workflow saved 200+ faculty hours and brought a two-week process down to two days.
What I'd do differently
I would have put a quality gate in at the same time as the speed gains. Faculty will not sign off on the output until the error rate is in a range they trust.