Scriba vs CaseCub
Scriba vs CaseCub — AI brief generators vs a reading desk.
Skipping the reading and getting a summary fast.
Actually learning to spot issues and hold cases apart on the exam.
The honest breakdown
CaseCub generates briefs from a case name or citation. Scriba starts from the opposite end: you read the opinion, highlight the passages that matter, and the brief assembles itself from what you tagged. Different theories about what a brief is for.
| Feature | Scriba | CaseCub |
|---|---|---|
| Reader panel with tag-to-brief workflow | Yes | No |
| One-click brief from citation | No — you read it | Yes |
| Outline builder from your semester’s briefs | Yes | No |
| Spaced-repetition flashcards from your rule statements | Yes | No |
| Grounded AI (only cites what you highlighted) | Yes | No |
| Honor-code appendix on every export | Yes | No |
Switching from CaseCub — a short guide
- Cancel the generator subscription — you’re paying for text you can’t safely submit.
- Import your syllabus into Scriba; every reading is now on your dashboard.
- Read each case in Scriba’s Reader. Highlight the five to eight passages that matter.
- Export the brief. You wrote it. It ships with the honor-code appendix.
Objections we hear
Aren’t AI generators just faster?
Yes, for producing an artifact. No, for producing a J.D. The exam does not test the artifact — it tests the reasoning behind it, which the generator did for you.
What if my honor code allows AI-generated briefs?
A few schools do. Even so, the generator’s output is ungrounded — it may cite lines that don’t exist in the opinion. Scriba constrains AI to text you actually highlighted, which is honest either way.