AI for teachers: the honest use cases.

Teachers are one of the largest professional groups using LADLE. Their feedback has been unusually specific about what works and what doesn't, so this post exists to compile that experience.

**What LADLE helps teachers with, honestly:**

**Differentiation drafts.** You have the same content to teach and three reading levels in the class. LADLE will produce three versions of a short explanation at three different reading levels in a minute. You edit them for accuracy and voice, but the mechanical work of "restate this concept at grade 6, grade 8, grade 10" is exactly what the model is good at.

**Rubric generation.** Give it the assignment, the learning objectives, and the grade level. Ask for a scoring rubric with 4 levels. You'll get a starting draft that's 80% right; the last 20% is you knowing your specific class and standards. This saves an hour on the mechanical rubric work.

**Parent communication drafts.** "Draft a note to a parent about a student who's struggling with X. Be direct, kind, and specific. Suggest one concrete thing we could try together." The output is a starting draft; you edit. Faster than starting blank, and often catches phrasing better than the tired-Friday version of you.

**Lesson-plan variation.** You've taught the same unit for five years. It's tired. Ask LADLE for three different ways to open the unit that hit the same objectives but through different angles. You'll get some useful reframes and some that don't fit your class — the useful ones justify the exercise.

**Feedback for student drafts (not grading).** Paste a student's essay draft (with permission and appropriate anonymization). Ask for observational feedback focused on structure and reasoning, not grading. The reply is a starting point for you to refine into feedback you give — it's not the feedback itself. Students should hear your voice, not the model's.

**What LADLE does NOT do well for teachers:**

**Grading.** Even with a rubric, LADLE grading isn't reliable enough to trust for stakes. Two problems: (1) the reasoning behind a grade is often subtle and rubric-inconsistent in ways only a human notices, and (2) students deserve grades from their teacher, not from a machine. Use it for feedback drafts, not for grades that go on records.

**Answer keys for math or science with high accuracy requirements.** For anything past basic arithmetic, verify answers manually. LLMs still make specific errors on multi-step math and physics that a student catching would embarrass everyone.

**Detecting AI-written work.** Every "AI detector" has high false-positive rates. LADLE can't reliably tell you if a student's essay was AI-written. Don't use it that way; you'll wrongly accuse honest students.

**Substituting for your subject knowledge.** LADLE will confidently produce content in your subject area that sounds correct and contains subtle errors only you would catch. Use it for phrasing help and structural drafts, not for content you don't know deeply enough to verify.

**On the "students are using AI to cheat" question:**

The reality is: some are. Some will keep doing it. AI writing detection isn't reliable. The pedagogical response is to rethink what assignments actually assess, not to try to detect AI harder. Assignments that can be completed by pasting the prompt into an AI shouldn't be your primary assessment. Oral defenses, in-class writing, project-based work, and process artifacts (drafts with revision history) are harder to shortcut.

That's a whole other conversation and not really a LADLE conversation. But if you're a teacher weighing whether to teach WITH AI or against it, the middle path (teach with it, redesign assessments so it doesn't undermine learning) is where most of the effective teachers we've talked to have landed.

**Rule of thumb.**

Use LADLE for the mechanical work you'd otherwise do at 10pm on Sunday. Save your time for the parts of teaching that only you can do — knowing your students, giving your feedback, holding the room. AI helps with the drafts, not with the teaching itself.