Grading essays as a teacher: a 3-step chain (lens → diagnose → tone)
A method dreamed up by a teacher 19 essays into a 30-essay all-nighter. Where typical AI prompts "act as an English teacher" and devolve into a wall of rubric noise, this chain solves the real grading workflow: don't comment on everything.
3-step chain: Lens (this student's primary growth edge + under-comment list) → Diagnosis (ground every observation in specific quote) → Voice (mirror teacher tone with 2-3 sample feedback sentences)
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The author spent a week testing six prompts found online; all of them failed. So they reverse-engineered the real grading workflow out of Hattie's research. The key is telling the model what not to flag: the under-comment list is the load-bearing part. A keeper for teachers, writing coaches, ESL instructors, and exam-prep writing tutors.
聚焦的 margin comments（每個 < 20 字、附原文引用）+ 180 字內 end note（≤ 3 個 growth points）、用你的真實語氣不像 AI、學生能真的看完並改
Suno Engineer's Mindset: 4 Steps to a Song That Doesn't Sound Like AI
A studio engineer's breakdown of Suno's fatal weaknesses (fried vocals, high-frequency artifacts), plus a 4-step DAW workflow and a Suno Studio cleanup prompt.
5 Claude Weekly Workflows That Stuck After 6 Months
Proposal generator / meeting processor / content repurposer / Friday review / shutdown reset — out of 40 I tried, only these 5 survived, each saving 30+ minutes per run.