Contrastive Example Calibration: Show It What You Want AND What You Don't — One Negative Example Beats Three Positive Ones
Demonstrate both the 'desired output' and the 'output that shouldn't appear' at the same time, so the AI calibrates between the two poles; for tasks about tone and precision, a single negative example often outperforms three positive ones.
Task: {{task}}
GOOD example (match this tone and depth):
{{good}}
BAD example (avoid this, it is too {{badtrait}}):
{{bad}}
Now produce the output for: {{input}}. Calibrate against both anchors.Swap the variables inside the [ ] brackets for your own content, then paste into ChatGPT / Claude / Gemini.
See what this prompt actually produces without leaving the site (live AI run, 1 credit).
Can't get the AI to nail the tone you want? Beyond positive examples, give it one 'not like this' counter-example too — it will calibrate between the two poles, and that's usually more accurate than giving it only good examples.
一段語氣與深度貼近你正例、且避開反例毛病的輸出。
[task]任務
[good]想要的輸出範例
[badtrait]反例的毛病,如:太正式 / 太空泛 / 太長
[bad]不想要的輸出範例
[input]這次要處理的實際輸入
填下面的欄位,上方 prompt 會即時替換 [方括號] 內容。填好後按「複製組好的 prompt」直接丟進工具。
Task: {{task}}
GOOD example (match this tone and depth):
{{good}}
BAD example (avoid this, it is too {{badtrait}}):
{{bad}}
Now produce the output for: {{input}}. Calibrate against both anchors.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.