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When AI comments come out off topic

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Why a model writes generic filler instead of answering the post, and the three prompt changes that fix it fastest.

When AI comments come out off topic

Comments come out, and they read like placeholders: «interesting point», «thanks, useful». The prompt is almost always the cause, not the model.

Why it happens

A model answers what it was given. If the prompt says «write a comment», it writes a comment in general — the safest and least useful kind. Specificity in the answer comes from specificity in the task.

Three changes, by return

  1. Give it a role and experience. Not «you are a commenter» but «you have done this for five years and answer to the point». Role changes tone more than any instruction about tone.
  2. Require it to anchor on the post. Explicitly: «open with a specific detail from the post». That removes half the filler.
  3. Ban the clichés. List what must not appear: «thanks for the post», «interesting», «I agree». Models avoid what is named.

What not to do

Do not grow the prompt to two pages. A long prompt costs more on every call and stops improving results past a point — the model loses priorities when there are too many instructions.

Testing changes

One at a time, reading twenty live comments after each. Change everything at once and you will not know what worked. The cost of those experiments is in the model-call piece.

Topic: Automation

More on this topic: The tool for this

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