Reading this article made me realize that after all this time tinkering with model versions and context lengths, we've actually been optimizing pipeline speed but forgot to implement quality control gates. Hermes's approach is quite engineering-oriented and worth trying.

> Original Title: How To Fix AI Slop (Using Hermes)
> Original Author: @EXM7777
> Translated by: Peggy
>

Editor’s note: The "garbage" generated by AI is often attributed to poor prompts, insufficiently powerful models, or incomplete context. But this article presents a more engineering-oriented perspective: the problem is not on the input side, but on the output side.

The author believes that many people have repeatedly tried rewriting prompts, upgrading models, enabling memory, and stacking context files, but AI slop still recurs. The reason is that these methods all optimize the "generation" itself but do not establish a stable quality control mechanism. Just as a factory wouldn't rely solely on workers' intuition to decide whether a product leaves the factory, AI