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Generalize LLM advice to non-prompt models

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* HACKING: Don’t assume traditional LLM prompt model.
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Paul Eggert
2026-09-05 10:49:07 -07:00
parent 0f83f0223b
commit 58df1afe78
2 changed files with 8 additions and 1 deletions
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@@ -1,3 +1,8 @@
2026-09-05 Paul Eggert <eggert@cs.ucla.edu>
Generalize LLM advice to non-prompt models
* HACKING: Don’t assume traditional LLM prompt model.
2026-09-05 Oleg Tolmatcev <oleg.tolmatcev@gmail.com>
stat, fstat: Optimize on native Windows.

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HACKING
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@@ -261,7 +261,9 @@ We need to avoid two problems with that:
To this end:
1) Code included in this package that comes from a single LLM prompt
1) Code derived from an LLM must respect copyrights and licenses
in the source material that the LLM is based on.
For a traditional, single LLM prompt this means a code response
must be limited in size: it must be at most 5 lines long.
2) As a submitter, you assert that you have reviewed such code that you