= Use of AI in Spectrum contributions
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// SPDX-FileCopyrightText: 2026 Alyssa Ross <hi@alyssa.is>
// SPDX-License-Identifier: GFDL-1.3-no-invariants-or-later OR CC-BY-SA-4.0

Non-trivial Large Language Model (LLM) output in Spectrum contributions should
be clearly marked as such.
This is important context for reviewers, because humans and LLMs are prone to
different kinds of mistakes.

LLM-generated prose is discouraged.
It tends to be overly verbose, and can be confusing because misunderstandings or
false assumptions tend to be more difficult to spot in prose from LLMs than from
humans.

Contributors should ensure they understand and are able to answer questions about
contributions they submit, in their own words.
It's generally unhelpful to send LLM output in response to questions, because it
can be expected that reviewers can ask LLMs questions themselves if LLM-generated
answers would be useful to them.
If a reviewer asks a contributor a question, it's because they want that
contributor's answer, not an LLM's.
