= Use of AI in Spectrum contributions :page-nav_order: 150 // SPDX-FileCopyrightText: 2026 Alyssa Ross // 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.