link org wide LLM_POLICY

Signed-off-by: Paul Holzinger <pholzing@redhat.com>

LLM_POLICY.md

@@ -1,81 +1,3 @@
-![PODMAN logo](https://raw.githubusercontent.com/containers/common/main/logos/podman-logo-full-vert.png)
+# Podman Container Tools LLM (AI) Development Policy
-# Podman LLM (AI) Development Policy
 
-This document is based on [Jellyfin LLM Policy](https://jellyfin.org/docs/general/contributing/llm-policies/)
+Please read our organization wide policy here: https://github.com/podman-container-tools/community/blob/main/LLM_POLICY.md
-and licensed under [CC-BY-ND-4.0](http://creativecommons.org/licenses/by-nd/4.0/).
-
-LLMs such as Claude and ChatGPT are powerful development tools. They can
-help both experienced and new developers. However, they also introduce risks.
-
-Podman has always prioritized code quality (readability, simplicity, and conciseness)
-and friendly communication. Our small team maintains these standards manually. As LLM
-usage grows within the Podman community, this policy clarifies our expectations for
-contributions and communication across all official projects and spaces.
-
-## No LLM-Generated Direct Communication
-
-LLM output must **not** be used verbatim in:
-
-* Issues or comments
-* Pull request bodies, comments, or commit messages.
-* Forum or chat posts
-* Security and vulnerability reports
-
-All communication must be written in your own words. You must understand what you are submitting.
-
-LLM-written content is often long, impersonal, and error-prone. As a small team with limited
-resources, we are unable to spend time reviewing unclear submissions or responding to impersonal
-comments.
-
-* Exception: If you use an LLM to translate your thoughts into English, clearly state this
-  (e.g., “Translated with an LLM from MyLanguage”).
-* Exception: The LLM-based bot can be configured by the maintainers to review the PRs
-  and suggest changes. These changes are only suggestions and might be wrong. It’s up
-  to the contributor and maintainer to decide whether the particular suggestion makes sense.
-
-Repeated violations may result in the closure or deletion of the submission or in a permanent ban from Podman projects.
-
-## LLM Code Contributions
-
-LLMs may assist with code, but you are fully responsible for what you submit.
-
-### Requirements
-
-* Follow all guidelines in [CONTRIBUTING.md](CONTRIBUTING.md).
-* Keep changes concise and focused.
-* Match existing formatting and quality standards.
-* Remove unnecessary comments, poor structure, whitespace issues, and editor/LLM metadata files (e.g., .claude configs).
-* The code must build, run, and pass tests before review begins.
-* Explicitly test the functionality you modify.
-
-### Understanding and Ownership
-
-You must:
-* Review all generated code.
-* Clearly explain (in your own words) what the change does and why in both the PR body and commit message.
-* Be able to discuss and justify your changes during review.
-
-Submitting “vibe-coded” or poorly understood changes will result in rejection after a few attempts to correct them.
-
-### Handling Review Feedback
-
-Do not paste reviewer feedback into an LLM and resubmit whatever it generates.
-
-Please engage in the review process by:
-* Responding thoughtfully to feedback using your own words.
-* Making minimal, targeted changes to address comments.
-* Understanding the implementation of required changes.
-
-### Final Discretion
-
-Maintainers have final discretion. PRs that are too large, overly complex, poorly structured,
-or difficult to review may be rejected after a few attempts to correct them — regardless
-of whether LLMs were used.
-
-Violations may result in the closure or deletion of the submission, or in a permanent ban from Podman projects.
-
-## The Golden Rule
-Do not prompt an LLM vaguely. Do not commit the LLM results unchanged. And do not submit them as-is.
-
-Using LLMs as a tool is completely fine. Using them as a replacement for understanding,
-responsibility, and craftsmanship is not.