LLM seeding
LLM seeding is the practice of placing accurate information about your brand on the sources AI answer engines retrieve and cite: your own site, reviews, industry publications, forums and reference sites. Legitimate seeding earns coverage; fake reviews, undisclosed paid posts and spam violate platform rules and Google’s spam policies.
Where do you seed information?
- Your own site: clear facts, FAQs, comparisons.
- Industry publications: see digital PR.
- Forums and communities: see Reddit SEO; Google and OpenAI both have Reddit data partnerships.[1][2]
- Reference sites: see Wikidata and Wikipedia.
How do you find the right sources?
Check which domains engines cite for your prompts: Bing reports cited pages,[3] and trackers report source domains. See AI citations.
What is off-limits?
Reddit’s rules prohibit spam and vote manipulation;[4] Wikipedia strongly discourages conflict-of-interest editing and requires paid editors to disclose;[5] Google’s spam policies cover link schemes and scaled content.[6]
Frequently asked questions
Is LLM seeding the same as link building?
It overlaps, but the goal is mentions in sources AI uses, linked or not.
Can I seed training data?
Training sets are not disclosed; focus on sources engines retrieve at answer time.
How long does it take?
Retrieval-based engines can reflect new sources once they are crawled and indexed.
See also
References
Sources accessed October 14, 2026 unless another date is given. See all sources.
- “An expanded partnership with Reddit”. Google. February 22, 2024.
- “OpenAI and Reddit Partnership”. OpenAI. May 16, 2024.
- “AI Performance”. Bing Webmaster Tools Help. accessed October 14, 2026.
- “Reddit Rules”. Reddit. accessed October 14, 2026.
- “Wikipedia: Conflict of interest”. Wikipedia. guideline, accessed October 14, 2026.
- “Spam policies for Google web search”. Google Search Central. accessed October 14, 2026.