LLM seeding refers to actively placing brand content into the datasets and retrieval sources that large language models (LLMs) use to generate answers. The article frames LLM seeding as a practical complement to search engine optimization and generative engine optimization, explaining that many of the same visibility principles apply. Examples of LLMs named in the piece include OpenAI, Perplexity, Claude, and Google’s AI overviews. The main goal of LLM seeding is to ensure that Artificial Intelligence systems retrieve and cite your content so your brand appears in answers and drives higher-quality leads.
The article details where LLMs get their data: pre-trained general web data such as Common Crawl, Wikipedia (noting historic figures like a 3 percent contribution to GPT-3), community Q&A platforms like Reddit, Quora, and Stack Overflow (including recent licensing and partnership mentions), independent review sites such as Capterra and G2, and licensed news partners like Reuters and Bloomberg. It presents a practical seeding map for PR teams, listing favored sources and why Artificial Intelligence systems use them. Recommended PR channels to prioritize include media coverage in authoritative outlets, data-backed press releases in public newsrooms, thought leadership on LinkedIn and industry blogs, vendor comparison pages, event and award listings, and community Q&A and video content.
The guide outlines how to craft content for LLM pickup: write clear, standalone definitions early in the text; use explicit attribution with full names and titles; prioritize evergreen factual statements; include FAQ or Q&A sections; use descriptive H2/H3 headings; present lists and tables; repeat key facts across assets; maintain a neutral factual tone; and add structured comparisons and schema markup. For distribution, it recommends interrogating LLMs to surface their sources, testing in incognito or different accounts and devices, and tracking patterns. Tools and tactics for monitoring LLM presence include platforms such as Brand24 and Profound. The article also highlights Prowly features that support seeding: AI-ready press release formatting, distribution to trusted media networks, and combined media and Artificial Intelligence monitoring to measure when and where content is reused by LLMs.
