Breaking news generates traffic spikes but rarely compounds. Evergreen content — articles that remain accurate and useful regardless of the date — builds a permanent citation base that pays dividends for years. In the LLM age, the distinction matters more than ever.
LLM Training Windows and Content Half-Lives
Most LLMs have training cutoffs. Even retrieval-augmented systems prioritise sources that have accumulated citations and authority over time. A news article about yesterday's headline has a citation half-life measured in hours. An explainer titled "What is retrieval-augmented generation?" published two years ago with regular updates accumulates citations continuously — and each new LLM training run is more likely to include it.
The Evergreen Content Formula
The best evergreen articles: define a concept clearly; include historical context, current best practices, and future outlook; use version-stamped updates ("Updated March 2026") to signal freshness; and end with a FAQ section that anticipates follow-on questions. This format works equally well for human readers and AI retrieval systems.
Repurposing News into Evergreen Assets
Most newsrooms generate enormous volumes of time-sensitive reporting that could be repurposed. A series of breaking-news articles on a court case can become an evergreen "How [Case Name] Changed AI Liability Law" explainer. A month of AI tool reviews can become "The Best AI Tools for Newsrooms in 2026." Each conversion extends the useful citation life of existing research.