Content half-life (freshness decay)

Content half-life describes how quickly a page decays in AI-search visibility once it stops being fresh. AI engines weight recency heavily, particularly for technology, security, and other fast-moving topics, and they read both the explicit dates on a page and the schema dateModified field. A page without a visible date is treated as untrusted relative to a dated equivalent; a page visibly dated two years ago is discounted against a current one even when the older content is still accurate.

The half-life varies by topic. A definitional explainer of a stable concept decays slowly; a "best tools for X in 2024" page decays fast, because the year in the title is a freshness signal that turns negative the moment the year turns. Fast-moving topics have short half-lives and demand a refresh cadence; evergreen topics tolerate longer gaps.

Managing content half-life is a maintenance discipline, not a one-time act. Keep a visible last-updated stamp on every page, update dateModified when you materially change the content (not cosmetically, which the engines can detect), and run a periodic refresh pass on the pages that matter most for citation share. The investment compounds: a domain that consistently signals freshness builds the trust that makes the engines retrieve from it preferentially. This is the operational side of the dating discipline in the citation-worthy content guide.