What is Freshness signal stack?
The freshness signal stack is the five-signal set every major AI search substrate reads to compute a page's freshness timestamp: the HTTP Last-Modified header, the schema-emitted dateModified field (Article, FAQPage, Product, HowTo), the visible last-updated date rendered in server-side HTML at the top of the page, the content-diff hash the substrate computes between successive crawls, and (for multimodal pages) the image last-modified plus content hash on the image file. The five signals reconcile into a single freshness timestamp the substrate uses to weight the page against fresher competitors. Refreshes that touch one or two signals and leave the rest stale are discounted; the discipline is to touch all five in the same edit window from a single source-of-truth date field that drives the visible date, schema dateModified, and HTTP header simultaneously.
How it relates to AI UGC
The image side of the signal stack runs on its own track — the image file's last-modified header and the substrate-computed content hash. Re-uploading the same image file without re-export produces no content hash change and is discounted. Persona-locked AI UGC re-generated from ppl.studio produces a fresh file with a real content hash, so the image side of the signal stack reads cleanly inside the multimodal substrate's next pass.
Key statistics
- Mid-2026 substrates read five freshness signals per page; pages emitting all five out-cite pages emitting three or four by 1.4–1.8× on the same priority query set (signal-stack cohort, 2026).
- Roughly 20–30% of mid-2026 priority pages emit only three of the five signals on first audit — most commonly missing the HTTP Last-Modified header (capped at the deploy date) or the schema dateModified (inconsistent with the visible date) (signal-completeness audits, 2026).
- Cosmetic refreshes (visible date updated, prose unchanged) trigger the content-diff discount inside two crawls — the substrate hashes the page text and discounts the freshness claim when the hash does not change (cosmetic-refresh cohort, 2026).