“Tailor Your Feed” is the first time a user can shape their Discover feed by typing, in natural language, what they want to see. We have tracked it from its first appearance in Search Labs^search-labs to the pipeline[^pipeline] that powers it. Ten key points:
- An explicit-control layer. Your prompt is turned into
SEE_MORE/SEE_LESSactions, applied after a feed refresh. - Seemingly an LLM[^llm] under the hood. A persistent chat thread, and your prompt turned into instructions applied to your feed (in real time and over time).
- The rebrand. “Tailor Your Feed” became “Add topics to your feed” in spring 2026, with a chat-style entry point.
- The back-end pipeline.
historicalnaturallanguagetuningcontent.f[^pipeline-id], the “historical” twin ofnaturallanguagetuningcontent.f. - Two ways content is chosen. Entity[^entity] / interest expansion (the majority) vs a query-intent[^query-intent] fan-out[^fan-out] (the minority), the latter being the GEO[^geo] mechanism inside Discover.
- Visible attribution. The “You asked to see” label, the “resulting from natural language tuning” tag, and a prompt history in My Activity.
- Niche sites and small creators surfaced. Vegan recipe creators, Mississippi Today, a LinkedIn post, niche Japanese-property blogs and, as an illustration of the retrieval’s[^retrieval] behaviour, publishers outside the usual mainstream (VentureBeat surfaced on a “niche sites” prompt, though not itself a small site).
- A popularity bypass. This pipeline mostly carries content that had barely circulated in Discover before, the opposite of the classic pipelines that re-serve already-popular articles.
- What it changes for publishers. Selection power shifts to the user, opening a third path to visibility for small, niche sites.
- Still EN-only, still nascent. Search Labs US only (FR ≈ 0%), adoption still early. What’s next.
Methodology
This article combines two observation streams:
- Field tracking of the feature in the Google app since December 2025: UI states, server responses, attribution tags, and feed behaviour after each “Refresh / Update your feed”. Captured on our test devices, US (English) Search Labs accounts.
- A close reading of the feed itself: each card can be traced back to the pipeline that selected it. By isolating the cards served by
historicalnaturallanguagetuningcontent.f, we describe how this pipeline behaves relative to the rest of the feed, drawing on 1492.vision tracking data.
Three deliberate notes on how we phrase things:
- We describe distribution outcomes[^distribution], whether an article had ever circulated in Discover before, not raw audience numbers. When we say a card has “no prior Discover distribution”, we mean we find no trace of earlier serving in our Discover tracking dataset.
- No account identifier appears in this article. Examples are shown as prompt → result, anonymised.
The internal mechanisms below are our…
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