Published: April 5, 2025
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I trained an AI agent to study YouTube’s open-source research... this is why the algorithm intentionally kills your video’s reach 👇

Image in tweet by phed

Before we get into it, I post a lot of AI X YouTube threads Bookmark to come back and re-read this thread in the future 👇

1. reach decay is real your video isn't shadowbanned it’s just getting outdated in the algorithm’s eyes youtube uses a mechanism called temporal decay — and it's built directly into the recommendation model

2. the algorithm penalizes age every video has a kind of “freshness score” under the hood as time passes, that score fades — fast even if your video performed great on day 1, by day 30, it needs new signals to stay relevant

3. why? the training data is time-biased neural networks learn from historical data so they naturally favor videos that did well in the past but this creates a problem: 📉 it biases the model against new content 📉 and locks in old viral videos forever

4. youtube fixed this with a feature called “example age” they literally feed the age of the training example into the neural net during training: it knows the example is 7 days old during serving: it pretends the example is brand new this forces the model to stay fresh, and helps new videos go viral

5. but temporal decay still exists even with fixes, the model still weights recency older impressions get devalued stale candidates drop in rank inactive videos slowly fade from the system this is why you see views die down after the first 24–72 hours

6. reach decay varies by niche temporal decay is not fixed a viral news video decays faster than a slow-burn documentary the decay rate changes based on: - topic - user interest over time - click & watch trends per niche the algorithm adapts based on content life cycle

7. how to beat the decay there’s only one way to keep a video alive in the feed: ⚡ generate new watch time ⚡ get clicks from new users ⚡ spark new comments, shares, or embeds every new signal resets the clock just a little

8. youtube doesn’t just want good videos it wants good videos people still care about your video can be a masterpiece - but if no one’s clicking or watching it now the algorithm moves on

9. creators who win long-term do this: optimize for both burst & shelf life re-promote evergreen videos remix or follow-up on past hits build videos that compound over time (guides, lists, case studies)

when we say burst & shelf life - we refer to: Burst: Hook viewers early to win the initial algorithm boost Shelf: but build long-term value so the video keeps ranking in recommendations/search for weeks or months

10. bottom line: your video isn’t dying the algorithm is just evolving reach decays by design but attention revives it

tl;dr: YouTube’s algorithm applies temporal decay to every video Without ongoing engagement signals — clicks, watch time, retention — your content gradually loses ranking power Freshness isn’t optional Reach is a function of current relevance, not historical performance

To counter this decay, you need to inject fresh signals into the system: - Reintroduce your content to new audiences - Create follow-up or related content that loops back to it - Build videos that answer timeless questions (evergreen content)

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