How the X algorithm works: a plain guide

You are trying to work out why one post travels and another sits still. The first thing to know about the X algorithm is that no single formula decides it. A pipeline runs every time someone opens the For You feed, and X has published the code for it.

This guide walks that pipeline in order: where posts come from, what gets removed, how what is left is scored, what changes the score afterwards and what decides whether a post can be shown at all. Every claim is labelled as something the code shows, something X says, or our own reading, so you can tell which is which.

How does the X algorithm work in one picture

Each time you open For You, X builds the feed again from scratch. The code describes six stages: gather candidate posts, filter, score, adjust, check visibility, then blend in ads and other items. X's Help Center describes the same shape in plainer words.

It says X finds content inside and outside your network, ranks it with a neural network trained on your interactions, and filters harmful, abusive or spammy content before showing it. It also says the system distils roughly 500 million posts a day down to a handful of top posts for your feed.

1. Gather. Three sources supply candidate posts: one for accounts you follow, two for accounts you do not.
2. Filter. Posts that cannot or should not be shown to this viewer are removed before any scoring.
3. Score. A model predicts how likely the viewer is to act on each post, and weights turn those chances into one number.
4. Adjust. Rules change the score for variety, for accounts the viewer does not follow and for new authors.
5. Check. The top posts go through visibility filtering, which answers allow, notice, interstitial or drop.
6. Blend. Ads, Who to Follow and prompts are mixed in with the posts.

What does X publish, and what can't the code tell you

X publishes the code that builds the For You feed at github.com/xai-org/x-algorithm, under an Apache 2.0 licence. The README says "our aim is for the public to be able to understand how posts are distributed on X". That makes it the best primary source there is, and it is still not the whole picture.

An older release exists. X first published recommendation code in March 2023, in an earlier repository that showed parts of the system. Write ups from that time describe that version, not the one in this guide.

X's engineering account announced the release, saying the new algorithm is powered by the same transformer architecture as xAI's Grok model. The Phoenix README adds that earlier releases shipped a sample model, while the current release ships the production code. An article about an older release may describe something that no longer runs. For the accounts X suggests rather than the posts, see how Who to follow chooses accounts.

For You or Following: which feed is your post competing in

The two feeds work differently. According to the Help Center, Following shows posts only from accounts you follow, newest first. For You mixes accounts and Topics you follow with recommended posts and ranks them for you.

The code ships separate servers for the three: for_you_server.rs, following_feed_server.rs and ranked_following_feed_server.rs. The Help Center page we could read describes Following as newest first. If your app shows a sort option next to Following, check which one is selected before you draw conclusions about reach.

In a newest first feed, timing is plain arithmetic: an older post sinks as newer ones arrive. We cover that in our guide to the best time to post on X. The rest of this guide is about For You.

Where do the posts in a For You feed come from

Three sources run at the same time, and each one returns candidate posts. Before they run, X loads context about the viewer: recent engagements (the main input to the model), the follow list, blocks and mutes, muted keywords, posts already seen and followed topics.

Our reading: a post reaches people who do not follow you only through the two out of network sources. Both are driven by what the viewer, and people who engage like them, have engaged with. Follower count is not one of the sources. For what the weights mean for replies, reposts and likes in particular, see our guide to X engagement signals.

Which posts are filtered out before ranking

The README lists 19 filters that run before any scoring. Most are housekeeping. Here are the ones that matter most to a person writing posts, in plain words.

The 48 hour limit is an age cap on candidates. It is one of the few hard numbers about time in the whole pipeline, and we come back to it when we look at the claim that some hours are magic.

How does X score the posts that are left

A transformer model called Phoenix reads the viewer's recent engagement history and each candidate post, and predicts the chance of many actions at once. Then a scorer combines those chances with weights: final score equals the sum of weight times chance, action by action.

The model predicts five groups of actions, according to the README.

The weights live in a parameter file whose header says it is mirrored from configuration defaults, last synced 8 October 2026. These are the defaults, not a promise about what is live. X re-syncs the file often: by 13 October 2026 a like was 0.66 and not interested minus 52.272.

Two things follow, and they are our reading. A post has no single score, because the chances depend on who is looking. And the table is a map of what the model is asked to care about, not a recipe, because the README says live values come from a configuration system and are tested on a small share of traffic.

What changes the score after ranking

After scoring, a few adjustments reshape the list. The README describes three, and the docs folder describes a fourth.

A separate reranking service also trades a little score for less similarity between neighbours in the list, using a determinantal point process over the posts' embeddings. In plain words, it avoids stacking near twins side by side.

The fourth adjustment is the best documented change in the repository. The docs folder uses it as a worked example of how a change gets published.

1. 10 July 2026

   Test begins

   Random users get a boost value of 5, 10, 15 or 20. Most users have 0.

2. 13 July 2026

   Broad launch

   After positive early results, a value of 20 goes out widely while testing of other values continues.

3. 24 July 2026

   Lowered to 15

   The notes say people were not seeing as much discussion as they wanted, with many posts coming from accounts they did not follow during the World Cup.

Our reading: a value that went from a test to a broad launch to a lower number in two weeks is a reminder that these numbers are tuned by people, often on feedback. Do not build a posting plan on a number that is likely to change next month.

Who decides whether a post can be shown at all

Visibility filtering does. After the top posts are selected, the scorer's order stops mattering for any post that visibility filtering drops. The README puts it in one line: "Ranking decides the order. Visibility filtering decides whether a post can be shown at all."

For each post and viewer, visibility filtering gives one of four answers:

• Allow: show the post normally.
• Notice: show the post with a notice attached to it.
• Interstitial: show it behind a gate the viewer can tap through, for example for adult or graphic media.
• Drop: do not show it.

"The first rule that answers drop ends the evaluation," says the README. A further set of rules applies only to recommendations from accounts the viewer does not follow, and those rules can only drop. Spam caught at high recall is the README's example.

The rules registry groups the Home timeline rules into things like author state (suspended, deactivated or protected accounts), the viewer's blocks and mutes, safety labels, spam, legal takedowns and sensitive media. X's Help Center adds that it restricts the reach of posts that violate its policies, for example by excluding them from search, trends and recommended notifications, or by limiting discoverability to the author's profile.

A Community Note is a different thing: contributors write and rate it. If one appears on your post, read our guide to X Community Notes.

What gets mixed in after ranking

The ranked posts are one source for the final feed. The README says the others add ads, Who to Follow, prompts and push to home items. A blender interleaves them, the default ads blender reorders posts so that ads sit next to them, and Who to Follow and prompts go at fixed positions.

• Ranked posts come from the pipeline above.
• Ads are placed by the blender.
• Who to Follow and prompts sit at fixed slots.

Our reading: a post's place in someone's feed is not a clean read of its rank. Ads and fixed slots sit around it, so two posts with similar scores can look further apart on the screen than they were in the ranking.

What else lives in the repository

The repository is bigger than the feed. Most of it is the machinery that labels posts and accounts, which is what visibility filtering reads.

Two label systems are worth knowing by name:

• Grox holds classifiers for categories such as spam, adult content and violent media.
• Agatha labels accounts from how many blocks, reports and spam reports they receive relative to favorites.

Our reading: the second one is why audience fit matters more than a big number. An account that collects blocks and reports for every like it earns can pick up a label, and labels feed the visibility rules. Three narrower questions have their own guides: how X ranks replies under a post, why posts reach the wrong audience and whether editing a post hurts its reach.

The README is open about what it leaves out: the model prompts used by the Grox classifiers and some rules, to reduce the risk that people use them to game the system.

Which X algorithm myths does the code support

Most algorithm advice is a claim about a rule. Here are common claims and what the primary sources show. "Not found" means not found in the files and pages we read, and because some rules are withheld, that is not proof of absence.

If you want the neighbouring facts, our guides cover when to post, what the badges mean and how automation rules work.

What does this mean for the posts you write

None of this is a recipe, and nothing here promises reach. But the pipeline does give you better questions to ask of a draft. Everything in this list is our reading of the sources above.

Do not read this as a licence to bait. The negative weights are the largest in the table, and a post that earns mutes and blocks pays for it with every viewer who reacts that way.

To check your own results, calculate your engagement rate post by post. Kairo Post's analytics shows which topics and hours work for your own account, which is a better guide than a general tip.

How to keep up as the algorithm changes

The code, the weights and the filters all change. The only reliable habit is to check the source rather than the summary.

1. Open the README and the docs folder

   Look for dated change notes. The bidirectional follow notes are the model of what a published change looks like.

2. Read the sync stamp

   The weights file header says when it was last mirrored from configuration. If the date is old, the numbers may be too.

3. Open Under the Hood for your account

   Check whether any visibility labels apply to you before you blame the ranking.

4. Ask where every tip comes from

   If it cannot point to a file or a Help Center page, treat it as speculation and test it on your own posts.