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Garry Tan engagement report

@garrytan - 1.1M followers on X

Measured over 42 original posts from a 30-day window, last computed on September 1, 2026.

Engagement

Middle of its size range
Per follower
0.036%
of 1.1M followers
Per impression
0.57%
69K views on a typical post
Reach
6.36%
of its followers see a post
Typical post
394
interactions (median)
Saved
0.077%
53 bookmarks on a typical post
Posting rate
6.23/day
active 43% of days
Peak time
01:00 UTC
Friday

A typical post picks up 394 interactions against 1.1M followers, an engagement rate of 0.036%. Measured over 42 original posts, its engagement rate beats 55% of 3,758 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 69K times each, and 0.57% of those impressions turn into an interaction. That is about 6.36% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 6.2 posts a day over the last 30 days, though only 43% of days saw any activity at all. Most posts go out around 01:00 UTC, and Friday is the busiest day of the week. Of the 42 posts sampled, 52% carry an image or video and 52% link out. The account's strongest tracked post pulled 11K interactions, about 27x its own typical post.

Measured over 42 original posts from a 30-day window, last computed on September 1, 2026. Recurring tag: #sanfrancisco.

Compared with accounts its own size

Garry Tan's engagement rate beats 55% of the tracked X accounts closest to it in follower count (3,758 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 36% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.036%, Garry Tan sits above the 25th percentile of the 36,521 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.

p100.002%
p250.012%
p50 (median)0.08%
p750.434%
p902.10%
p99160.7%
Engagement rate as a share of followers, across the 36,521 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 107,166 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.08%
75th percentile0.434%
90th percentile2.10%
99th percentile160.7%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 01:00 UTC, and Friday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 01:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 01:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%50K
01:00 UTC-2%51K
02:00 UTC-3%50K
03:00 UTC-4%53K
04:00 UTC-6%43K
05:00 UTC-4%42K
06:00 UTC-4%48K
07:00 UTC-5%52K
08:00 UTC-4%60K
09:00 UTC-3%69K
10:00 UTC-2%72K
11:00 UTC-3%78K
12:00 UTC-2%86K
13:00 UTC-2%94K
14:00 UTC-4%97K
15:00 UTC-2%100K
16:00 UTC-3%97K
17:00 UTC-2%90K
18:00 UTC-1%84K
19:00 UTC-2%79K
20:00 UTC-1%74K
21:00 UTC-1%66K
22:00 UTC-2%57K
23:00 UTC-2%51K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Friday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Friday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%230K
Monday0%286K
Tuesday-2%276K
Wednesday-1%251K
Thursday-1%244K
Friday-3%252K
Saturday+3%227K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Aug 29, 202627x their median

    People often ask why today's tech wealth doesn't go towards more public works, like libraries, universities, and museums during the late 1800s. As far as I can tell the answer is that they would literally not be allowed to be built. In 2014, George Lucas, a long-time Bay Area resident who built Lucasfilm in the Bay, wanted to build a museum in the Presidio as a gift to the people of San Francisco, to be personally funded to the tune of ~$700 million. The Presidio Trust rejected it. He then tried to build it in his wife's hometown of Chicago, but local nonprofit Friends of the Parks sued and held the project up for two years, long enough for Lucas to give up on the city. The Lucas Museum of Narrative Art will finally open in Los Angeles next month after more than a decade of planning, eight years of construction, and over $1 billion personally spent by Lucas. Meanwhile, San Francisco has built no major museum projects since the 2016 expansion of SFMOMA, and no new libraries since the North Beach Branch in 2014. Public works, like so many other things, are bottlenecked not by donor will or available funding but by vetocracy

    9.5K854170851.3M viewsView on X
  • Aug 28, 202627x their median

    X has now confirmed a Chinese bot farm of 200K fake accounts intentionally trying to manipulate public opinion against data centers. People might want to consider how common this has become and how it is manipulating multiple policy discussions on social media. https://t.co/yEVmEFQNb8

    7.9K2.0K357258431K viewsView on X
  • Aug 28, 202624x their median

    So that Americans will continue to win for generations to come. https://t.co/1kLyCAwvXg

    7.5K1.2K4953121.6M viewsView on X
  • Aug 25, 202618x their median

    lmao https://t.co/y6BqsiuTQs

    6.5K26810760336K viewsView on X
  • Aug 28, 202610x their median

    Washington gives illegal immigrants $13,000 college tuition while out-of-state Americans pay $44,000, and the feds want it stopped https://t.co/AQHAhmYJWn

    3.3K7198325199K viewsView on X
  • Aug 24, 20269.7x their median

    Prediction: systems of record will need to become AI harnesses or face replacement by agents

    3.0K206389167710K viewsView on X
  • Aug 21, 20268.9x their median

    "Ban data centers!" is the "Defund the police!" of the current moral panic. It's a luxury belief policy idea that, if actually implemented, would have disastrous downstream consequences for the country. Love them or hate them, the entire global economy runs on these bad boys. https://t.co/Bjlc5RSCdf

    2.8K32028766175K viewsView on X
  • Jul 14, 20264.1x their median

    HOCHUL ENACTS NATION’S FIRST STATEWIDE DATA CENTER MORATORIUM https://t.co/qXmu2yHDo2

    670565553381.7M viewsView on X
  • Aug 24, 20263.5x their median

    The fact that SaaS co's are giving us agents instead of MCPs shows just how self-centered / narcissistic they are. I never wanted to "live in your product." Your product was the best way to get something done. If the best way to get it done is now headless, please let me do that.

    1.1K6715375395K viewsView on X
  • Aug 25, 20263.3x their median

    Form a view. Turn it into an artifact or experiment. Put it in contact with reality. Read the result without self-deception. Revise and run again.

    1.1K96872570K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

Recurring topics

#sanfrancisco

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

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Reading these numbers

A typical post picks up 394 interactions against 1.1M followers, an engagement rate of 0.036%. Measured over 42 original posts, its engagement rate beats 55% of 3,758 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 69K times each, and 0.57% of those impressions turn into an interaction. That is about 6.36% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 6.2 posts a day over the last 30 days, though only 43% of days saw any activity at all. Most posts go out around 01:00 UTC, and Friday is the busiest day of the week. Of the 42 posts sampled, 52% carry an image or video and 52% link out. The account's strongest tracked post pulled 11K interactions, about 27x its own typical post.

What is Garry Tan's engagement rate on X?
Garry Tan (@garrytan) has an engagement rate of 0.036%, based on the median interactions across 42 original posts from the last 30 days against 1,088,610 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.036%, Garry Tan sits above the 25th percentile of the 36,521 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @garrytan have real engagement?
Its engagement rate beats 55% of the tracked X accounts closest to it in follower count (3,758 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @garrytan post?
Most posts go out around 01:00 UTC, and Friday is its busiest day, at roughly 6.23 posts per day across the measured window.

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