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Paul Graham engagement report

@paulg - 5.4M followers on X

Measured over 73 original posts from a 30-day window, last computed on October 26, 2026.

Engagement

Middle of its size range
Per follower
0.031%
of 5.4M followers
Per impression
0.89%
187K views on a typical post
Reach
3.44%
of its followers see a post
Typical post
1.7K
interactions (median)
Saved
0.143%
267 bookmarks on a typical post
Posting rate
6.9/day
active 97% of days
Peak time
15:00 UTC
Wednesday

A typical post picks up 1.7K interactions against 5.4M followers, an engagement rate of 0.031%. Measured over 73 original posts, its engagement rate beats 51% of 20,444 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 187K times each, and 0.89% of those impressions turn into an interaction. That is about 3.44% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 6.9 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 15:00 UTC, and Wednesday is the busiest day of the week. Of the 73 posts sampled, 38% carry an image or video, 18% are part of a thread and 14% link out. The account's strongest tracked post pulled 92K interactions, about 55x its own typical post. Recurring topics include #designoftheday, #php2shell.

Measured over 73 original posts from a 30-day window, last computed on October 26, 2026. Recurring tags: #designoftheday, #php2shell.

Compared with accounts its own size

Paul Graham's engagement rate beats 51% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 44% 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 0.031%, Paul Graham sits above the 25th percentile of the 204,491 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.

p100.004%
p250.024%
p50 (median)0.143%
p750.677%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 204,491 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,891 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 percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.677%
90th percentile2.55%
99th percentile82.4%

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 15:00 UTC, and Wednesday 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: 15:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 15:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video38% of posts+111%+108% to +115%34K
Outbound link14% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 38% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 14% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
  • Its average post runs 279 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Sep 6, 202655x their median

    I predicted they’d call off Congress until the election to stop our new Epstein bill. Johnson said on TV that was “stupid” and “nonsensical.” But then he got a call from “upstairs” and canceled Congress from the middle of September until the election. https://t.co/LZ7GvhXvRq

    72K18K2.1K6311.6M viewsView on X
  • Apr 1, 202137x their median

    My best career advice: At every job you should either learn or earn. Either is fine. Both is best. But if it's neither, quit.

    47K15K178738View on X
  • Sep 17, 202634x their median

    BREAKING: ADHD researchers confirm that having "one single appointment" at 3:00 PM successfully destroys the entire day leading up to it. 1/6

    51K4.0K4631.2K5.9M viewsView on X
  • Aug 10, 202614x their median

    We asked an unreleased research version of Claude to take a stab at the Riemann hypothesis. It didn’t solve it, but it did make strides on a related problem: it increased the lower bound for the fraction of zeros of the Riemann zeta function that satisfy the hypothesis from 41.6% to 67.2%. https://t.co/aZDvqqhHRi

    18K2.0K9371.3K10M viewsView on X
  • Aug 21, 202611x their median

    There may not be many people left in 10 years who can write, or want to read, things longer than a page or two. But there will be at least a few of us, and we'll be a powerful club.

    16K1.7K706248694K viewsView on X
  • Aug 16, 202611x their median

    There is very simple math behind the need to tax billionaires. Billionaire wealth is increasing at an accelerating rate vastly outpacing the overall rise in GDP. This means that their wealth is not growing because the whole pie is growing. Their wealth is growing at your expense and the trend is accelerating. If you are not a billionaire and you and your children want to own things, this is your fight.

    13K2.7K2.5K3541.1M viewsView on X
  • Aug 23, 202610x their median

    Someone asked what I'd do if I were 17. I'd learn how to build LLMs from scratch, and then train ones as powerful as I could with whatever hardware I could get access to.

    15K9856412541.5M viewsView on X
  • Aug 11, 20269.9x their median

    We can finally talk about it: We found a way to extract hidden reasoning of frontier models using a vulnerability in the APIs of every frontier AI company. We verified that our reasoning token count matches billed API thinking tokens 1:1 for most of the prompts we queried. https://t.co/S7wN8aP3X7

    14K2.0K3826203.5M viewsView on X
  • Sep 19, 20269.8x their median

    Remember how eagerly the press swallowed stories about how Twitter was going to crash after Elon bought it? How could they have believed that someone who could run rocket and car companies couldn't run a forum? https://t.co/4XaSkqmAqU

    15K8886662157.3M viewsView on X
  • Oct 8, 20269.1x their median

    Talked to someone recently who knows a lot about defense tech, and he made an interesting point: the test of most military hardware right now is whether the Ukrainians want it. They have a hot war going against a determined opponent, and they know what works.

    14K7983951441.9M 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

#designoftheday#php2shell

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 1.7K interactions against 5.4M followers, an engagement rate of 0.031%. Measured over 73 original posts, its engagement rate beats 51% of 20,444 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 187K times each, and 0.89% of those impressions turn into an interaction. That is about 3.44% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 6.9 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 15:00 UTC, and Wednesday is the busiest day of the week. Of the 73 posts sampled, 38% carry an image or video, 18% are part of a thread and 14% link out. The account's strongest tracked post pulled 92K interactions, about 55x its own typical post. Recurring topics include #designoftheday, #php2shell.

What is Paul Graham's engagement rate on X?
Paul Graham (@paulg) has an engagement rate of 0.031%, based on the median interactions across 73 original posts from the last 30 days against 5,440,735 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.031%, Paul Graham sits above the 25th percentile of the 204,491 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 @paulg have real engagement?
Its engagement rate beats 51% of the tracked X accounts closest to it in follower count (20,444 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 @paulg post?
Most posts go out around 15:00 UTC, and Wednesday is its busiest day, at roughly 6.9 posts per day across the measured window.

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