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Siqi Chen engagement report

@blader - 416K followers on X

Measured over 21 original posts from a 30-day window, last computed on October 1, 2026.

Engagement

Middle of its size range
Per follower
0.016%
of 416K followers
Per impression
0.335%
19K views on a typical post
Reach
4.76%
of its followers see a post
Typical post
65
interactions (median)
Saved
0.052%
10 bookmarks on a typical post
Posting rate
2.7/day
active 70% of days
Peak time
00:00 UTC
Tuesday

A typical post picks up 65 interactions against 416K followers, an engagement rate of 0.016%. Measured over 21 original posts, its engagement rate beats 41% 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 19K times each, and 0.335% of those impressions turn into an interaction. That is about 4.66% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.7 posts a day over the last 30 days, with activity on roughly 70% of days. Most posts go out around 00:00 UTC, and Tuesday is the busiest day of the week. Of the 21 posts sampled, 76% carry an image or video and 33% link out. The account's strongest tracked post pulled 51K interactions, about 791x its own typical post.

Measured over 21 original posts from a 30-day window, last computed on October 1, 2026.

Compared with accounts its own size

Siqi Chen's engagement rate beats 41% 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 23% 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 0.016%, Siqi Chen sits above the 10th percentile of the 204,880 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.

p100.004%
p250.024%
p50 (median)0.143%
p750.678%
p902.55%
p9982.4%
Engagement rate as a share of followers, across the 204,880 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 percentile0.678%
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 00:00 UTC, and Tuesday 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: 00:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 00:00 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: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
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 video76% of posts+111%+108% to +115%34K
Outbound link33% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 76% 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.
  • 33% 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 255 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

  • Aug 22, 2026791x their median

    my 11 year old is taking a public speaking class they each had to speak on a random topic today she got 'dinosaurs' ... and ran out of things to say with 30 seconds left so she says: "and now please join me in a moment of silence for all those dead dinosaurs" 💀 proud dad

    49K2.5K18769431K viewsView on X
  • Sep 27, 2026259x their median

    Not sure what happened to Claude limits they went from barely usable to basically unlimited 😂

    16K34646477975K viewsView on X
  • Aug 5, 2026156x their median

    help i put screentime limits for youtube on my 11 year old’s laptop and i just found out she asked claude code to vibe code her own browser using electron and chromium to get around it what do i do now

    9.0K554430152644K viewsView on X
  • Sep 30, 202672x their median

    we found opus 5.5 to be 2X as efficient as gpt-6-sol in our internal https://t.co/QhA9tU0Lhp evals so i was not expecting 6.1-sol to improve on that much but to see it 3X the efficiency of opus 5.5 and 2.5X against even sonnet 5.5 is actually 🤯 this is an insane point release https://t.co/rKdWQEQe1O

    4.3K24113454319K viewsView on X
  • Jul 18, 202671x their median

    my new favorite of way of using fable: step 1. ask it to write a plan step 2: "please get second opinions from codex CLI using gpt-5.6-sol @ max effort and kimi CLI using kimi 3. Revise your plan with any sound findings. repeat until convergence or up to 5 rounds."

    4.3K12019028450K viewsView on X
  • Jul 22, 202653x their median

    Travis is back. https://t.co/3On4C0gO11

    3.1K183109101745K viewsView on X
  • Jul 17, 202638x their median

    looks like anthropic just silently removed the separate rate limit for fable in claude code: https://t.co/W2623TuKjS

    2.3K4615329261K viewsView on X
  • Jul 17, 202631x their median

    so kimi’s valuation is now a trillion bucks that is how this works right

    1.9K4938661K viewsView on X
  • Jul 26, 202627x their median

    My conversation with @dhh, co-founder of @37signals. 0:00 Cutting Rework From 50,000 Words To 25,000 2:54 Basecamp Was Built In 380 Hours 6:46 Unlimited Resources Build A Blob 10:22 Terminator Beats Avatar By A 1000x 15:24 The Printer DHH Never Wants To Upgrade 17:31 Millions In Profit From 16 Year-Old Software 20:10 The Beauty Of A Finished Product 22:54 I Would Quit Before Working In An Office 25:41 Four Uninterrupted Hours Or The Day Is Lost 31:21 Tobi Lütke Saw The AI Future First 38:51 Apple Pissed Him Off Enough To Switch 42:47 The 19 Year-Old Who Beat Apple 47:16 If Nobody Else Will Build It, I Will 52:02 The Need For Control, Independence, And Freedom 53:44 Chef's Choice, Not A Construction-Kit Burger 56:50 A New Computer Ready In 2 Minutes 1:00:33 A Cheaper Mac Will Never Win 1:02:27 The Best Ideas Sound Stupid At First 1:03:47 Out-Teach Your Competition 1:06:57 The Algorithms Broke Reciprocity 1:10:53 No Investors Is Freedom. No Customers Is Transcendence. 1:13:25 No One Gets To Tell Me What To Do 1:16:49 Your Moral Obligation To Buy A Ferrari 1:23:19 Costs Are The Only Thing You Control 1:26:49 Bezos Paid For The Promise 1:30:17 The Confidence To Say No To Everyone 1:32:59 The Day A Third Of The Company Left 1:36:49 Marc Andreessen Came To Help Includes paid partnerships.

    1.5K15963501.6M viewsView on X
  • Jul 29, 202625x their median

    i take back what i said about opus 5 initial results were promising / divergent but the more time i spent with it, the more infuriating of an experience it became my team feels the same way i am back on gpt-5.6-sol as my daily driver with fable and kimi 3 on planning / reviews

    1.4K481422087K 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.

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Reading these numbers

A typical post picks up 65 interactions against 416K followers, an engagement rate of 0.016%. Measured over 21 original posts, its engagement rate beats 41% 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 19K times each, and 0.335% of those impressions turn into an interaction. That is about 4.66% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.7 posts a day over the last 30 days, with activity on roughly 70% of days. Most posts go out around 00:00 UTC, and Tuesday is the busiest day of the week. Of the 21 posts sampled, 76% carry an image or video and 33% link out. The account's strongest tracked post pulled 51K interactions, about 791x its own typical post.

What is Siqi Chen's engagement rate on X?
Siqi Chen (@blader) has an engagement rate of 0.016%, based on the median interactions across 21 original posts from the last 30 days against 416,060 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.016%, Siqi Chen sits above the 10th percentile of the 204,880 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 @blader have real engagement?
Its engagement rate beats 41% 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 @blader post?
Most posts go out around 00:00 UTC, and Tuesday is its busiest day, at roughly 2.7 posts per day across the measured window.

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