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JetBrains engagement report

@jetbrains - 215K followers on X

Measured over 17 original posts from a 30-day window, last computed on October 4, 2026.

Engagement

Middle of its size range
Per follower
0.022%
of 215K followers
Per impression
0.555%
8.6K views on a typical post
Reach
4.02%
of its followers see a post
Typical post
48
interactions (median)
Saved
0.104%
9 bookmarks on a typical post
Posting rate
0.93/day
active 37% of days
Peak time
14:00 UTC
Thursday

A typical post picks up 48 interactions against 215K followers, an engagement rate of 0.022%. Measured over 17 original posts, its engagement rate beats 34% 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 8.6K times each, and 0.555% of those impressions turn into an interaction. That is about 4.02% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.93 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 14:00 UTC, and Thursday is the busiest day of the week. Of the 17 posts sampled, 94% carry an image or video, 12% are part of a thread and 35% link out. The account's strongest tracked post pulled 533 interactions, about 11x its own typical post.

Measured over 17 original posts from a 30-day window, last computed on October 4, 2026.

Compared with accounts its own size

JetBrains's engagement rate beats 34% of the tracked X accounts closest to it in follower count (20,444 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 28% 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 0.022%, JetBrains 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 14:00 UTC, and Thursday 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: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 14:00 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: Thursday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Thursday
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 video94% of posts+111%+108% to +115%34K
Outbound link35% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 94% 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.
  • 35% 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 280 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

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 29, 202611x their median

    GPT-6.1 Sol is out! Our colleague @kristel_tech asked GPT-6 Sol and GPT-6.1 Sol to "Build a cinematic, photorealistic rocket launch scene using Three.js" GPT-6.1 Sol: $0.553 | 17 mins GPT-6 Sol: $1.01 | 22 mins Try it in JetBrains Air or Junie. @OpenAIDevs https://t.co/okJbuTl7zf

    4772724564K viewsView on X
  • Oct 1, 20268.6x their median

    We've reimagined JetBrains IDEs to become the ultimate agentic workbench. Air is an open hub for agents inside your IDE: -Any agents to run (Claude, Codex & many more) -Agents are more efficient with IDE intelligence -Free Junie Lite agent bundled -Cloud runs via Air Teams ⬇️ https://t.co/9s0vpvyL6z

    29457332860K viewsView on X
  • Jul 30, 20268.2x their median

    We tested the RTK agent skill, which promises 60–90% token savings. See what our testing revealed and tell us what to test next. We even got a response from the maintainer, who confirmed that a fix is coming soon! 🙌 https://t.co/h4e3C8Bhw8 https://t.co/NJf6f5BqdO

    337262831.0M viewsView on X
  • Sep 10, 20266.5x their median

    Jake Wharton refuses to code with AI. When he left Cash App, he published nine requirements for his next job. Number one was: No AI. Our full conversation with the legendary Android developer is out now: layoffs, AI, Google and Kotlin in 2026. https://t.co/cF5TxO3sxt

    261356921K viewsView on X
  • Sep 13, 20266.3x their median

    The tools have evolved, the possibilities have expanded, the questions have become more challenging... and we're embracing it with the same creative spirit. Happy Programmer’s Day to the people building what's next! https://t.co/thTPwWW2Kt

    2395011411K viewsView on X
  • Aug 4, 20265.0x their median

    Your project runs on Markdown now, and we're giving it the tooling it deserves 👀 Get the first look at agentic markdown support in JetBrains IDEs. Join the waitlist → https://t.co/UfAFPnXlSz https://t.co/7RQgbA7wFO

    1992311854K viewsView on X
  • Aug 10, 20264.6x their median

    Figma Connect for WebStorm is now available. Set it up once, and enjoy a seamless IDE integration maintained with every WebStorm release. Select any layer from your @Figma file, get the full design spec in your IDE, and pass it straight to your AI agent: component hierarchy, spacing, and design variables – all from the source. Your agent implements from the actual spec instead of approximating your design system. This is the first stage of a visual design-to-code workflow in @WebStormIDE. There’s more to come. Check it out: https://t.co/fHXgMEjfPA

    19912811.3M viewsView on X
  • Aug 3, 20264.5x their median

    KotlinLLM is now open source! 🚀 It's a research prototype that lets you delegate logic to an LLM at runtime as explicit, persistent, and portable Kotlin code. The code evolves as your app encounters new scenarios during development and runs as plain Kotlin once generated. Learn more 👉 https://t.co/O71OERFwQ8 Explore it on GitHub 👉 https://t.co/Jj9XuDOKjt

    169289828K viewsView on X
  • Sep 22, 20264.2x their median

    This product video was generated entirely by Claude Opus 5.5. Our colleague @kristel_tech gave it @HeyGen’s HyperFrames skills and pointed it at https://t.co/yShoSTdQq3 – out came this Kotlin promo. Try it in JetBrains Air or Junie. https://t.co/SIzJCdvFjZ

    187111118K viewsView on X
  • Aug 14, 20263.9x their median

    Same prompt. Different results 👀 We built the same app with Gemini 3.6 and 3.7 Flash. Both worked. But 3.7 gave us the stronger codebase: better architecture, clean build/lint results, and a more maintainable foundation. Try it in Junie, Air, or any JetBrains IDE. https://t.co/g5oxOCIfX9

    1581610223K 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 48 interactions against 215K followers, an engagement rate of 0.022%. Measured over 17 original posts, its engagement rate beats 34% 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 8.6K times each, and 0.555% of those impressions turn into an interaction. That is about 4.02% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.93 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 14:00 UTC, and Thursday is the busiest day of the week. Of the 17 posts sampled, 94% carry an image or video, 12% are part of a thread and 35% link out. The account's strongest tracked post pulled 533 interactions, about 11x its own typical post.

What is JetBrains's engagement rate on X?
JetBrains (@jetbrains) has an engagement rate of 0.022%, based on the median interactions across 17 original posts from the last 30 days against 215,243 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.022%, JetBrains 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 @jetbrains have real engagement?
Its engagement rate beats 34% 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 @jetbrains post?
Most posts go out around 14:00 UTC, and Thursday is its busiest day, at roughly 0.93 posts per day across the measured window.

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