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Gergely Orosz engagement report

@GergelyOrosz - 354K followers on X

Measured over 24 original posts from a 30-day window, last computed on September 2, 2026.

Engagement

Middle of its size range
Per follower
0.177%
of 354K followers
Per impression
0.815%
76K views on a typical post
Reach
21.7%
of its followers see a post
Typical post
622
interactions (median)
Saved
0.145%
110 bookmarks on a typical post
Posting rate
3.4/day
active 33% of days
Peak time
10:00 UTC
Wednesday

A typical post picks up 622 interactions against 354K followers, an engagement rate of 0.177%. Measured over 24 original posts, its engagement rate beats 74% of 6,874 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 76K times each, and 0.815% of those impressions turn into an interaction. That is about 21.5% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.4 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 10:00 UTC, and Wednesday is the busiest day of the week. Of the 24 posts sampled, 42% carry an image or video, 50% are part of a thread and 25% link out. The account's strongest tracked post pulled 3.6K interactions, about 5.8x its own typical post.

Measured over 24 original posts from a 30-day window, last computed on September 2, 2026.

Compared with accounts its own size

Gergely Orosz's engagement rate beats 74% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 8 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 42% 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 0.177%, Gergely Orosz sits above the 50th percentile of the 66,258 accounts in this comparison. That places it in the above the median band, which runs 0.1% to 0.499%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99119.6%
Engagement rate as a share of followers, across the 66,258 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 56,968 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 percentile0.016%
50th percentile0.1%
75th percentile0.499%
90th percentile2.09%
99th percentile119.6%

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 10:00 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: 10:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 10:00 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 video42% of posts+111%+108% to +115%34K
Outbound link25% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 42% 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.
  • 25% 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 524 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

  • Aug 26, 20265.8x their median

    Well this is damning and explains SO MUCH about why Meta is losing its best engineers; why morale is rock-bottom; and why an engineering culture built up in 20 years was destroyed overnight. Zuck + execs wanted to lay off ~60% of staff. When the business does better than ever. https://t.co/36hOyxAz9S

    3.3K18812258447K viewsView on X
  • Aug 28, 20264.8x their median

    How Windows lost the mindshare of developers is something that needs to be studied. Microsoft has never stopped investing in standout dev tools (🫡 to the Visual Studio Team), but the OS, as a whole, became incredibly dev-hostile. Mac ate up their dev market share by doing... nothing, really? As in nothing focusing on devs, just having an OS that was not annoying AF as a dev

    2.6K8029536204K viewsView on X
  • Aug 31, 20264.0x their median

    I don't think most of us outside of OpenAI realize just how Codex-pilled everyone inside OpenAI is Because the Codex that we see and use is nowhere nearly as powerful as the one they see and use inside (Theirs integrated anywhere & everywhere inside OpenAI, nearly full access)

    2.4K27959302K viewsView on X
  • Sep 26, 20213.7x their median

    When you ask "Why did Company build 7 of the same products that all failed?", it always starts with the current solution struggling. This is an opportunity. Not to fix - which doesn't get you promoted - but to start anew. An all too real story about Promotion Driven Development:

    1.8K33023117View on X
  • Aug 28, 20263.3x their median

    Seeing internships become fewer at many tech companies tells me a bunch of stuff: 1. No plans to convert a year out. You run internships when you know a year later you’ll do new grad hiring 2. Not enough capacity for mentoring. Interns need at least one mentor - which takes time away from an eng doing whatever they do. On larger teams there’s more “slack” time. On small teams, rarely 3. Team dynamics less important. Interns really boost morale on teams - found this underrated, always. 4. Career growth not important. Mentoring interns grows that mentorship skill that is (used to be?) important for seniors. Food for thought on all

    1.9K747816133K viewsView on X
  • Sep 2, 20263.2x their median

    I still find it so wild that SO MANY European banks schedule 1-2x per month 4-8 hour maintenance windows between 10pm-6am local time. INSTEAD of biting the bullet and learning how to do zero downtime migrations + infra upgrades. Devs pull all-nighters instead and learn nothing

    1.8K5312619106K viewsView on X
  • Sep 2, 20262.9x their median

    At this point I just want models to be faster and cheaper. I have enough intelligence. Please, size doesn't matter any more, I need performance.

    1.5K661532757K viewsView on X
  • Aug 29, 20262.4x their median

    It’s a weird complaint to have but with AI agents, that “flow state” during coding is gone (because the coding itself is gone.) Every time I talk with a dev about work now vs before, it seems to come up, like today with a former colleague. Are we over-glorifying it (I mean it wasn’t all roses, it was also frustration) or is it something important / relevant they we had but now don’t really have?

    1.2K3026632155K viewsView on X
  • Jan 21, 20232.3x their median

    Substack launched analytics insights and: wow. Thank you to everyone reading @Pragmatic_Eng! https://t.co/X6owJ8af3N

    1.3K23714698K viewsView on X
  • Aug 31, 20262.1x their median

    I just heard: a large company is moving from GChat (Google's Chat product) to Slack, because... Slack has much better agent operability (true) Who thought AI+agents would be a big selling point for Slack? Or that Google would sleep on agents + GChat!

    1.1K2611214296K 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 622 interactions against 354K followers, an engagement rate of 0.177%. Measured over 24 original posts, its engagement rate beats 74% of 6,874 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 76K times each, and 0.815% of those impressions turn into an interaction. That is about 21.5% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.4 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 10:00 UTC, and Wednesday is the busiest day of the week. Of the 24 posts sampled, 42% carry an image or video, 50% are part of a thread and 25% link out. The account's strongest tracked post pulled 3.6K interactions, about 5.8x its own typical post.

What is Gergely Orosz's engagement rate on X?
Gergely Orosz (@GergelyOrosz) has an engagement rate of 0.177%, based on the median interactions across 24 original posts from the last 30 days against 354,308 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.177%, Gergely Orosz sits above the 50th percentile of the 66,258 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 @GergelyOrosz have real engagement?
Its engagement rate beats 74% of the tracked X accounts closest to it in follower count (6,874 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 @GergelyOrosz post?
Most posts go out around 10:00 UTC, and Wednesday is its busiest day, at roughly 3.4 posts per day across the measured window.

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