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Brad Traversy engagement report

@traversymedia - 360K followers on X

Measured over 6 original posts from a 30-day window, last computed on September 2, 2026.

Engagement

Per follower
0.072%
of 360K followers
Per impression
1.67%
16K views on a typical post
Reach
4.34%
of its followers see a post
Typical post
260
interactions (median)
Saved
0.422%
66 bookmarks on a typical post
Posting rate
0.27/day
active 27% of days
Peak time
09:00 UTC
Monday

Early reading. We have captured 6 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 260 interactions against 360K followers, an engagement rate of 0.072%. Posts are seen about 16K times each, and 1.67% of those impressions turn into an interaction. That is about 4.34% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.27 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 09:00 UTC, and Monday is the busiest day of the week. Of the 6 posts sampled, 50% carry an image or video and 50% link out. The account's strongest tracked post pulled 1.1K interactions, about 4.3x its own typical post. Only 6 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 6 original posts from a 30-day window, last computed on September 2, 2026.

Where this sits in the catalog

At 0.072%, Brad Traversy sits above the 25th percentile of the 68,576 accounts in this comparison. That places it in the below the median band, which runs 0.016% to 0.1%.

p100.002%
p250.016%
p50 (median)0.1%
p750.5%
p902.09%
p99116.4%
Engagement rate as a share of followers, across the 68,576 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 55,420 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 percentile0.5%
90th percentile2.09%
99th percentile116.4%

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 09:00 UTC, and Monday 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: 09:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 09:00 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: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
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 video50% of posts+111%+108% to +115%34K
Outbound link50% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 50% 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.
  • 50% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 842 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

  • Mar 27, 20264.3x their median

    I know some people are sick of all the AI content everywhere. Tutorials are not dead at TM. Working hard on a 2026 React Native crash course for youtube. Start recording Monday 😀 Quick Screengrab/Preview: https://t.co/XCFcJ8KRl6

    1.0K6154729K viewsView on X
  • Jan 16, 20263.8x their median

    AI generated code is causing some serious problems. Stats show that AI usage has come with a 1.7x increase in bugs. 32% of senior devs have shipped AI generated code, and research shows 45% of it contains security flaws. The problem isn’t AI. It’s over trusting it and shipping oversized PRs with less oversight. Check out the latest video on this topic where @dennisivy11 shares how you can still use AI and secure your code 👇

    79086861358K viewsView on X
  • Jun 23, 20263.5x their median

    Finally finished my homelab server rack 😊 video coming soon Inside: - Sysracks enclosed cabinet - TP-Link Omada 2.5G / 10G core switch - 2U Intel Core Ultra 9 Docker/staging server - GMKTec EVO-X2 AI/automation box (Hermes box) - Dell PowerEdge lab server (Proxmox) - QNAP 8-bay rack NAS with 8x8TB RAID 6 - Synology NAS during migration - Dual APC UPS units - AC Infinity rack cooling - Sonos + smart-home gear tucked in cleanly This runs my internal dev/staging services, local DNS, reverse proxy, storage, backups, automation, and AI agent stack. Proxmox & virtualization learning server. Completely unnecessary. Extremely satisfying. #homelab #serverrack #selfhosted #homeserver #networking

    7915247944K viewsView on X
  • Aug 28, 20263.4x their median

    When using AI to code, be careful about constantly switching between projects. It may not feel exhausting in the moment, but it can burn you out fast. The goal shouldn't be to create as much as possible. It should be to build useful things and actually finish them.

    75870541324K viewsView on X
  • Aug 13, 20263.2x their median

    I seriously cannot stand these people anymore. I don't know what happened to a good chunk of the tech community. I used to connect with these people because they loved technology like I do. They wanted to learn, build, experiment, and talk about what was possible. Over the past couple of years, though, I've watched a huge portion of that curiosity turn into pure skepticism, pessimism, and hostility. There are two ridiculous extremes in the AI debate. On one end, you have people claiming that non-developers can vibe code anything and that anyone can instantly become a developer. On the other, you have people who treat AI like politics and completely lose their minds over anything associated with it. Lately, I see far more of the latter, and honestly, they are even more irrational and insufferable than the vibe coders. I also know that many of them use AI themselves. They don't actually care about having an honest discussion. AI is just their latest excuse to shit on everyone and everything while pretending they are taking some principled stand. I used to follow politics, but the audiences around political content, on both the left and the right, became so toxic and irrational that I eventually stopped caring about any of it. I appreciate level-headed people who can discuss complicated topics without turning everything into a tribal war. That is what I once believed the tech community was. It does not feel that way anymore, and it is incredibly demotivating and depressing. I am not saying this describes most people, but it describes a large and increasingly loud group. If you find yourself making stupid comments like this, take a step back and ask what you are actually contributing. Criticism is healthy. Skepticism is necessary. Blind hostility, personal attacks, and performative outrage are not. You do not have to love AI. You do not have to use it. You can question the hype, the ethics, the business models, and the effect it may have on our industry. But if you cannot discuss any of that without attacking people, assuming the worst, or turning every conversation into a moral crusade, then you are not protecting the tech community. You are helping destroy the very curiosity and openness that made it worth being part of in the first place. Sorry for the long post

    6974879853K viewsView on X
  • Apr 21, 20262.9x their median

    I’m creating a lot of cool shit lately, but it feels like I’m becoming more of a project manager than a developer 😐

    66918461064K viewsView on X
  • May 3, 20262.5x their median

    My take has changed from “vibe coding will never work” to “vibe coding may work with future models.” But only if you understand software development and architecture. That if will never change for me.

    5403261830K viewsView on X
  • Apr 3, 20262.3x their median

    AI is amazing, and getting into things like OpenClaw has opened my eyes to how much you can automate. But I’m starting to feel the downside too. At a certain point, it starts feeling like I’m outsourcing my own thinking. It’s both cool and scary.

    5143349321K viewsView on X
  • Mar 11, 20262.3x their median

    https://t.co/BWLf3BeDIG

    5086419352K viewsView on X
  • Jun 30, 20262.0x their median

    I'm losing it 😂 https://t.co/9Y6dSKxP31

    4801329134K 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 260 interactions against 360K followers, an engagement rate of 0.072%. Posts are seen about 16K times each, and 1.67% of those impressions turn into an interaction. That is about 4.34% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.27 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 09:00 UTC, and Monday is the busiest day of the week. Of the 6 posts sampled, 50% carry an image or video and 50% link out. The account's strongest tracked post pulled 1.1K interactions, about 4.3x its own typical post. Only 6 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is Brad Traversy's engagement rate on X?
Brad Traversy (@traversymedia) has an engagement rate of 0.072%, based on the median interactions across 6 original posts from the last 30 days against 360,415 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.072%, Brad Traversy sits above the 25th percentile of the 68,576 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 @traversymedia have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @traversymedia post?
Most posts go out around 09:00 UTC, and Monday is its busiest day, at roughly 0.27 posts per day across the measured window.

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