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Sally Stockholm engagement report

@aiwithsally - 245K followers on X

Measured over 22 original posts from a 30-day window, last computed on September 9, 2026.

Engagement

Middle of its size range
Per follower
0.113%
of 245K followers
Per impression
1.23%
23K views on a typical post
Reach
9.22%
of its followers see a post
Typical post
277
interactions (median)
Saved
0.011%
2 bookmarks on a typical post
Posting rate
1.53/day
active 70% of days
Peak time
19:00 UTC
Tuesday

A typical post picks up 277 interactions against 245K followers, an engagement rate of 0.113%. Measured over 22 original posts, its engagement rate beats 64% 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 23K times each, and 1.23% of those impressions turn into an interaction. That is about 9.22% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 70% of days. Most posts go out around 19:00 UTC, and Tuesday is the busiest day of the week. Of the 22 posts sampled, 59% carry an image or video. The account's strongest tracked post pulled 3.0K interactions, about 11x its own typical post.

Measured over 22 original posts from a 30-day window, last computed on September 9, 2026.

Compared with accounts its own size

Sally Stockholm's engagement rate beats 64% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 7 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 52% 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 0.113%, Sally Stockholm sits above the 50th percentile of the 65,980 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%
p99120.0%
Engagement rate as a share of followers, across the 65,980 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 57,142 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 percentile120.0%

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 19:00 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: 19:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 19:00 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 video59% of posts+111%+108% to +115%34K
Outbound link0% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 59% 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.
  • 0% 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 621 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 8, 202611x their median

    Gemini 3.8 Flash and Muse Spark 1.3 are two of the most clearly benchmaxxed models we've seen yet. Despite being comparable to both GPT-6 and Fable 5.1 on Terminal Bench 2.1, their Terminal Bench 4.0 performance is markedly worse. (1/5)🧵 https://t.co/K2ccQjWm11

    2.6K15911277457K viewsView on X
  • Sep 1, 20267.2x their median

    Fable 5.1 is rolling out right now!! It is selectable in Claude Code v2.1.257. WE ARE SO BACK! https://t.co/V9PMOlJqn2

    1.8K549336125K viewsView on X
  • Aug 26, 20263.6x their median

    MiniMax H3 Max, a post-trained version of MiniMax H3 developed by fal, debuts at #1 in Image to Video and #3 in Text to Video on the Artificial Analysis Video Leaderboards with Audio, ahead of the base MiniMax H3 on both MiniMax H3 Max is built and served by fal, and post-trained from MiniMax H3. fal describes it as being tuned for stronger prompt adherence and better aesthetics, co-optimized with their custom inference stack for higher throughput. It generates 5 to 15 second clips with native audio at up to 768p. In the Artificial Analysis Video Arena, H3 Max ranks #1 in Image to Video with Audio, narrowly ahead of ByteDance's Dreamina Seedance 2.0 720p. It ranks #3 in Text to Video with Audio, on a board where the top three models sit within 6 points of each other. fal prices MiniMax H3 Max at $0.04 per second of 768p video ($2.40 per minute). The base MiniMax H3 endpoint on fal is $0.06 per second at the same resolution. fal has stated its intent to release the weights for MiniMax H3 Max. If it does, H3 Max would become the highest ranked open weights model on both boards, ahead of MiniMax H3, which leads on open weights today. Congratulations to @fal on the release! See below for comparisons between MiniMax H3 Max and other leading models in the Artificial Analysis Video Arena 🧵

    848754029191K viewsView on X
  • Jul 14, 20262.0x their median

    Getting a like from the co-founder of OpenAI means the world to me. Thank you @gdb I pour my entire life into my research and making it available to you all. ❤️ https://t.co/KxW3W4JHdv

    35146160025K viewsView on X
  • Aug 22, 2026

    One thing about agentic AI feels way bigger than another AI model getting slightly smarter: We're moving from AI that answers to AI that acts. You used to open ChatGPT, ask a question, get an answer, and then do the actual work yourself. Now you can give an agent a goal: “Find potential customers for my business.” And it can research companies, browse websites, find the right people, organize the data, write personalized messages, and keep going until the task is done. That's a completely different relationship with software. We're not just using AI as a better search box anymore. We're starting to delegate work to it. And honestly, I think the biggest opportunity won't be the people who use AI to save 10 minutes. It'll be the people who figure out which entire workflows they can hand over to AI. That's when this gets really interesting.

    279784114K viewsView on X
  • Sep 4, 2026

    The difference between GPT-6 Astra and Fable 5.1 is obvious here. Same prompt, both building a website with real-time fluid physics. Move the cursor and the water reacts, waves spread, run into each other, and slowly flatten out. Built end to end on Higgsfield Supercomputer. https://t.co/5yFM9Wzw94

    2782222845K viewsView on X
  • Aug 23, 2026

    The image generation leaderboard is getting seriously competitive. GPT Image 2 is sitting at #1 with a 1369 Elo, but the gap is actually pretty small Reve 2.1 and Nano Banana 2 are right behind at 1322 and 1320. What’s interesting is how crowded the top has become. Google, OpenAI, and newer models are all fighting within a pretty tight range. Image generation is no longer just about making a decent picture. The real competition now is who can consistently nail quality, text, composition and details. This space is moving FAST.

    2092381019K viewsView on X
  • Aug 26, 2026

    AI is entering a weird phase. A year ago, the big question was: “Which AI model is smarter?” Now the more interesting question is: “Which AI can actually get the job done?” We’re moving from models that answer questions to agents that can research, browse, write code, use tools, make decisions and keep working without someone guiding every step. That changes the game. Because if AI can handle an entire workflow instead of just helping with one task, we're no longer talking about a better chatbot. We're talking about software that can actually work for you. And honestly, I think we're still very early.

    1963074020K viewsView on X
  • Aug 28, 2026

    AI is entering a dangerous phase. Not because it's becoming too intelligent. Because humans are getting too comfortable being less intelligent. We used to Google things and read. Now we ask AI. We used to write emails. Now AI writes them. We used to solve coding problems. Now AI generates the solution. We used to think through ideas. Now we ask, “Give me 10 ideas.” And honestly, I get it. AI saves an insane amount of time. But there’s a weird trade-off happening. The more AI does for us, the less often we practice doing things ourselves. The next era of AI won't just be about smarter models. It will be about figuring out how to use AI as a superpower... without outsourcing our ability to think.

    1972176022K viewsView on X
  • Aug 25, 2026

    2016 AI: “Look, it can recognize a cat.” 2026 AI: “Give me a goal.” Then it can research, write code, analyze data, create images, use tools, browse the internet, and actually get parts of the job done. That's the part people underestimate. We didn't just make AI better at answering questions. We made it increasingly capable of doing things. And the next decade might be less about asking: “How smart can AI become?” and more about: “How much of our work are we willing to let it handle?”

    1882770127K 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 277 interactions against 245K followers, an engagement rate of 0.113%. Measured over 22 original posts, its engagement rate beats 64% 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 23K times each, and 1.23% of those impressions turn into an interaction. That is about 9.22% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.5 posts a day over the last 30 days, with activity on roughly 70% of days. Most posts go out around 19:00 UTC, and Tuesday is the busiest day of the week. Of the 22 posts sampled, 59% carry an image or video. The account's strongest tracked post pulled 3.0K interactions, about 11x its own typical post.

What is Sally Stockholm's engagement rate on X?
Sally Stockholm (@aiwithsally) has an engagement rate of 0.113%, based on the median interactions across 22 original posts from the last 30 days against 245,184 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.113%, Sally Stockholm sits above the 50th percentile of the 65,980 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 @aiwithsally have real engagement?
Its engagement rate beats 64% 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 @aiwithsally post?
Most posts go out around 19:00 UTC, and Tuesday is its busiest day, at roughly 1.53 posts per day across the measured window.

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