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Addy Osmani engagement report

@addyosmani - 409K followers on X

Measured over 16 original posts from a 30-day window, last computed on August 31, 2026.

Engagement

Middle of its size range
Per follower
0.104%
of 409K followers
Per impression
0.143%
298K views on a typical post
Reach
72.9%
of its followers see a post
Typical post
426
interactions (median)
Saved
0.095%
284 bookmarks on a typical post
Posting rate
1.3/day
active 57% of days
Peak time
06:00 UTC
Tuesday

A typical post picks up 426 interactions against 409K followers, an engagement rate of 0.104%. Measured over 16 original posts, its engagement rate beats 55% of 3,739 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 298K times each, and 0.143% of those impressions turn into an interaction. That is about 72.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.3 post a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 06:00 UTC, and Tuesday is the busiest day of the week. Of the 16 posts sampled, 56% carry an image or video and 69% link out. The account's strongest tracked post pulled 14K interactions, about 33x its own typical post.

Measured over 16 original posts from a 30-day window, last computed on August 31, 2026.

Compared with accounts its own size

Addy Osmani's engagement rate beats 55% of the tracked X accounts closest to it in follower count (3,739 accounts, accounts of similar size (decile 6 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 8% 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 0.104%, Addy Osmani sits above the 50th percentile of the 36,134 accounts in this comparison. That places it in the above the median band, which runs 0.08% to 0.431%.

p100.002%
p250.012%
p50 (median)0.08%
p750.431%
p902.11%
p99161.6%
Engagement rate as a share of followers, across the 36,134 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 107,713 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 percentile0.012%
50th percentile0.08%
75th percentile0.431%
90th percentile2.11%
99th percentile161.6%

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 06:00 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: 06:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 06:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%50K
01:00 UTC-2%51K
02:00 UTC-4%49K
03:00 UTC-4%53K
04:00 UTC-6%42K
05:00 UTC-4%41K
06:00 UTC-4%47K
07:00 UTC-5%51K
08:00 UTC-4%60K
09:00 UTC-3%68K
10:00 UTC-2%71K
11:00 UTC-3%77K
12:00 UTC-2%85K
13:00 UTC-2%93K
14:00 UTC-3%96K
15:00 UTC-2%99K
16:00 UTC-3%96K
17:00 UTC-2%89K
18:00 UTC-2%83K
19:00 UTC-2%79K
20:00 UTC-1%73K
21:00 UTC-1%65K
22:00 UTC-1%57K
23:00 UTC-2%51K
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 5%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%228K
Monday0%281K
Tuesday-2%270K
Wednesday-1%249K
Thursday-2%242K
Friday-3%250K
Saturday+3%225K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Aug 9, 202633x their median

    For anyone with endless ideas, this agent age is nirvana as those ideas are met with endless execution, endless exploration. I've never had has much fun working with computers as I do right now. What a time to be alive.

    12K1.2K522257540K viewsView on X
  • Aug 22, 202615x their median

    “Look at my incredible new factory!” Yo that’s cool, what do you make? “It’s highly optimised, fully automated, zero tolerance for defects and with a continuous feedback cycle” Cool cool, so what do you actually make? “I can interact with it on my phone, laptop, messenger, completely async, and the shared context means it’s always learning how to get better” Very impressive, but what do you make? “Every agent has full context, can spawn other agents, review their work, fix defects, and ship continuously.” yes yes. WHAT DOES IT MAKE? “Software.” Oh nice. What software? “Well right now we’re mostly using it to improve the factory.” Improve it to make what? “Anything!” Such as? “…a better factory.”

    5.9K331155100911K viewsView on X
  • Aug 25, 202613x their median

    Just FYI. If you are switching models in a session all the time - you are doing it wrong. Every time you switch, your entire prompt cache is invalidated on the new model you switch to, and you have to repay the full input tokens price for all of it. Stop doing this unless those models are free. This is not a hermes thing - this is a fundamentals of inference thing.

    4.9K31333098400K viewsView on X
  • Dec 24, 20239.5x their median

    "First do it, then do it right, then do it better." Just start. The journey to success often begins with a single step, but that first step can be the hardest to take. It's easy to get caught up in the fear of failure or the desire for perfection, but I hope this quote I first shared in 2013 can be a reminder of the importance of simply getting started as we go into 2024. Just Start Somewhere "Start slow if you have to. Start small if you have to. Start privately if you have to. Just start." - James Clear Taking that first step doesn't require perfection or immediate mastery. The key is to overcome inertia and take action, as this action will lead to progress, learning, and (if you’re lucky and consistent) ultimately success. When you start, you allow yourself the opportunity to grow, adapt, and move forward. The Power of Starting Beginning a new project or habit often feels daunting. According to psychologists, we tend to overestimate the pain of starting and underestimate our ability to persist. However, studies show that "small starts" predict eventual success better than initial enthusiasm or early progress. This phenomenon is known as the fresh start effect - taking the first step energizes us and bolsters motivation. So focus on starting without putting pressure on perfection. Progress and course corrections will follow. First, Do It: Embrace the MVP Mindset Doing it = get the simplest MVP out. A Minimum Viable Product (MVP) represents the simplest version of a product or idea that allows you to test, gather feedback, and iterate. By embracing this mindset (just get something done - it's OK if rough, a prototype, a draft), you focus on progress over perfection, understanding that getting something out into the world is far more valuable than waiting for the perfect moment. Expand Your Comfort Zone Venturing outside one's comfort zone can elicit fears of failure. Leaning into discomfort not only builds confidence and skills, but research shows it makes us more receptive to learning. Recognize that fear is often the mind's way of urging us to grow. Don't let it stop you from progressing. Then, Do It Right: Refine and Correct Doing it right = fix correctness issues. Once you've taken that first step and put your MVP out into the world, it's time to refine and correct. This stage is about learning from feedback, identifying areas of improvement, and making adjustments accordingly. It's a chance to iterate on your idea, ensuring that it meets the needs of your audience or customers while aligning with your vision. Cultivate Curiosity and Resilience Meeting new challenges with curiosity and resilience makes venturing outside our comfort zone more sustainable and enjoyable. Cultivate curiosity about growth opportunities and your capacity to rise to them. Set mini-challenges to incrementally expand your horizons. When facing inevitable setbacks, avoid self-criticism and tap into resilience - the ability to recover, learn and continue progressing. Self-compassion, adaptability and maintaining perspective are key here. With consistent effort, you build confidence in your ability to start, stumble, learn and work toward mastery. Finally, Do It Better: Strive for Continuous Improvement "Doing it better = iterate towards an ideal end-state (e.g., make it fast)." The journey doesn't end with merely doing it right. The final step is to continuously improve, striving for excellence and growth. By iterating towards an ideal end-state, you demonstrate a commitment to progress, ensuring that your product, idea, or project remains relevant, innovative, and successful. Set New Goalposts As you improve, have a clear idea of when you are “done” or update your goalposts. Elite athletes turn small gains into competitive edges via the aggregation of marginal gains. Identify areas of potential improvement and set measurable stretch goals, from increasing efficiency to enhancing user delight. Overcoming the Greatest Barrier to Progress "The greatest barrier to progress is not lack of resources or talent, but fear of failure." Recognizing that fear of failure is the most significant obstacle in the pursuit of success allows you to confront it head-on. By acknowledging this fear, you can focus on taking that first step, knowing that once the ball starts rolling, it becomes much easier to keep it in motion. Remember that starting is more than half the battle. Don't wait until you feel ready, because the perfect moment may never come. The Bottom Line Rather than striving for perfect execution, embrace the power of starting - put forth an MVP, soft launch an initiative, or set a milestone. Progress begets motivation. By simply starting, you open the door to growth and innovation. The rest will follow. Embrace the power of starting and then iterating until you're happy.

    3.2K65813051548K viewsView on X
  • Jul 7, 20265.2x their median

    "When intelligence is plentiful, volition is valuable. The people who are going to make a difference are not the ones who seek relaxation and passively use AI to work less. They are the ones who will seek improvement and actively wrestle with AI to develop their own mental capabilities and accomplish more." https://t.co/gDEy4aABwo

    1.9K2298234334K viewsView on X
  • Jul 8, 20264.3x their median

    https://t.co/YOd4ptcTeD

    1.5K19470381.3M viewsView on X
  • Jul 30, 20263.6x their median

    Software quality now depends on the constraints you set around your agents. When humans manually wrote most of the code we could look at the code itself for signs of quality. Is it clean? Is it thoughtful? Is it fast? Can another engineer understand it? Does it have tests? Agents can now generate more code than people can read. When code generation scales beyond review, quality - checks for one or more of correctness, maintainability, security, performance etc - increasingly has to live somewhere else. It moves into the harness, environment and operating system around the agent. This can be the tests and deterministic checks that decide what the system is allowed to do (amongst others). Your constraints are what may eventually enable loops of agents to deliver production software reliably. They can include unit tests, property tests, acceptance tests, mutation testing and quality metrics. This back-pressure lets the system resist bad work before it becomes somebody elses problem. Set your constraints. They decide whether the code your agents generate is good enough to ship.

    1.3K1589021466K viewsView on X
  • Aug 12, 20262.9x their median

    https://t.co/Gkd5qvcrAk

    1.1K1303621421K viewsView on X
  • Jul 21, 20262.1x their median

    https://t.co/4INzNxFRZn

    7477428351.6M viewsView on X
  • Aug 18, 2026

    If you're building a software factory, code good enough to ship still needs human taste and ownership. You'll likely need humans in the loop upfront for deciding on product intent, system design (if you care) and your quality bar. Do review code (lights-on factory) but be intentional with where it's needed the most. I've found you want to watch out for where automated back-pressure breaks. Or where maintainability trade-offs need to be made. Aim for quality checks to happen as early and continuously as possible. Not all of them have to, but this includes type systems, automated tests, mutation testing, security scanners and linting for architecture rules. Number of checks != quality. You'll likely need to experiment with what checks give you the best signal to noise ratio. Be ready to tighten or relax your constraints deliberately. You want to build your factory so some aspects of human taste get encoded in the environment, the agent gives you evidence of its work being right and where a human still "owns" what ships to production.

    48749372295K 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 426 interactions against 409K followers, an engagement rate of 0.104%. Measured over 16 original posts, its engagement rate beats 55% of 3,739 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 298K times each, and 0.143% of those impressions turn into an interaction. That is about 72.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.3 post a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 06:00 UTC, and Tuesday is the busiest day of the week. Of the 16 posts sampled, 56% carry an image or video and 69% link out. The account's strongest tracked post pulled 14K interactions, about 33x its own typical post.

What is Addy Osmani's engagement rate on X?
Addy Osmani (@addyosmani) has an engagement rate of 0.104%, based on the median interactions across 16 original posts from the last 30 days against 409,413 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.104%, Addy Osmani sits above the 50th percentile of the 36,134 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 @addyosmani have real engagement?
Its engagement rate beats 55% of the tracked X accounts closest to it in follower count (3,739 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 @addyosmani post?
Most posts go out around 06:00 UTC, and Tuesday is its busiest day, at roughly 1.3 posts per day across the measured window.

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