Robert Scoble engagement report
@Scobleizer - 603K followers on X
Measured over 20 original posts from a 30-day window, last computed on August 26, 2026.
Engagement
A typical post picks up 176 interactions against 603K followers, an engagement rate of 0.029%. Measured over 20 original posts, its engagement rate beats 50% of 3,774 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 30K times each, and 0.579% of those impressions turn into an interaction. That is about 5.05% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, though only 13% of days saw any activity at all. Most posts go out around 01:00 UTC, and Tuesday is the busiest day of the week. Of the 20 posts sampled, 80% carry an image or video, 15% are part of a thread and 50% link out. The account's strongest tracked post pulled 3.4K interactions, about 19x its own typical post. Recurring topics include #batteries, #medicine, #quantumcomputing.
Measured over 20 original posts from a 30-day window, last computed on August 26, 2026. Recurring tags: #batteries, #medicine, #quantumcomputing.
Compared with accounts its own size
Robert Scoble's engagement rate beats 50% of the tracked X accounts closest to it in follower count (3,774 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 38% 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 0.029%, Robert Scoble sits above the 25th percentile of the 36,654 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.433% |
| 90th percentile | 2.10% |
| 99th percentile | 160.5% |
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 01:00 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 51K |
| 01:00 UTC | -2% | 52K |
| 02:00 UTC | -3% | 50K |
| 03:00 UTC | -4% | 53K |
| 04:00 UTC | -6% | 43K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 48K |
| 07:00 UTC | -5% | 52K |
| 08:00 UTC | -4% | 61K |
| 09:00 UTC | -3% | 70K |
| 10:00 UTC | -2% | 72K |
| 11:00 UTC | -3% | 78K |
| 12:00 UTC | -2% | 86K |
| 13:00 UTC | -2% | 94K |
| 14:00 UTC | -4% | 97K |
| 15:00 UTC | -2% | 101K |
| 16:00 UTC | -3% | 98K |
| 17:00 UTC | -2% | 91K |
| 18:00 UTC | -1% | 85K |
| 19:00 UTC | -1% | 80K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -1% | 57K |
| 23:00 UTC | -2% | 52K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 231K |
| Monday | 0% | 288K |
| Tuesday | -2% | 278K |
| Wednesday | -1% | 251K |
| Thursday | -1% | 245K |
| Friday | -3% | 253K |
| Saturday | +3% | 227K |
Best tweets
- Aug 25, 202619x their median
There is a child with a rare disease who is currently suffering and struggling to manage his symptoms. Rare as this is, you can directly help him. Today we are launching the "Rare Disease, Real Kid" Hackathon, and there are $50,000 in prizes from @AnthropicAI and @awscloud. We (@huggingface & @Sagebio) are helping this child open his genome and clinical data to the community, so that we can find what's caused his disease and what currently-approved drugs could help him. I doubt I need to motivate this much further or explain how rare it is for a family to share their child's genome and clinical data, but if you're not sure, consider this: Until very recently, it wasn't feasible for patients like this to get treatment because their disease was so rare that the economics could never justify the investment. Now, as we've seen, people with rare diseases are starting to be able to find the answers themselves (with the help of AI tools, cheaper sequencing, etc). This kid is not able to do that for himself and neither are his parents, so we're asking you for help. Both for this kid and to prove that it's possible for everyone else suffering from a rare disease. More details in 🧵. https://t.co/hjjagALtMu
- Aug 25, 202614x their median
NEW: Apple is gearing up to launch a new version of the Mac mini, as early as ahead of its September iPhone launch. https://t.co/k8Zz9g0SFI
- Aug 25, 20266.7x their median
Get some sleep. Another big breakthrough in robotics in the morning.
- Aug 23, 20265.1x their median
Building an Artificial Mechanical Engineer: All of the "AI CAD" demos you've seen have been essentially the same thing, a frontier lab LLM writing code that is translated by an existing geometry kernel into a 3d B-rep model. I think this approach is fine, but generally lossy, and lacks true spatial understanding and geometric reasoning that humans naturally posses and apply when encoding their designs in a CAD system. So I attempted to do something unique in the generative design space, building off of other generative 3d research, and trained my own (two tiny, 16M Parameter) AI models on a hyper specific set of data. Introducing FieldGeo - a set of models that encode geometry, physics (FEA, Stress) and DFM into the same latent space, and reproduces (assisted with an additional design agent) geometries to meet the stated cases. Today, it's just for L shaped brackets.
- Aug 24, 20262.3x their median
Real-time translation that sounds like you 🚀 We've been building speech-to-speech simultaneous translation for a while. The newest piece is on-the-fly voice cloning: the model picks up your voice as you speak and carries it into the other language. Here's the alpha running live during our all-hands: you speak in Japanese, the room hears you in English, and it still sounds like you. It's early and the edges are rough, but this is the experience we've been building toward. Coming very soon. Demo video below 👇 #VoiceAI #SpeechAI #RealTimeTranslation #VoiceCloning #AI
- Aug 24, 20261.6x their median
Video world models shouldn't just render plausible pixels, they should understand "how the world evolves". 🤔 Introducing Latent Dynamics Reasoning (LDR). Instead of predicting future frames directly, LDR maps past frames into structured latent states, then rolls those states forward through kinematic integration. It learns only the higher-order motion residuals that drive the rollout. 🚀 To our knowledge, LDR is the first video world model to extrapolate learned dynamics beyond its training distribution. 💪 Paper / code / models / data are now public, check them out! 🥳 - Paper: https://t.co/Mnh1sD9jLf - Code: https://t.co/uJhu28darp - Model: https://t.co/1fJLmwFwTL - Data: https://t.co/Pxl0eirIgo
- Aug 25, 2026
How to approach an unknown language in the ocean? Here’s one of the first cases of AI interpretability leading to a scientific discovery -- in whales. We built an artificial baby model that learns language directly from raw sound and trained it to imitate whale speech. Then we looked inside. Our interpretability method recovered the properties biologists already thought were meaningful and pointed out those that had not been considered before. This was the initial clue that eventually led to the discovery of vowels in sperm whales. Understanding AI and reframing language as informative imagitation can help us step outside our human biases and discover new realities about the natural world. Published in Royal Society Open Science.
- Aug 25, 2026
The next decade is going to produce the most impactful hardware companies, ever. So today, we're going all in. Announcing Blueprint 2. A 3 month program focused on enabling and accelerating hardware founders. - 30 teams get $150k/ea - up to 1 year dedicated industrial space in SF - network of founders, investors and alumni - $1M+ in credits - our full team building alongside you Applications are now open: https://t.co/JEHEKubCss
- Aug 25, 2026
Lights, Camera, Traction Introducing Yarn – the video product for agentic GTM teams. The growth teams at Clay and Faire have made 100s of videos with Yarn already. You provide the spark, agents do the rest. It’s Waymo for video production. Our launch video was made entirely in @yarn_so
- Aug 23, 2026
My mom’s 2026 Model X just had every single window shot out in Chattanooga, Tennessee. Sentry was on. All security features were on. Not one single clip of the perpetrator. Police have been called and they’re pulling cameras from surrounding locations. This shouldn’t be possible. @Tesla @elonmusk — what’s going on with Sentry?
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 176 interactions against 603K followers, an engagement rate of 0.029%. Measured over 20 original posts, its engagement rate beats 50% of 3,774 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 30K times each, and 0.579% of those impressions turn into an interaction. That is about 5.05% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.5 posts a day over the last 30 days, though only 13% of days saw any activity at all. Most posts go out around 01:00 UTC, and Tuesday is the busiest day of the week. Of the 20 posts sampled, 80% carry an image or video, 15% are part of a thread and 50% link out. The account's strongest tracked post pulled 3.4K interactions, about 19x its own typical post. Recurring topics include #batteries, #medicine, #quantumcomputing.
- What is Robert Scoble's engagement rate on X?
- Robert Scoble (@Scobleizer) has an engagement rate of 0.029%, based on the median interactions across 20 original posts from the last 30 days against 602,767 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.029%, Robert Scoble sits above the 25th percentile of the 36,654 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 @Scobleizer have real engagement?
- Its engagement rate beats 50% of the tracked X accounts closest to it in follower count (3,774 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 @Scobleizer post?
- Most posts go out around 01:00 UTC, and Tuesday is its busiest day, at roughly 2.5 posts per day across the measured window.