Thomas Power engagement report
@thomaspower - 271K followers on X
Measured over 4 original posts from a 30-day window, last computed on October 27, 2026.
Engagement
Early reading. We have captured 4 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 342 interactions against 271K followers, an engagement rate of 0.126%. Posts are seen about 312K times each, and 0.11% of those impressions turn into an interaction. That is about 115.1% 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, though only 10% of days saw any activity at all. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 4 posts sampled, 75% link out. The account's strongest tracked post pulled 9.2K interactions, about 4.8x its own typical post. Only 4 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 4 original posts from a 30-day window, last computed on October 27, 2026.
Where this sits in the catalog
At 0.126%, Thomas Power sits above the 25th percentile of the 217,857 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.149%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.149% |
| 75th percentile | 0.705% |
| 90th percentile | 2.63% |
| 99th percentile | 82.6% |
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 13:00 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 0% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 75% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 0% 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.
- 75% 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 865 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
- Jul 18, 20264.8x their median
日本の富が本国に帰ってくる。 手段を選ばず。 日本銀行はそう決めた。
- Oct 29, 201516x their median
Twitter is not a task it's a documented story of your life so others can consider your point of view ...and choose whether to engage or not
- Aug 2, 202616x their median
I did my homework. When Elon and Tesla give me the thumbs up, I’m going all in to own my own fleet of Tesla Robotaxis. Owning your own Tesla Robotaxi fleet could become one of the most powerful cash flow generating assets ever available to everyday investors. A $30,000 Cybercab could generate roughly $58,500 in annual revenue and around $19,800 in net income after Tesla’s fee and operating expenses. At that rate, a fleet of 50 vehicles could produce approximately $1 million in annual net income, requiring about $1.5 million in vehicle capital. To generate the same income from Bay Area rentals, you would need around 50 homes with a combined value of roughly $75 million, and leveraged cash flow could still be negative fyi. That is the power of autonomy… one vehicle can operate for most of the day, serve thousands of customers, relocate to stronger markets, and scale without needing tenants, mortgages, or decades of appreciation. However, the trade-off is risk. Private-owner access is not broadly available yet, and the final economics will depend on utilization, regulation, insurance, operating costs, and Tesla’s Network fee. But if Tesla delivers the technology and opens the Robotaxi network to owners, Robotaxi fleets could become one of the most capital-efficient ways to generate serious cash flow. I’m going to prove this to the world on 𝕏.
- Oct 26, 202613x their median
My predictions over the following months: 1. Stock market will get hurt bad when the music stops on data centers, models, and chips. Too much froth, too high of investment, too many companies will fail. The switching costs are low. I don't know how these companies will become profitable. Its a mega bubble. The rest of the economy is already in a deep recession. Real pain will set in when the public markets dive. 2. Power is the bottleneck. AI is burning an absurd amount of power. The cost of electricity is skyrocketing which is making the cost of everyday life more expensive and hurting quality of life. I'm against data centers because of the power, not the water. The grid is extremely fragile and the weakness will be exposed in the coming months. 3. Subsidies are skewing the market. AI isn't cheap. The prices to use it are artificially low because of subsidies all the way up the chain. You pay $20 or $200 a month but the true costs are 10x That spread is venture capital money being incinerated at scale. When they raise the price, the users will disappear and investors will hold the bag. 3. A big security breach is coming. A bank, a certain model, something is going to rock our world. People are letting bots log in to their banks, their email and everything else. Big trouble coming. 4. Grokbot is exceptional. Its the first model that is adding significant value to my everyday life. I don't know why anybody would use a different personal assistant. 5. AI is insanely high maintenance Billions are being poured into training the next model. They day it comes out its already behind. China has cheaper electricity and more chips. The chips they bought will be obsolete in 18 months. Companies are stuck paying big money every month to maintain and update all of their AI tools. Its a mess. 6. The power companies will renege on their deals. Political pressure will unwind all the unsustainable power deals these data centers and LLMs have negotiated. Power costs will explode. Then comes the choice: Do we jack up costs for our AI / compute and watch everybody switch to the next model or do we incinerate more VC capital? Nobody wins. 7. Credit will be the first domino to fall. Data centers are already struggling to finance the GPUs over 10 years when they will be obsolete in 18 months. We'll end up with a shit load of half built data centers who can't negotiate power rates or buy chips because nobody will let them borrow money. The money will get cold feet as soon as the markets tank and the show will be over. 8. It'll be a dark, dark period in economic markets. The people who own assets that make real money (real estate or businesses) will win. The people who plan ahead and avoid massive leverage will win. The people with cash on their balance sheet will accumulate more assets and generate exceptional wealth. -- Don't listen to me. I'm just a bear. Not investment advice. Good luck!
- Sep 21, 202611x their median
I think Silicon Valley is making a fundamental mistake with personal agents… optimizing entirely for the outcome and forgetting that, for a lot of things, the process is a very core part of experience. Travel is the obvious example. People will almost always never want “book me a trip.” They want to browse, compare, daydream, change their mind, send options to friends, and eventually book. And the average person probably has far fewer recurring tasks worth delegating than the AI industry seems to think. That’s why personal agents feel more like a feature that gets absorbed into existing products than a standalone category.
- Sep 6, 20267.3x their median
There is an employment recession in the US Information sector. The Information industry shed -23,000 jobs in August, bringing employment down to 2.75 million, its lowest since the 2020 pandemic. The Information sector includes software publishing, data processing and computing infrastructure, web search, telecom, broadcasting, publishing, and other information services. Excluding 2020, this is the lowest reading since April 2015. Since the November 2022 peak, Information employment has contracted -270,000, or -12%. By comparison, during the 2008 Financial Crisis and its aftermath, employment in this industry also fell -12%, or -350,000 jobs. AI is increasingly replacing skilled human labor across parts of the Information sector.
- Sep 6, 20265.6x their median
Built an insane model of the human cell in just 30 minutes 🤯 GPT-6 Astra is ridiculously powerful. Can’t wait to put it to the test on biological tasks. @RimShayakhmetov @DeryaTR_ take a look! https://t.co/J9BrKuq8Wr
- Jun 16, 20264.6x their median
https://t.co/zujwYXVfAU
- Aug 19, 20261.8x their median
https://t.co/PwUcHdewJJ
- Oct 26, 2026
https://t.co/PXdDCMUA8c
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 342 interactions against 271K followers, an engagement rate of 0.126%. Posts are seen about 312K times each, and 0.11% of those impressions turn into an interaction. That is about 115.1% 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, though only 10% of days saw any activity at all. Most posts go out around 13:00 UTC, and Monday is the busiest day of the week. Of the 4 posts sampled, 75% link out. The account's strongest tracked post pulled 9.2K interactions, about 4.8x its own typical post. Only 4 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 Thomas Power's engagement rate on X?
- Thomas Power (@thomaspower) has an engagement rate of 0.126%, based on the median interactions across 4 original posts from the last 30 days against 270,783 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.126%, Thomas Power sits above the 25th percentile of the 217,857 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 @thomaspower have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @thomaspower post?
- Most posts go out around 13:00 UTC, and Monday is its busiest day, at roughly 1.53 posts per day across the measured window.