Mitchell Hashimoto engagement report
@mitchellh - 237K followers on X
Measured over 13 original posts from a 30-day window, last computed on October 1, 2026.
Engagement
A typical post picks up 1.6K interactions against 237K followers, an engagement rate of 0.698%. Measured over 13 original posts, its engagement rate beats 89% of 21,185 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 215K times each, and 0.751% of those impressions turn into an interaction. That is about 90.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.6 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 19:00 UTC, and Friday is the busiest day of the week. Of the 13 posts sampled, 77% carry an image or video and 8% link out. The account's strongest tracked post pulled 14K interactions, about 8.4x its own typical post.
Measured over 13 original posts from a 30-day window, last computed on October 1, 2026.
Compared with accounts its own size
Mitchell Hashimoto's engagement rate beats 89% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 9 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 35% 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 0.698%, Mitchell Hashimoto sits above the 75th percentile of the 212,656 accounts in this comparison. That places it in the top 25% band, which runs 0.697% to 2.61%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.697% |
| 90th percentile | 2.61% |
| 99th percentile | 82.9% |
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 Friday 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 | 77% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 8% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 77% 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.
- 8% 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 599 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 11, 20268.4x their median
I can’t stress enough how little an idea matters compared to the agency of the people executing the idea. I have had the privilege of knowing and sometimes even working with some of the most successful people (by various metrics). The difference between mediocre and excellent work and outcomes is predominantly one of agency. In practice this means: they dont wait for things to happen to them they go out and make things happen for them. They don’t wait for someone else to do something, for someone to teach them, for someone to give them the path, etc. They just go out and find a way to do it. I think the single biggest superpower these people have is the realization/belief that the world around them is completely mutable. Most everything that happens is because a person made it happen. I used to tell people to look around the room you’re sitting in. Look at everything. Every noun. It almost all exists because a person willed it into existence. Nothing is stopping you from doing the same. I see people online all the time dismissing someone else’s success because “I had that idea first” or whatever. I mean… yeah? If so then the difference is… you. So a bit of a self own whenever I hear that. Number one tip: act with agency.
- Sep 2, 20264.4x their median
Beware people obsessed with outcomes instead of building outcome machines. Its worse than ever with AI, but these people existed before. Short term results above all else, etc. Don't fall into the trap. Invest in building strong fundamentals, invisible supports, and outcomes flow like water. An outcome machine.
- Jul 20, 20263.0x their median
Testing some UI. Not Ghostty btw (but, libghostty). Not ready to talk more yet, but sharing things I'm excited about. Plenty more details soon. https://t.co/Ag7kOMGLQL
- Sep 11, 20262.8x their median
I've never had a case on any iPhone, I've never cracked a screen or broken the phone. People used to say "oh wait until you have kids." Well, I have a couple now, and one is 3. No problems, clearly a skill issue. No cases for me, using the device as it was intended by design.
- Aug 13, 20262.6x their median
I'm so incredibly tired of seeing low-effort AI-designed web pages. I basically bounce off any new product immediately when I see it (never get a chance to judge the product itself). Lots of thin lines, glowy styles, inconsistent fonts, lots of monospace. You know who you are.
- Jul 14, 20262.5x their median
A ChatGPT automation just found ~$45K in erroneous invoices across 3 years of billing history that I've confirmed and already had resolved. My lifetime history for ChatGPT is ~$1,800, so it just paid for itself 25x over. I setup an automation with read-only access to my email, and tasked this one specifically with analyzing construction invoices. It has access to prior construction invoices, emails, meeting notes, etc. It produces a report and emails it to me (the only email its allowed to send, enforced by API token) whenever I receive a construction invoice. Across 3 years of construction projects, it found about $45K in issues. Some were wrong amounts, some were duplicate invoices, some were invoices addressed to the wrong person. I manually verified, emailed my GCs, and got refunded/credited. I get multiple construction bills each month and each bill is ~50 pages in a PDF of low-quality scanned paper. I do manually review each bill but its pretty hard to be right all the time. I do believe these were genuine mistakes and not done out of ill will just based on what the mistakes were. I don't want to share my full construction costs across the past few years, but $45K is a very small percentage of overall billed amounts. Pretty sweet.
- Aug 11, 20262.5x their median
I live in a nice neighborhood. I will never understand how people that are so well off can be so cheap and mean to household employees. Especially those taking care of your kids and being in your house! Take care of people, folks. One of my neighbors called me a communist in the street because I said I provide healthcare and pay taxes (you know, don’t pay under the table). I took it as a compliment.
- Jul 30, 20262.4x their median
Let's talk a bit about what makes the Superlogical multiplexer different architecturally from traditional terminal multiplexers! There's a lot (a LOT) more coming, but wanted to share a little bit about the terminal-specific part compared to tmux and zellij. https://t.co/lP1gXLQNl2
- Aug 21, 20262.4x their median
Ghostty (and libghostty!) now has a 100% complete implementation of the Kitty Graphics Protocol. We support every feature, every option. We are the first terminal beyond Kitty to do this. Most terminals stop at basic image placements, then give up on the long tail of other features. Ghostty covers all of them: - Unicode placeholders (so it works in tmux) - Relative placements (so images can be positioned relative to other images) - Animation - Scroll region handling (so images scroll properly with terminal scroll regions) - All transport mediums: shared memory, temp files, etc. - etc... All of these features don't impact steady-state use (CPU or memory, besides raw code size). And for libghostty consumers, you can use the compile-time features flags to disable them completely. I read the spec myself a hundred times. I read Kitty's source code to validate behaviors (our implementation is markedly different, so no GPL violation). I also utilized agents, primarily for validation. I spun Fable and Sol in a loop for 3 weeks (pausing only when their dedicated subs exhausted limits) with a prompt to find mismatches between the spec, Kitty's reference implementation, and Ghostty. And now we're done. Ghostty is the most compliant Kitty Graphics implementation (ignoring Kitty itself of course). And, this is all in libghostty, so now everyone can be perfectly compliant.
- Sep 24, 20262.2x their median
I’ve been building a new home office (plus other things of course) for 4 years and it’s finally almost complete! Missing lots of details still that’ll take a few more weeks, but truly can’t wait to work out of here every day. The desk and coffee table are completely custom. The desk is a convertible standing desk. The coffee table is actually a convertible desk (you can lift half its top out and it becomes sitting desk height). The sliding glass on the other side fully pockets so I can have a fully open office. It faces west so it gets the ocean breeze. The millwork includes a drawer dishwasher, a full espresso machine, fridge and more. Coffee and tea within easy access. Lots of work and care to make the HVAC, speakers, lights, networking, outlets, etc as hidden as possible or reasonable. From the other side we have a totally outdoor hallway (CA baby) with a sitting area overlooking some trees (cushion still being made so it’s just bare atm). Dream office. Almost complete.
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 1.6K interactions against 237K followers, an engagement rate of 0.698%. Measured over 13 original posts, its engagement rate beats 89% of 21,185 tracked accounts of a similar size. Comparing inside a size band matters here: engagement rate falls as accounts grow, so a raw rate would mostly just re-measure the follower count. Posts are seen about 215K times each, and 0.751% of those impressions turn into an interaction. That is about 90.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.6 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 19:00 UTC, and Friday is the busiest day of the week. Of the 13 posts sampled, 77% carry an image or video and 8% link out. The account's strongest tracked post pulled 14K interactions, about 8.4x its own typical post.
- What is Mitchell Hashimoto's engagement rate on X?
- Mitchell Hashimoto (@mitchellh) has an engagement rate of 0.698%, based on the median interactions across 13 original posts from the last 30 days against 236,837 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.698%, Mitchell Hashimoto sits above the 75th percentile of the 212,656 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 @mitchellh have real engagement?
- Its engagement rate beats 89% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the top quarter for its size 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 @mitchellh post?
- Most posts go out around 19:00 UTC, and Friday is its busiest day, at roughly 0.6 posts per day across the measured window.