andrew chen engagement report
@andrewchen - 456K followers on X
Measured over 19 original posts from a 30-day window, last computed on September 24, 2026.
Engagement
A typical post picks up 387 interactions against 456K followers, an engagement rate of 0.087%. Measured over 19 original posts, its engagement rate beats 68% of 20,444 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 35K times each, and 1.10% of those impressions turn into an interaction. That is about 7.74% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.7 posts a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 03:00 UTC, and Sunday is the busiest day of the week. Of the 19 posts sampled, 26% carry an image or video, 26% are part of a thread and 5% link out. The account's strongest tracked post pulled 1.7K interactions, about 4.3x its own typical post.
Measured over 19 original posts from a 30-day window, last computed on September 24, 2026.
Compared with accounts its own size
andrew chen's engagement rate beats 68% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 50% 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 0.087%, andrew chen sits above the 25th percentile of the 204,956 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 03:00 UTC, and Sunday 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 | 26% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 5% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 26% 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.
- 5% 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 326 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
- Aug 23, 20264.3x their median
2012: acquire company for users 2021: acquire company for engineers 2026: acquire company for training data
- Sep 1, 20263.8x their median
Before AI: - hardware is hard - teams > solo founders - technical founders only - PhDs build tech in search of a problem - hot SaaS startups get 100x ARR multiples After AI: - hardware is the only thing AI can't build - solo founders are 100x engineers - anyone can build - PhDs building AI infra name their price - SaaSpocalypse Am I missing anything?
- Sep 20, 20263.5x their median
Jev is going to change the prosumer/consumer AI landscape by unlocking a specific thing: Ad-supported + free AI native apps this is going to usher in a generation of new AI-native marketplaces, social networks, photo apps, messaging, calendars, email, collab tools, and much more. Why? Previously, if you wanted to have an AI-native app with multiple/fast LLM calls on every screen, the math just didn’t work - inference costs just couldn’t be paid back from throwing a few video ads or affiliate links. So there were really just two solutions: 1) be a massive company and subsidize AI costs 2) charge a subscription fee to cover inference (or both) So what happens when you take a different approach that’s looks to be, initially, >400x cheaper than a more general LLM? I think it means that app developers are going to make their apps smarter and different in interesting ways. It won’t be as generically powerful as LLMs, but instead folks will create highly differentiated point solutions. You may not have a generically powerful virtual admin to schedule all your meetings, but you may have a free/ad-powered assistant that can comb through your inbox, filter for only important emails, figure out important dates, prioritize contacts, and do other interesting 80/20 work. Same for generically powerful virtual companions, or app builders, etc - it may be that we can hybridize the LLM and future Jev-like models that adds “wow” features at 1/1000ths of the cost, to make the economics work. If folks hear of interesting new apps/interactions/etc built on Jev, I’d love to hear it!
- Aug 1, 20262.8x their median
Unlimited mathematical proofs but limited skilled mathematicians who can verify them Unlimited code but limited skilled programmers to review them Unlimited videos but limited attention to watch them Unlimited lawsuits but limited courts/judges/lawyers to adjudicate them When the creation of something goes to zero, the cost moves elsewhere…
- Aug 30, 20262.4x their median
15M npm downloads / week 🚀 https://t.co/X4Tcos6YGR
- Aug 10, 20261.6x their median
COMING SOON - a new a16z office launching in SF Want to guess the meeting room naming scheme? https://t.co/A8i5LbjCsh
- Sep 24, 20261.6x their median
Epic https://t.co/wOIVIamS4m
- Aug 24, 2026
it’s live! we’re flying 20 top builders from around the world to San Francisco for Tech Week Oct 5-11th Applications for the Global Founder Sprint by @speedrun are now live What? - up to $3K to cover travel costs to SF (by @Airwallex) - small dinner with a16z investors - invites to VIP a16z events @Techweek_ - access to executive buyers & customers at our AI Faire - US sales coaching Who? - very early global builders just thinking about starting >>> Apply below! App open for 7 days <<< https://t.co/MFAAZDoK4w
- Sep 4, 2026
i'd pay 2x for an iPhone where siri/dication/other AI features actually were good
- Jul 31, 2026
Run DeepSeek v4 Flash GA (0731) on 2x @NVIDIAAI DGX Sparks with easy ✨ 82 tok/s single stream, peak ~95 tok/s 135 tok/s at 3 sessions Uses the official FP8 weights. Special thanks to @0xSero for a PR on this. Further improvements to the recipe are planned! Get it here: https://t.co/6HXa9pxqhj
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 387 interactions against 456K followers, an engagement rate of 0.087%. Measured over 19 original posts, its engagement rate beats 68% of 20,444 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 35K times each, and 1.10% of those impressions turn into an interaction. That is about 7.74% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.7 posts a day over the last 30 days, with activity on roughly 73% of days. Most posts go out around 03:00 UTC, and Sunday is the busiest day of the week. Of the 19 posts sampled, 26% carry an image or video, 26% are part of a thread and 5% link out. The account's strongest tracked post pulled 1.7K interactions, about 4.3x its own typical post.
- What is andrew chen's engagement rate on X?
- andrew chen (@andrewchen) has an engagement rate of 0.087%, based on the median interactions across 19 original posts from the last 30 days against 456,317 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.087%, andrew chen sits above the 25th percentile of the 204,956 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 @andrewchen have real engagement?
- Its engagement rate beats 68% of the tracked X accounts closest to it in follower count (20,444 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 @andrewchen post?
- Most posts go out around 03:00 UTC, and Sunday is its busiest day, at roughly 1.7 posts per day across the measured window.