a16z engagement report
@a16z - 1.1M followers on X
Measured over 29 original posts from a 30-day window, last computed on September 1, 2026.
Engagement
A typical post picks up 342 interactions against 1.1M followers, an engagement rate of 0.032%. Measured over 29 original posts, its engagement rate beats 53% 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 86K times each, and 0.398% of those impressions turn into an interaction. That is about 8.06% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.3 posts a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 14:00 UTC, and Wednesday is the busiest day of the week. Of the 29 posts sampled, 72% carry an image or video and 59% link out. The account's strongest tracked post pulled 3.4K interactions, about 9.9x its own typical post.
Measured over 29 original posts from a 30-day window, last computed on September 1, 2026.
Compared with accounts its own size
a16z's engagement rate beats 53% of the tracked X accounts closest to it in follower count (3,774 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 28% 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 0.032%, a16z sits above the 25th percentile of the 36,521 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 | 0.434% |
| 90th percentile | 2.10% |
| 99th percentile | 160.7% |
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 14:00 UTC, and Wednesday 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% | 50K |
| 01:00 UTC | -2% | 51K |
| 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% | 60K |
| 09:00 UTC | -3% | 69K |
| 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% | 100K |
| 16:00 UTC | -3% | 97K |
| 17:00 UTC | -2% | 90K |
| 18:00 UTC | -1% | 84K |
| 19:00 UTC | -2% | 79K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -2% | 57K |
| 23:00 UTC | -2% | 51K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 230K |
| Monday | 0% | 286K |
| Tuesday | -2% | 276K |
| Wednesday | -1% | 251K |
| Thursday | -1% | 244K |
| Friday | -3% | 252K |
| Saturday | +3% | 227K |
Best tweets
- Aug 23, 20269.9x their median
AI power users are showing up outside tech. The fastest-growing Codex adopters since February: Legal: 108x Sales: 41x Recruiting: 41x Marketing: 26x Healthcare: 24x Charts of the Week: https://t.co/7YT2BXvuUu https://t.co/U4TloyrAw3
- Aug 28, 20268.0x their median
$1.1B for the Machine Age. https://t.co/q2myAcojQ5
- Aug 24, 20265.7x their median
.@bhorowitz on why he refused the Databricks founders' $200K ask and wrote them a $10M check instead: "So there were six PhD students, and Ion Stoica, who was their professor." "What they had was this thing called Spark, and the competitor was something called Hadoop. Hadoop had very well-funded companies already running towards it, and Spark was open-source. So the clock was ticking. I think they didn't quite know what they had." "Professors in general, it's a pretty big win if you start a company and you make $50 million. You're a hero on campus... So I'm always a little nervous about a company that comes out of academia thinking too small." "So I said 'I'm not gonna write you a check for $200,000. I'll write you a check for $10 million.'" "You need to build a company. You need to really go for it if you're gonna do this, otherwise you guys should stay in school." Ben Horowitz w/ @lennysan on Lenny's Podcast (2025)
- Aug 28, 20264.6x their median
https://t.co/rohq8Li7GK
- Aug 17, 20264.6x their median
Curiosity compounds https://t.co/aFvreVHBb8
- Aug 26, 20264.0x their median
Airbnb HQ, San Francisco, 2008 https://t.co/iKya2ZYRJN
- Aug 21, 20263.3x their median
It's time to build mega data centers. In counties where they're already operational, the picture is uniformly better since 2024: - More housing - Higher home values - Less unemployment - More job growth Charts of the Week: https://t.co/7YT2BXvuUu https://t.co/ocqduQCtLj
- Aug 19, 20263.1x their median
Been a good week
- Aug 31, 20262.1x their median
Gavin Baker and a16z's David George on the state of the AI boom: The future doesn't have to be winner-take-all. Labs, open-source, applications, and the clouds can all capture value. Demand for intelligence is still dramatically underestimated. Today's power users number in the millions and will grow to hundreds of millions. Gavin and David argue a compute shortage is a more real risk than an AI bubble, and building through it is an opportunity to reindustrialize America. In this episode, they get into why compute investments pay back so fast, what the data center backlash gets wrong, the case for putting compute in orbit, why enterprises will run several models at once, and how Nvidia ended up at the center of the entire supply chain. 00:00 Intro 01:06 The bear case Gavin couldn't find 05:50 Why a lab would cut its own revenue 75% 08:05 What LPs get wrong about a crash 10:50 Microsoft slowed its capex and regrets it 14:33 The engineers spending 100x the median 17:35 Why 23-year-olds use AI better than Gavin 21:45 How much copper 500M AI users need 23:00 Stop promising to cure cancer 26:00 America's richest county is full of data centers 30:48 Who gets priced out of compute 33:05 The age of Elon and Jensen 34:25 Orbital data centers 44:40 Asteroid mining 48:12 Why Microsoft doesn't need a frontier model 54:02 Who becomes the abstraction layer 55:40 Everyone wanted a deity, Cursor wanted a product 1:00:25 Never take shots at Jensen 1:07:40 What happens when the chip doesn't work 1:12:10 What chip deals reveal about customer demand YouTube: https://t.co/2mokoHwtDa @GavinSBaker @DavidGeorge83
- Aug 20, 20262.0x their median
https://t.co/0JwKo5sa8y
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 1.1M followers, an engagement rate of 0.032%. Measured over 29 original posts, its engagement rate beats 53% 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 86K times each, and 0.398% of those impressions turn into an interaction. That is about 8.06% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3.3 posts a day over the last 30 days, with activity on roughly 53% of days. Most posts go out around 14:00 UTC, and Wednesday is the busiest day of the week. Of the 29 posts sampled, 72% carry an image or video and 59% link out. The account's strongest tracked post pulled 3.4K interactions, about 9.9x its own typical post.
- What is a16z's engagement rate on X?
- a16z (@a16z) has an engagement rate of 0.032%, based on the median interactions across 29 original posts from the last 30 days against 1,067,174 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.032%, a16z sits above the 25th percentile of the 36,521 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 @a16z have real engagement?
- Its engagement rate beats 53% 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 @a16z post?
- Most posts go out around 14:00 UTC, and Wednesday is its busiest day, at roughly 3.3 posts per day across the measured window.