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Chamath Palihapitiya engagement report

@chamath - 2.4M followers on X

Measured over 55 original posts from a 30-day window, last computed on August 31, 2026.

Engagement

Middle of its size range
Per follower
0.044%
of 2.4M followers
Per impression
0.294%
361K views on a typical post
Reach
15.1%
of its followers see a post
Typical post
1.1K
interactions (median)
Saved
0.068%
247 bookmarks on a typical post
Posting rate
4.4/day
active 97% of days
Peak time
16:00 UTC
Tuesday

A typical post picks up 1.1K interactions against 2.4M followers, an engagement rate of 0.044%. Measured over 55 original posts, its engagement rate beats 72% of 3,739 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 361K times each, and 0.294% of those impressions turn into an interaction. That is about 15.1% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.4 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 55 posts sampled, 51% carry an image or video and 36% link out. The account's strongest tracked post pulled 48K interactions, about 45x its own typical post.

Measured over 55 original posts from a 30-day window, last computed on August 31, 2026.

Compared with accounts its own size

Chamath Palihapitiya's engagement rate beats 72% of the tracked X accounts closest to it in follower count (3,739 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 27% 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 0.044%, Chamath Palihapitiya sits above the 25th percentile of the 36,378 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.

p100.002%
p250.012%
p50 (median)0.08%
p750.432%
p902.10%
p99161.0%
Engagement rate as a share of followers, across the 36,378 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 107,364 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.08%
75th percentile0.432%
90th percentile2.10%
99th percentile161.0%

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 16:00 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.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 16:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 16:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
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
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%230K
Monday0%286K
Tuesday-2%276K
Wednesday-1%251K
Thursday-1%244K
Friday-3%252K
Saturday+3%227K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Aug 17, 202645x their median

    In 2001 George W Bush proposed a partial privatization plan for Social Security so you could put 10% of your SS contribution into the markets. People rejected this. We can now see that if it had passed, the 10% that went into the markets would have outperformed the 90% the government managed, the program would be solvent, and the average SS recipient would be receiving 2X what they currently receive. The worst bet you’ll ever make is betting on government.

    41K6.0K9715002.9M viewsView on X
  • Aug 14, 202641x their median

    Søren Kierkegaard on the Importance of Walking “Above all, do not lose your desire to walk. Everyday, I walk myself into a state of well-being & walk away from every illness. I have walked myself into my best thoughts, and I know of no thought so burdensome that one cannot walk away from it. But by sitting still, & the more one sits still, the closer one comes to feeling ill. Thus if one just keeps on walking, everything will be all right.”

    37K6.0K3375593.5M viewsView on X
  • Aug 13, 202619x their median

    All other sources of energy combined are utterly insignificant compared to the Sun

    21K2.5K2.0K2086.4M viewsView on X
  • Aug 3, 20269.5x their median

    The AI Singularity The argument goes like this: 1. Humans build an AGI. 2. The AGI becomes good at AI research. 3. It designs a smarter AI. 4. That smarter AI designs an even smarter AI. 5. The cycle repeats faster and faster. Looking at the results and capabilities from the various labs over the past few weeks I would say we are firmly in this loop now. The next 18months will be wild. Recursive self improvement will dramatically increase capability very quickly from here. Marginal costs of all models will go to ~$0.

    8.4K778745225858K viewsView on X
  • Aug 5, 20267.0x their median

    Many of the loser children of my wealthy friends who see no way to emulate the success of their parents, have gravitated toward Mamdani-ism and found community and a sense of purpose by rejecting capitalism as a way to cope with their own failure. Please note they have nor however rejected their trust funds or living subsidies while pursuing their “passions” in NGOs, dabbling in the arts or trying to invest their parents money in “VC”.

    7.9K8774081461.9M viewsView on X
  • Jul 2, 20268.4x their median

    https://t.co/vPrPSUjTJG

    7.4K9303941952.3M viewsView on X
  • Aug 3, 20267.3x their median

    If I were the company on the right I would try to kill every company that is like the one on the left. This way, the company on the right can make trillions of dollars and then infect American politics with hundreds of billions of dollars to implement their vision of being the sole judge, jury and executioner of future progress.

    6.8K517341134636K viewsView on X
  • Aug 1, 20267.0x their median

    Here is my AI investing guide. Sitting here August 2026, my current best thoughts are as follows: 1. LPS (Land Power Shell) is still the most obvious and fastest path to cash on cash returns. Lots of value can be assembled and traded quickly at this layer. And as data centers get more pushback, energized land can explode in value. Very bullish here. I’ve stepped into this layer very aggressively. My partner @anitavlallian and I have acquired almost 6GW coming online in a ramp from today thru 2029 of grid power and behind the meter. 2. Silicon - I helped get @GroqInc off the ground in 2015 and we licensed it to @nvidia for $20B Dec2025. I won’t invest or incubate anything in this layer now. The perf demands of the chips are too high, manufacturing precision is too complex and supply chain influence to get adjacent components like memory isn’t possible for a startup anymore. Lots of capital will be wasted here chasing Groq and Cerebras’ success. Note that both startups made sense a decade ago when these constraints were much more modest. 3. Clouds - Clouds are very very lucrative but very hard to build and very expensive and technically complicated to maintain. And as alignment becomes a more important issue, I expect the clouds will be asked to build robust KYC and attest to it. This makes the risk:reward ratio skewed. I don’t want to be responsible when the USG says a cloud allowed a bad actor to do something bad because of poor KYC. 4. Models are complicated. The big open question is how much of the revenue being generated by them today is because of tokenmaxxing and poor model behavior. If it’s a lot, then the annualized revenues will diminish meaningfully even as token consumption inflects upwards. This is the big economic question at this layer. 5. Harnesses are where the action is and why I started @8090solutions two years ago. In a nutshell, the harness helps enterprises owns their proprietary context (what Alex Karp calls their ‘alpha’). This is an enterprise’s data, workflows, evals, and business rules. A harness that gives this to an enterprise is what creates very low model-agnostic switching costs, which further reinforces my views of #4 above. 6. Applications will be another long term winner along with harnesses. This is where the differentiation between “off the shelf” and “custom time and materials” melts away. Every company, with the right harness, can now imbue their alpha into the software that runs their company. I expect this to mean that “off the shelf” is largely replaced with custom software creating a huge opportunity to write these solutions for companies. Build once and sell repeatedly is a laggard GTM motion for a SaaS world that isn’t needed here. Think custom by design, alpha embedded, proprietary by nature. Fin. Good luck to all the players!

    6.2K671391181918K viewsView on X
  • Aug 5, 20266.9x their median

    Today we're introducing Hark Handoff Handoff has been independently verified as the best internet-use model ever built, outperforming ChatGPT 5.4 & Opus 4.8 While others focus on coding, we focus on everyday life: ordering food, booking flights, shopping, & navigating the web https://t.co/jcBuAzga9X

    6.2K4844482271.4M viewsView on X
  • Jul 27, 20266.1x their median

    This chart says so much.... - Literally the exact same prompt. - All long horizon one-shots. - Totally reflects real-world experience. https://t.co/sbFyHEfYSb

    5.9K2402581251.7M viewsView on X

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 1.1K interactions against 2.4M followers, an engagement rate of 0.044%. Measured over 55 original posts, its engagement rate beats 72% of 3,739 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 361K times each, and 0.294% of those impressions turn into an interaction. That is about 15.1% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 4.4 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 55 posts sampled, 51% carry an image or video and 36% link out. The account's strongest tracked post pulled 48K interactions, about 45x its own typical post.

What is Chamath Palihapitiya's engagement rate on X?
Chamath Palihapitiya (@chamath) has an engagement rate of 0.044%, based on the median interactions across 55 original posts from the last 30 days against 2,400,555 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.044%, Chamath Palihapitiya sits above the 25th percentile of the 36,378 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 @chamath have real engagement?
Its engagement rate beats 72% of the tracked X accounts closest to it in follower count (3,739 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 @chamath post?
Most posts go out around 16:00 UTC, and Tuesday is its busiest day, at roughly 4.4 posts per day across the measured window.

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