Discover Crypto | AI Investing engagement report
@DiscoverCrypto - 1.0M followers on X
Measured over 56 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 62 interactions against 1.0M followers, an engagement rate of 0.006%. Measured over 56 original posts, its engagement rate beats 27% 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 30K times each, and 0.21% of those impressions turn into an interaction. That is about 2.86% 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 14:00 UTC, and Wednesday is the busiest day of the week. Of the 56 posts sampled, 48% carry an image or video and 38% link out. The account's strongest tracked post pulled 39K interactions, about 632x its own typical post. Recurring topics include #bitcoin, #hex.
Measured over 56 original posts from a 30-day window, last computed on October 25, 2026. Recurring tags: #bitcoin, #hex.
Compared with accounts its own size
Discover Crypto | AI Investing's engagement rate beats 27% 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 15% 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 0.006%, Discover Crypto | AI Investing sits above the 10th percentile of the 204,694 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 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 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% | 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 | 48% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 38% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 48% 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.
- 38% 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 270 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.
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 24, 2026632x their median
BREAKING: 🇺🇸 American wages have fallen to 43% of national income, the lowest since the Great Depression. For every $1 the US economy produces, workers are getting less of it than at any point since 1929. The rest is going to corporate profits, which are now at an all time high. This is why the economy keeps growing but most Americans feel poorer. GDP goes up, wages go up in dollar terms, but workers are getting a smaller and smaller slice of what they actually produce. Asset prices keep rising for the same reason. Money that used to go to wages is now going to shareholders instead, and shareholders put it into stocks, real estate and other assets.
- Sep 2, 2026253x their median
$1,000 invested 15 years ago today would be worth: • Bitcoin: $8,970,000 • Nvidia: $735,000 • Tesla: $231,000 • Apple: $29,000 • S&P: $8,400 • Gold: $2,150 https://t.co/9ykMebL6nW
- Oct 7, 2026246x their median
I don't recommend anyone scramble to move their funds to new wallets today. But we should take the risks to cryptography from AI-accelerated math seriously, and minimize our exposure to not just quantum-vulnerable cryptography, but also potentially AI-vulnerable cryptography. The core new area of risk from this viewpoint is, unfortunately, ML-DSA / FHE / lattices. (and it's also another reason, along with quantum, why ECDSA might fall even faster than expected, hence the "fresh address" recommendation) So far most people have been in the mode of thinking "elliptic curves broken, hashes safe, lattices safe". But there is a good chance that the concrete security of lattices will take serious hits from the next two years of AI math. The basic threat model is: factoring is something that naively takes 2^(n/2) time, but over decades smart people have found and optimized number field sieves, and degraded that to 2^O(n^(1/3)), which is why RSA keys and signatures need to be ~400 bytes (and not 64 bytes). What if there are skeletons in the closet like that, both for elliptic curves and lattices, that we are simply not smart enough to discover - but bots soon will be? This is a major part of the reason why for the past year ethereum's lean roadmap has been going in the "hash-only" direction: no lattices, no ML-DSA, no Falcon, no lattice-based commitments inside ZK proofs, etc. Signatures in lean ethereum are all hash-based, either WOTS or SPHINCS-. For signatures and proofs, we already know how to go hash-only. The bigger challenge is for *public-key encryption* - and this goes far beyond blockchains. Secure communication, anonymizing protocols, lots of things need public-key encryption. And unfortunately there are long-standing mathematical theorems showing why public-key encryption cannot be done with hashes alone. You have to have some kind of trapdoor object that has at least one form of usable "structure" - either group theory (incl. isogenies) or lattices or code-based or potentially in the future even more newfangled and spooky things (local mixing?). But for anything that has structure, you should assume that AI will make at least some progress in breaking that structure. Here, one reasonable inference is that if you want to make something plausibly long-term secure, multiply the key sizes by 10. To me that's a very plausible world and something not at all extreme to predict. If AI will bring us 50 years of math in 2 years, then that 50 years of math may very plausibly include a "naive factoring -> GNFS" level of improvement to our ability to break lattices. In that world, lattices will still exist, but they will have to be significantly bigger to guarantee the same level of safety. And at those new larger sizes, hash-based constructions will beat lattice-based constructions on concrete efficiency in every use case where hash-based constructions are possible at all. Theoretically, of course it's possible that hashes are broken too (eg. P = NP would imply that). But I think P = NP is very unlikely. And intuitively, it's much more likely that a mathematical object has exactly no exploitable structure (like hashes are intended to), than that a mathematical object has exactly ~3 forms of exploitable structure (for elliptic curves: associativity, Schoof, pairings) and not some secret fourth form of structure we have not yet discovered that greatly degrades its security (for elliptic curves, ECDLP and pairing security). Similar for LWE, SVP, RLWE and the zoo of lattice problems. For this reason, we do not yet see any reason to worry and start padding the byte size of hashes (if we start to worry more, we would pad the round count first before doing anything to the byte size). Concrete TLDR, my own personal views: * Hash-based > lattice-based, in those situations where hash-based is possible at all * For anything lattice-based, be much more paranoid on param sizes. Remember that blockchains are only a small portion of the cryptography story; this point goes far beyond blockchains and applies to eg. access to websites, secure messaging, Tor / VPNs ... * For privacy protocols, strongly favor NOT putting encrypted notes onchain. Instead, send them offchain through some third-party mechanism. * If it's not difficult for you, keeping your funds in addresses which have not yet been used to make a transaction is a good idea. If it's easy for you, do it. **But be careful about migrations; I personally have lost more money in botched migrations than I have lost in all hacks combined**. * For multisig wallets, doing confirmations offchain is better than onchain, because this way the signatures of signer wallets do not get exposed to the public, so if ECDSA falls to AI much faster than expected, at least the multisig "gracefully degrades" to a 1-of-1 where the 1 is whoever was gathering the signatures - a much better place to be than "anyone can take the money" https://t.co/oVjwZog2lL
- Sep 21, 2026200x their median
JUST IN: Google $GOOGL and Apple $AAPL are hiring crypto experts as they expand into stablecoins, tokenization and blockchain payments. https://t.co/R2QmBF4yVt
- Aug 25, 2026163x their median
JUST IN: Bitcoin surges to $81,000 as $225,000,000 in shorts are liquidated from the crypto market in 10 minutes. https://t.co/z6ULLseNjj
- Oct 2, 2026136x their median
Want to have your mind blown? The median U.S. family income in 1971 was 252.2 oz of gold. That would be $1,053,623/yr today.
- Sep 2, 2026136x their median
JUST IN: G20 agrees to develop clear regulatory framework for crypto and stablecoins.
- Sep 9, 2026133x their median
Incredible quote by Bessent… "I am the house now." https://t.co/T23GkRTvi1
- Sep 4, 2026109x their median
BREAKING 🚨: Housing Market Number of Home Buyers falls to lowest level ever recorded 🤯 👀 https://t.co/fH9z9DYyZO
- Oct 13, 2026109x their median
Mila Kunis called Uber "the worst idea ever." Ashton Kutcher and his partner invested $500,000 in the company. By 2016, that stake was worth roughly $50 million, according to Forbes. In the video below, Kunis tells Stephen Colbert why she tried to talk her future husband out of investments like these. Her family left Soviet Ukraine in 1991, when she was seven. In Los Angeles, her father, a trained engineer, worked as a cab driver. Kutcher described Uber as a cab company where anyone could drive. He offered to order her a ride so she could try it. "You're going to put me in a car with a stranger? What is wrong with you?" Then he told her about Bitcoin. She asked, "Is it FDIC insured?". Kutcher replied: "No. That's the point. It's not." "I think this is a horrible idea," she recalled telling him. His response: "Cool, we're investing it." At the beginning of 2013, Bitcoin traded below $100. During the week of her interview in April 2021, it traded above $50,000. Kunis says she now books accommodation through Airbnb and takes Uber everywhere. "I've never been happier to be wrong."
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 62 interactions against 1.0M followers, an engagement rate of 0.006%. Measured over 56 original posts, its engagement rate beats 27% 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 30K times each, and 0.21% of those impressions turn into an interaction. That is about 2.86% 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 14:00 UTC, and Wednesday is the busiest day of the week. Of the 56 posts sampled, 48% carry an image or video and 38% link out. The account's strongest tracked post pulled 39K interactions, about 632x its own typical post. Recurring topics include #bitcoin, #hex.
- What is Discover Crypto | AI Investing's engagement rate on X?
- Discover Crypto | AI Investing (@DiscoverCrypto) has an engagement rate of 0.006%, based on the median interactions across 56 original posts from the last 30 days against 1,032,681 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.006%, Discover Crypto | AI Investing sits above the 10th percentile of the 204,694 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 @DiscoverCrypto have real engagement?
- Its engagement rate beats 27% 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 @DiscoverCrypto post?
- Most posts go out around 14:00 UTC, and Wednesday is its busiest day, at roughly 4.37 posts per day across the measured window.