Walrus engagement report
@WalrusProtocol - 369K followers on X
Measured over 15 original posts from a 30-day window, last computed on September 1, 2026.
Engagement
A typical post picks up 62 interactions against 369K followers, an engagement rate of 0.017%. Measured over 15 original posts, its engagement rate beats 34% of 6,874 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 9.3K times each, and 0.667% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 15 posts sampled, 73% carry an image or video, 7% are part of a thread and 27% link out. The account's strongest tracked post pulled 2.3K interactions, about 37x its own typical post. Recurring topics include #walrusmemory, #walrus.
Measured over 15 original posts from a 30-day window, last computed on September 1, 2026. Recurring tags: #walrusmemory, #walrus.
Compared with accounts its own size
Walrus's engagement rate beats 34% of the tracked X accounts closest to it in follower count (6,874 accounts, accounts of similar size (decile 8 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 37% 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 0.017%, Walrus sits above the 25th percentile of the 66,258 accounts in this comparison. That places it in the below the median band, which runs 0.016% to 0.1%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.016% |
| 50th percentile | 0.1% |
| 75th percentile | 0.499% |
| 90th percentile | 2.09% |
| 99th percentile | 119.6% |
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 Monday 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 | 73% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 27% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 73% 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.
- 27% 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 462 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 26, 202637x their median
working with ai agents is like if all your employees had dementia
- Aug 28, 202619x their median
I receive around 3-5 requests to test a new AI product daily. Almost all of them require creating a new account and logging into a separate website or app. Meanwhile, I basically only use ChatGPT, Grok, etc to do everything on my computer and browser. These harnesses already have all my context and I don't want to start over from scratch with a new website or tool that only understands a small slice of my data. So with a few exceptions, the new products that I'm mostly likely to adopt need to work in today's top AI harnesses. I realize only a small segment of users behave this way but I bet this segment will expand drastically soon.
- Aug 24, 20262.4x their median
Moving your AI memory has never been more necessary. @kostascrypto @gazza_jenks on @theblockco. https://t.co/ssUV7ylVw5
- Aug 10, 20262.3x their median
🧵1/3: Claude Code's auto memory only lives on your machine, in one repo. Switch machines, or open Codex, and it starts from zero. You could commit it to your repo instead. Now it's a file everyone with repo access can read, and it still never leaves Claude Code.
- Aug 27, 20262.0x their median
Live in Lagos @SuiHubAfrica: over 30 builders gathered in person to learn prompt design and build with Walrus Memory and context. Taking our online Prompt Jam 5 format offline, this session gives builders hands-on guidance to explore what is possible with portable agent memory. Looking forward to seeing what the teams build.
- Sep 1, 20262.0x their median
Around 4B paper documents circulate through the $25T global trade market, making document fraud a massive, systemic risk. @blockticity is changing that by bringing over 1M authenticated records ($7.7B+ in real-world assets) onto Walrus. By mirroring 15TB+ of trade evidence across five commercial verticals, Blockticity gives partners public, cryptographic proof of origin while keeping sensitive commercial data protected. Read the full announcement: https://t.co/U0fvb0Qzw0
- Aug 21, 2026
Most exam prep tools re-test material students already understand. Today's Prompt Jam spotlight: Exam Mistake Memory by @eazitechh, (@/eazitech1) on Github. Exam Mistake Memory tracks errors, pinpoints specific knowledge gaps, and generates targeted practice sessions based on past attempts. Explore the prompt: https://t.co/15kukEn0pi
- Sep 1, 2026
August brought verifiable AI trading, new Walrus Memory tutorials, and $WAL to 80M+ Revolut users. Here is everything that shipped: ⬛️ Launched the Walrus Verifiable Trading Standard with @Astros_ag to make market data machine-readable and auditable. ⬛️ Shipped three new tutorials for adding portable Walrus Memory across TypeScript SDK, Claude Code, and Claude Desktop. ⬛️ Published a 4-part deep dive breaking down agentic memory and context engineering. ⬛️ $WAL went live on @Revolut, expanding access to 80M+ users across 40+ countries. ⬛️ @KostasCryptos broke down verifiable infra on @TheBlockCo's Starting Block podcast and @ThePaypers. ⬛️ Rebuilt the Docs with product-first navigation across Walrus, Walrus Memory, and Walrus Sites. ⬛️ Catch us next month at @HumanXCo in Amsterdam, and grab your tickets for Sui Basecamp in Singapore (Oct 7–8). Need links to the events? Let us know in the comments and we can reshare them.
- Aug 20, 2026
We're announcing Session Lagos: Walrus Memory x AI Prompt, a hands-on hackathon hosted at SuiHub. Participants will build an AI agent with real memory using Walrus Memory, then share the exact prompt so others can build the same thing. No coding or web3 background required. $300 WAL prize pool. 📍 SuiHub Lagos, 27th August 🕑 12:00 PM · Judging (virtual), 28th August
- Sep 1, 2026
Decentralized notes, stored on Walrus. Tune in tomorrow for our next Builder AMA featuring @Edcriptofi, Founder of @wal_notes. We'll be diving into how they use Walrus for storage and answering questions live. We're giving away exclusive merch for the best questions shared in our @discord [ama-questions] channel! 📅 Sept 2 @ 3 PM UTC 📍 Walrus Discord: https://t.co/4CrUUipBkL You'll want to bookmark this one.
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.
Buy or sell X accounts - escrow-protected
PlayerSells is an escrow marketplace for X accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 62 interactions against 369K followers, an engagement rate of 0.017%. Measured over 15 original posts, its engagement rate beats 34% of 6,874 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 9.3K times each, and 0.667% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 14:00 UTC, and Monday is the busiest day of the week. Of the 15 posts sampled, 73% carry an image or video, 7% are part of a thread and 27% link out. The account's strongest tracked post pulled 2.3K interactions, about 37x its own typical post. Recurring topics include #walrusmemory, #walrus.
- What is Walrus's engagement rate on X?
- Walrus (@WalrusProtocol) has an engagement rate of 0.017%, based on the median interactions across 15 original posts from the last 30 days against 368,500 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.017%, Walrus sits above the 25th percentile of the 66,258 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 @WalrusProtocol have real engagement?
- Its engagement rate beats 34% of the tracked X accounts closest to it in follower count (6,874 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 @WalrusProtocol post?
- Most posts go out around 14:00 UTC, and Monday is its busiest day, at roughly 2.6 posts per day across the measured window.