Walrus

@WalrusProtocol · Sui · joined 20 Jun 2024

The Verifiable Data Platform for AI & onchain finance. Walrus makes every byte provable, programmable, & always available. Built by the team behind @SuiNetwork.

368 569Followers

249Following

4 859Posts total

31.8KViews on collected posts

Ultimi post

Walrus@WalrusProtocol8 Sep

Join us tomorrow Sept 9th at 3:00 PM UTC on Walrus' @discord for an AMA with Stefano, founder of @EpochSui. We'll dive into trust infrastructure on @SuiNetwork, trustless vesting, and .epoch names. Join here: https://t.co/69DCLEcfI3 https://t.co/Q04u4A7aAN

2.7K views · 21 likes · 3 reposts · 5 replies Open on X →

Walrus@WalrusProtocol8 Sep

🧵 1/4: Builder Spotlight: @Sceat_ 🛠 You give Claude Code or Cursor a prompt, it writes the code, fixes its errors, and drops a completed project folder in front of you. Then it stops; because publishing a website usually requires human accounts, credit cards, and logins. https:

5K views · 33 likes · 6 reposts · 4 replies Open on X →

Walrus@WalrusProtocol8 Sep

When an AI agent loses state, where do you feel it first? Let us know in the poll below. We're taking the question into @HumanXco. 🇳🇱 4.8K views · 20 likes · 3 reposts · 3 replies Open on X →

Walrus@WalrusProtocol8 Sep

Heading to @HumanXCo in Amsterdam? 🇳🇱 We’re joining 8,000+ AI builders to solve a critical production issue: agents that reset every time a session ends. Catch @kostascrypto on Day 1 for our interactive Masterclass:"Memory that survives the session: building agents that don't 6K views · 40 likes · 9 reposts · 2 replies Open on X →

Walrus@WalrusProtocol8 Sep

If you're still deciding whether HumanX 2027 is worth it, the speaker roster just made that decision for you. 100 names, live now: https://t.co/7NVH9UQLyk #HumanX #AI #ArtificialIntelligence https://t.co/2B49OON4hr

0:25

1.8K views · 0 likes · 0 reposts · 0 replies Open on X →

Walrus@WalrusProtocol8 Sep

@WalrusProtocol Giving an AI memory is easy but making sure it remembers your data (and only your data) is the hard part. That distinction matters. 32 views · 1 likes · 0 reposts · 1 replies Open on X →

Walrus@WalrusProtocol8 Sep

@WalrusProtocol Exactly. AI needs fresh and private memory to give the right answers. If the data is old or exposed, even a smart agent can get it wrong. Walrus is solving a real problem here. 25 views · 0 likes · 0 reposts · 0 replies Open on X →

Walrus@WalrusProtocol7 Sep

@WalrusProtocol true, devs keep treatin storage like a simple cache layer 33 views · 2 likes · 0 reposts · 1 replies Open on X →

Walrus@WalrusProtocol7 Sep

A hotel search yielding stale rates is bad state management. Exposing another user's prompt is a lack of access control. If memory isn't encrypted, isolated, and verifiably updated at the storage layer, agents will keep leaking private context and serving stale outputs. 11.5K views · 71 likes · 8 reposts · 7 replies Open on X →

Rispetto ad account della stessa dimensione

9 post degli ultimi 90 giorni, accanto alla fascia di 100K–1M follower. sotto i pari sia per copertura sia per interazione.

Visualizzazioni mediane2 728questo account4 820mediana per 100K–1M

Copertura, %0.74%questo account1.76%mediana per 100K–1M

Interazione, %0.87%questo account1.29%mediana per 100K–1M

Metrica	Questo account	Mediana per 100K–1M	Rapporto
Visualizzazioni mediane per post	2 728	4 820	0.57×
Copertura (visualizzazioni ÷ follower)	0.74%	1.76%	0.42×
Tasso di interazione	0.87%	1.29%	0.67×

Altri account di questa fascia → Confronta con un altro account → Come sono costruiti questi parametri →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

11.5K7 Sep

258 Sep

1.8K

4.8K

2.7K

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.77%7 Sep

9.09%

0.00%8 Sep

6.25%

0.06%

0.87%

0.54%

0.87%

1.10%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.29%.

What the audience does

Likes75.5%188 in total

Reposts11.6%29 in total

Replies9.2%23 in total

Quotes2.0%5 in total

Bookmarks1.6%4 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Ultimi post

Rispetto ad account della stessa dimensione

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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