Walrus is the data platform built for the demands of AI, where data is portable, protected, and verifiable. Created by the ex-Meta engineers behind @SuiNetwork.
Sui
Joined June 2024
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Featured in @Forbes: Walrus Memory.
“There was a point in time that we were stopped from accessing Fable and Mythos. And imagine at that time, what do I have to do?” — @kostascrypto
5,000+ agents and 4.5M+ retrievals later, here is why builders are moving to portable, user-keyed memory so switching LLMs doesn't mean starting from zero.
Read the full piece by @guneyyildiz: forbes.com/sites/guneyyildiz…
ALT If a company can swap one model for another in an afternoon, the real lock-in moves to everything its agents have learned about the business. Chalkias noted three reasons companies switch models: a better model arrives, a cheaper one does the job, or a regulator or employer restricts which systems can be used. He pointed to this summer’s interruption, between June 12 and July 1, when access to Anthropic’s Fable and Mythos models was suspended. “There was a point in time that we were stopped from accessing Fable and Mythos. And imagine at that time, what do I have to do?” Chalkias said. In most enterprise setups, switching models means leaving accumulated context behind. “You’re not able to go and get your data and move it to another LLM.”
The plan was to type “login.” The system crashed after “lo.”
Today the problem is different: your files live in one tool, your agent’s context in another. Walrus Console puts them in one place. ☝️
→ Files and agent context together
→ Native MCP for Claude Code and Cursor
→ Encrypted by default
#InternationalInternetDay
Walrus retweeted
Unwritten in 2 minutes 🎥
A house's spending rules, written by nobody.
Learned from real decisions, checked against the wallet on @SuiNetwork Mainnet.
Rules that drift. Spend nobody approved. Proof you can run live.
Built for #TotalRecall with @WalrusProtocol Memory × @tatum_io
Money just left the household account, but did anyone agree to it?
That’s the question behind Unwritten, @EdCriptoFi’s Total Recall build. It learns a family’s real spending rules from their decisions, then checks them against what happened.
Walrus Memory holds what was agreed, with every rule versioned so the history stays intact. @tatum_io reads what moved on Sui.
Where they don’t match, Unwritten flags it, like a “2 signatures over $100” rule the family stopped following.
Solid submission @EdCriptoFi 🙌.
BUILDERS: Total Recall is open through Nov 10, drop your submissions 🫡
Walrus retweeted
In 5 years, the goal for Walrus is simple: powering the AI applications and agent experiences that couldn't exist on legacy infrastructure.
Video by @AltCryptoGems, interviewing @Kenton.
Walrus retweeted
When your agent buys something for you, what did you ask for, and what did it do?
Answering that takes a record both sides can check. Memory that’s verifiable and can’t be quietly edited later gives you that record.
We’ve always said there’d be disputes once agents started acting for people, especially in commerce
Any time someone acts on your behalf, there’s a gap between what you asked for and what they did
With people, we close that gap with things like contracts, receipts and signatures. But agents are different
They’ll make thousands of decisions for you, far more than anyone could check. And none of those decisions comes with anything that proves what you actually agreed to
So disputes are coming either way, and we need a way to settle them
As far as I can see, there are 3 ways this can go
The first is sharing your login with the agent, which is what a lot of people are doing today
The problem is that the agent then looks exactly like you. Nobody can separate what you asked for from what it decided on its own
The second is letting every platform keep its own logs and trusting them. That falls apart the moment two sides disagree, because each one is holding its own version
The third is giving agents their own authority with clear limits, plus a shared record of what they did with it
That third option sounds simple, but it puts real demands on the infrastructure underneath
1. The proof has to sit somewhere neither side controls
2. Once it’s written, nobody can change it without everyone seeing
3. Anyone in the dispute has to be able to verify it on their own
4. It has to hold up at agent scale, which means a huge amount of data kept available for a long time
A regular cloud account can’t give you that on its own. Cloud storage is fine for the private details. But the proof can’t depend on trusting one company, because trust in one party is the first thing to go in a dispute
The proof needs a different kind of infrastructure, and @WalrusProtocol is a good example of what that looks like
It’s run by many independent operators, so no side in a dispute controls it
Each piece of data stored on Walrus is tied to an ID made from its own content. That means no one can change the proof once it’s stored. A record either matches its proof or it doesn’t, and there’s no way to fake the match
Access can be limited to the parties involved, so nobody outside the dispute can read it. Each of them can check the proof on their own, without going through the other side
It’s also built to keep a huge amount of data available for the long run. Even if some operators go offline, the data will still be there
That’s one of the reasons Walrus is core infrastructure for VAA
Walrus retweeted
🥇1st place in Walrus Session 8: Chatbots That Remember goes to @inspikalu for Playbook, a chatbot with a built-in simulation workbench (bridges, queues, solar, and more).
It remembers your limits, your best settings, and what already failed, so every session picks up where you left off.
“The useful part of engineering help is not the textbook answer. It is remembering your limits, your best result, and your failures.”
Check out the article on @Medium: medium.com/@inspikalu/playbo…
Live demo on @vercel: playbook-nine-tau.vercel.app
In 5 years, the goal for Walrus is simple: powering the AI applications and agent experiences that couldn't exist on legacy infrastructure.
Video by @AltCryptoGems, interviewing @Kenton.
🥇1st place in Walrus Session 8: Chatbots That Remember goes to @inspikalu for Playbook, a chatbot with a built-in simulation workbench (bridges, queues, solar, and more).
It remembers your limits, your best settings, and what already failed, so every session picks up where you left off.
“The useful part of engineering help is not the textbook answer. It is remembering your limits, your best result, and your failures.”
Check out the article on @Medium: medium.com/@inspikalu/playbo…
Live demo on @vercel: playbook-nine-tau.vercel.app
Walrus retweeted
Decentralized storage and data availability protocols like @WalrusProtocol are definitely going to be crucial for scaling Web3 and AI infrastructure
Walrus retweeted
AI 연구소들은 컴퓨팅 파워를 살 수 있습니다. 하지만 학습 데이터가 어디서 왔는지 증명하는 일은 훨씬 더 어렵습니다. 🧵
@datafdn 의 DATA Network가 @SuiNetwork 에 합류합니다. Trace(출처 증명), @WalrusProtocol(저장), Sui(기반 인프라)가 하나의 공급망을 이루어, 사용 권한이 확보된 AI 학습 데이터를 공급합니다.
각 요소가 어떻게 맞물리는지 살펴보겠습니다 👇
xitter.gq/datafdn/status/2109468…
#DATAonSuiQuest
DATA is coming to @SuiNetwork.
The DATA Network and Trace are joining the Sui stack, bringing a live supply of rights-cleared AI training data to infrastructure built for AI workloads.
With 250M+ receipts already recorded by Trace, AI labs will be able to source real-world data with verifiable provenance, while @WalrusProtocol provides the underlying storage layer.
Sui Foundation is investing $30 million in the DATA Network, establishing the largest institutional stake in the network, alongside the continuing holdings of PIP Labs and the DATA Foundation. Furthering the alignment, SY Lee, founder of the DATA Network and CEO of PIP Labs, joins Sui Foundation as Strategic Advisor.
In the coming months:
▸ The DATA Network will be upgraded to run as a protocol natively on Sui
▸ Walrus becomes the default storage layer for DATA Foundation apps
▸ $DATA remains the token of the DATA protocol
The next chapter of DATA starts here.
Walrus retweeted
If you're in crypto - trying Matterhorn today is your No. 1 TO DO!
Let's buidl 🦾🦾🦾
Vibe coding is democratizing how software gets built.
Shoutout to @matterhornso for building an AI agent solution on Walrus that makes it possible for anyone (developer or not), to become an AI builder.
Video by @AltCryptoGems featuring our Product Marketing Manager, @Kenton.
Walrus retweeted
EPITAPH - The wall is closed.
75 filed. The Keeper read every one and kept 15.
Kept by the Keeper: @rizkialfazr @icechog @woibilly
Chosen by the ground: @0xratel @notautumnnnnn
The Keeper files.
The five carry the first window and the pen.
Everyone who filed a valid entry carries the pen.
It is on the record and on the board.
Walrus retweeted
Memory @WalrusProtocol with @X API
Read all posts, categorized them, and assigned badges and points.
Way too easy to run giveaways 🎁
EPITAPH - The wall is closed.
75 filed. The Keeper read every one and kept 15.
Kept by the Keeper: @rizkialfazr @icechog @woibilly
Chosen by the ground: @0xratel @notautumnnnnn
The Keeper files.
The five carry the first window and the pen.
Everyone who filed a valid entry carries the pen.
It is on the record and on the board.
Walrus retweeted
We’ve always said there’d be disputes once agents started acting for people, especially in commerce
Any time someone acts on your behalf, there’s a gap between what you asked for and what they did
With people, we close that gap with things like contracts, receipts and signatures. But agents are different
They’ll make thousands of decisions for you, far more than anyone could check. And none of those decisions comes with anything that proves what you actually agreed to
So disputes are coming either way, and we need a way to settle them
As far as I can see, there are 3 ways this can go
The first is sharing your login with the agent, which is what a lot of people are doing today
The problem is that the agent then looks exactly like you. Nobody can separate what you asked for from what it decided on its own
The second is letting every platform keep its own logs and trusting them. That falls apart the moment two sides disagree, because each one is holding its own version
The third is giving agents their own authority with clear limits, plus a shared record of what they did with it
That third option sounds simple, but it puts real demands on the infrastructure underneath
1. The proof has to sit somewhere neither side controls
2. Once it’s written, nobody can change it without everyone seeing
3. Anyone in the dispute has to be able to verify it on their own
4. It has to hold up at agent scale, which means a huge amount of data kept available for a long time
A regular cloud account can’t give you that on its own. Cloud storage is fine for the private details. But the proof can’t depend on trusting one company, because trust in one party is the first thing to go in a dispute
The proof needs a different kind of infrastructure, and @WalrusProtocol is a good example of what that looks like
It’s run by many independent operators, so no side in a dispute controls it
Each piece of data stored on Walrus is tied to an ID made from its own content. That means no one can change the proof once it’s stored. A record either matches its proof or it doesn’t, and there’s no way to fake the match
Access can be limited to the parties involved, so nobody outside the dispute can read it. Each of them can check the proof on their own, without going through the other side
It’s also built to keep a huge amount of data available for the long run. Even if some operators go offline, the data will still be there
That’s one of the reasons Walrus is core infrastructure for VAA
The banking giant reminds customers that "you're responsible for activity" resulting from your AI agents' access.
spr.ly/6015BHc2mT
When your agent buys something for you, what did you ask for, and what did it do?
Answering that takes a record both sides can check. Memory that’s verifiable and can’t be quietly edited later gives you that record.
We’ve always said there’d be disputes once agents started acting for people, especially in commerce
Any time someone acts on your behalf, there’s a gap between what you asked for and what they did
With people, we close that gap with things like contracts, receipts and signatures. But agents are different
They’ll make thousands of decisions for you, far more than anyone could check. And none of those decisions comes with anything that proves what you actually agreed to
So disputes are coming either way, and we need a way to settle them
As far as I can see, there are 3 ways this can go
The first is sharing your login with the agent, which is what a lot of people are doing today
The problem is that the agent then looks exactly like you. Nobody can separate what you asked for from what it decided on its own
The second is letting every platform keep its own logs and trusting them. That falls apart the moment two sides disagree, because each one is holding its own version
The third is giving agents their own authority with clear limits, plus a shared record of what they did with it
That third option sounds simple, but it puts real demands on the infrastructure underneath
1. The proof has to sit somewhere neither side controls
2. Once it’s written, nobody can change it without everyone seeing
3. Anyone in the dispute has to be able to verify it on their own
4. It has to hold up at agent scale, which means a huge amount of data kept available for a long time
A regular cloud account can’t give you that on its own. Cloud storage is fine for the private details. But the proof can’t depend on trusting one company, because trust in one party is the first thing to go in a dispute
The proof needs a different kind of infrastructure, and @WalrusProtocol is a good example of what that looks like
It’s run by many independent operators, so no side in a dispute controls it
Each piece of data stored on Walrus is tied to an ID made from its own content. That means no one can change the proof once it’s stored. A record either matches its proof or it doesn’t, and there’s no way to fake the match
Access can be limited to the parties involved, so nobody outside the dispute can read it. Each of them can check the proof on their own, without going through the other side
It’s also built to keep a huge amount of data available for the long run. Even if some operators go offline, the data will still be there
That’s one of the reasons Walrus is core infrastructure for VAA
Walrus retweeted
Three ways to integrate Walrus Memory:
1. Core SDK
Store and recall memory with automatic embedding, SEAL encryption, and Walrus storage.
pnpm add @mysten-incubation/memwal
2. OpenClaw plugin
Add automatic memory capture and recall to OpenClaw agents, keeping memory available across sessions.
openclaw plugins install @mysten-incubation/oc-memwal
3. Vercel AI SDK
Add persistent memory to streamText and generateText workflows with middleware.
import { withMemWal } from "@mysten-incubation/memwal/ai";
Full setup + source on @github: github.com/MystenLabs/MemWal
Walrus retweeted
Thank you to all the builders who participated and shipped applications with persistent memory.
Here are the winners across the App, Article, Infrastructure, and Ecosystem categories. 🧵👇
Walrus retweeted
@OpenAI retired legacy API models including GPT‑4, GPT‑4 Turbo, o1, o3-mini, and o4-mini on October 23.
GPT‑4o and GPT‑4.1 willfollow on January 14, 2027.
Model lifecycles are normal. Your agent’s memory shouldn’t share them.
When memory lives outside the model layer, teams can change models without rebuilding accumulated context or locking it to one provider.
Switch models. Keep the memory.
With Walrus Memory, the interface stays the same: remember() on write, recall() on read – whichever model or runtime comes next.
developers.openai.com/api/do…
Walrus retweeted
Vibe coding is democratizing how software gets built.
Shoutout to @matterhornso for building an AI agent solution on Walrus that makes it possible for anyone (developer or not), to become an AI builder.
Video by @AltCryptoGems featuring our Product Marketing Manager, @Kenton.