Pinned
Walrus Sessions 6 is live with @inkray_io.
A 30-day challenge to write about AI agents and Walrus Memory, the tech, the use cases, and what portable memory actually makes possible.
$3,000 WAL prize pool. Here's how it works 👇
Walrus 🦭/acc
@WalrusProtocol
The Verifiable Data Platform for AI & onchain finance.
Walrus makes every byte provable, programmable, & always available.
Built by the team behind @SuiNetwork.
- 🧵 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.
- "It's been one of the biggest upgrades for my productivity." Huge thanks to @nateherk for breaking down how Walrus Memory lets you jump between Claude and ChatGPT without ever having to re-explain yourself. Check out the breakdown on YouTube:
- 🧑🚀@astros_ag wanted traders to be able to see the pattern behind a trade, not just the P&L line. Read more about how they're building that on Walrus: onchain data run through #AI analytics, so every decision leaves a record you can check against.Replying to @astros_agBy combining Walrus' decentralized data infrastructure with AI-powered analytics, Astros is creating new ways for traders to understand their performance, uncover patterns, and improve. Welcome to a smarter trading experience. 🧠⚡️ Full Story 👇 x.com/astros_ag/stat…
- AI agents are entering financial markets, but they can't verify the data they act on. Trading data today is fragmented across exchanges, indexers, and custom pipelines. Humans lean on trust and reputation. Agents need something else: a verifiable, common standard for execution
