rebecca simmonds 🦭/acc
695 posts

rebecca simmonds 🦭/acc
@RJ_Simmonds
Managing Executive of Walrus Foundation

Crypto Tumbles as Iran Conflict Escalates, BTC back under $70K, and we're Talking NFTs, AI, & Prediction Markets with Managing Executive of Walrus Foundation @RJ_Simmonds x.com/i/broadcasts/1…

Episode 227: Decentralized Data Markets for the AI Era with Rebecca Simmonds of Walrus Foundation @alextapscott @RJ_Simmonds @WalrusProtocol @CMCC_Global 0:00 Introduction 0:35 Why AI Agents Need Crypto Rails 3:51 Walrus: Building a Decentralized Data Layer 6:06 Sui, Storage, and the New AI Infrastructure Stack 8:09 Who Needs Verifiable, Censorship-Resistant Data? 10:20 AI Decision-Making and the Importance of Data Provenance 11:59 Owning Your Data in the Age of Personal AI Agents 15:19 How Walrus Compares with Existing Projects 21:15 Enterprise Adoption: Crossing the Web3 Chasm 23:06 What Matters Most: Security, Availability, and Trust 26:40 Tokenomics: How the WAL Ecosystem Works 29:21 Big Picture: Why Data Ownership Defines the AI Future 33:37 Where to Learn More & Outro






Had meetings and a dinner with 20+ enterprise AI and IT leaders today. Lots of interesting conversations around the state of AI in large enterprises, especially regulated businesses. Here are some of general trends: * Agents are clearly the big thing. Enterprises moving from talking about chatbots to agents, though we’re still very early. Coding is still the dominant agentic use-case being adopted thus far, with other categories of across knowledge work starting to emerge. Lots of agentic work moving from pilots and PoCs into production, and some enterprises had lots of active live use-cases. * Agentic use-cases span every part of a business, from back office operations to client facing experiences from sales to customer onboarding workflows. General feeling is that agentic workflows will hit every part of an organization, often with biggest focus on delivering better for customers, getting better insights and intelligence from data and documents, speeding up high ROI workflows with agents, and so on. Very limited discussion on pure cost cutting. * Data and AI governance still remain core challenges. Getting data and content into a spot that agents can securely and easily operate on remains a huge task for more organizations. Years of data management fragmentation that wasn’t a problem now is an issue for enterprises looking to adopt agents. And governing what agents can do with data in a workflow still a major topic. * Identity emerging as a big topic. Can the agent have access to everything you have? In a world of dozens of agents working on behalf, potentially too much data exposure and scope for the agents. How do we manage agents with partitioned level of access to your information? * Lots of emerging questions on how we will budget for tokens across use-cases and teams. Companies don’t want to constrain use-cases, but equally need to be mindful of ultimate token budgets. This is going to become a bigger part of OpEx over time, and probably won’t make sense to be considered an IT budget anymore. Likely needs to be factored into the rest of operating expenses. * Interoperability is key. Every enterprise is deploying multiple AI systems right now, and it’s unlikely that there’s going to be a single platform to rule them all. Customers are getting savvier on how to handle agent interoperability, and this will be one of the biggest drivers of an AI stack going forward. Lots more takeaways than just this, but needless to say the momentum is building but equally enterprises are acutely aware of the change management and work ahead. Lots of opportunity right now.




🚨 BIG: 65 TB of indexed blockchain data from Bitcoin, Sui, Ethereum, Arbitrum, Tron and XRP just landed on Walrus. And we're not talking raw data. These are standardized, finance-ready datasets from @AlliumLabs, the platform trusted by Visa and Stripe. All datasets are encrypted and unlocked the moment you purchase, whether you're a human or an AI agent. And this is just the first 65 TB 🦭👀

⚡️ LATEST: The global data monetization market hit $3.47B in 2024. That's just the visible part. There are trillions of dollars in data value sitting untouched because there's no infrastructure to make it safely tradable. Walrus doesn't unlock all of that overnight, but it gives builders the tools to start: prove where data came from, control who can access it, set usage terms with smart contracts, and verify that the data is exactly what it claims to be. The first real foundation for a data economy.





Agents will eventually outnumber humans by orders of magnitude. Aaron Levie on the infrastructure that will be needed to manage them: "Whether you think the number is 10x or 100x... we're going to have some order of magnitude more agents than people." "There's going to be just incredibly spectacularly crazy security incidents that will happen with agents, because you'll prompt-inject an agent and find your way through the CRM system and pull out data you shouldn't have access to." "How do you make sure you have the right security, the permissions, the access controls, the data governance?" "We actually don't yet exactly know in many cases how we're going to regulate some of these agents." "No matter what, there's going to need to be a layer that manages the data they have access to and the workflows they're involved in." "This is the new infrastructure opportunity in the era of agents." @levie on @latentspacepod








