. @Silicon_Data and @computeexchange were both built after the ChatGPT moment. But I still wouldn’t call either company truly AI-native—yet. Being founded in the AI era doesn’t automatically make an organization AI-native. Giving every employee access to ChatGPT certainly doesn’t. I’ve been thinking about the organizational structures of both companies, and the exercise has made me realize that AI-native organizations will not all look the same. @Silicon_Data is organized around building the independent reference layer for the compute economy: data infrastructure, indices, benchmarking, research, product commercialization and market adoption. @computeexchange is organized around creating liquidity: sourcing, verification, pricing, matching, contracting and settlement. Agents can transform both companies—but differently. At @Silicon_Data, agents can accelerate data analysis, research, product development, content production and customer intelligence. At @computeexchange, they can automate inventory normalization, provider onboarding, RFQs, matching and transaction workflows. This has also changed how I think about organizational design. Traditional companies are built around people, roles and reporting lines. Knowledge is distributed across individual brains, inboxes, documents, Slack channels and meetings. In that sense, a human organization is web-based: every person is a node, and work moves through the relationships connecting those nodes. An agent organization may be fundamentally different. It is Brain-based. Instead of every agent holding a fragmented version of the company, agents can operate from a centralized institutional Brain containing shared knowledge, history, decisions, priorities, permissions and real-time operating context. Each Brain sits a task-ownership system. Instead of asking, “Whose job is this?” the organization asks: What needs to be accomplished? What context and authority does it require? Should a human, an agent or a human-agent team own it? What constitutes completion? Who remains accountable? Humans continue to operate through networks of relationships, judgment, negotiation and trust. Agents operate through centralized knowledge, shared context and structured task ownership. The task layer tells you what needs to happen, who—or what—owns it, and whether it has actually been completed. To me, becoming AI-native means continuously redesigning this boundary between people, agents, knowledge and work. We are still experimenting. I’ll share what works, what fails, and how the two organizations evolve.