Top Tweets for #SearchTech

At OptimAI, we treat search very differently. 💡https://t.co/23lplRMNR8 Search is often framed as a product, a place you go to retrieve information. But for AI systems, search is not a destination. It is infrastructure. Agents don’t operate on isolated queries. They require continuous access to fresh, multi-source data (web, social, and real-time signals) flowing as part of an ongoing process. This fundamentally changes how search must be designed. It is no longer a query-response loop. It becomes a distributed pipeline that continuously retrieves, verifies, and updates context. OptimAI Search is built this way. Through a decentralized network of nodes, it can scale horizontally: accessing and processing thousands of sources in parallel, rather than being limited to a small set of indexed results. Instead of searching a few pages better, the system explores the web at scale --> concurrently, continuously, and without bottlenecks. This is what enables agents to operate, not just respond. What you’re using is not just search. It’s the data layer for autonomous systems.