AI Agents: From Chatbots to Coworkers — What Actually Changed скачать в хорошем качестве

AI Agents: From Chatbots to Coworkers — What Actually Changed

Three companies made the same move in the same week. Anthropic shipped enterprise plugins that let Claude edit your spreadsheets and file your docs. AWS published IAM integration for managed MCP servers. Google put AI agents at the OS level on Pixel and Galaxy devices. The pattern is clear: AI stopped being something you ask questions to. It's becoming something that does work for you — inside the tools you already use. But here's what most coverage misses: the model isn't the moat. The harness is. Constraints, permissions, observability, feedback loops — that's what separates a demo from a production system. In this video, I break down what actually changed, why the control layer matters more than model capability, and what this means whether you're an architect designing agent infrastructure or someone just trying to understand where AI is heading. Not technical? No problem — I walk through the plain-English version too. --- Timestamps: 0:00 — Three announcements, one pattern 0:25 — What AI agents actually do now 0:55 — The control layer: why governance is the real moat 1:25 — Plain English: what this means for everyone 1:50 — What to watch next --- Subscribe for weekly breakdowns on AI, cloud, and security — built on 30 years of pattern recognition, not repackaged press releases. #AIAgents #CloudComputing #AWS #Anthropic #GenerativeAI #PlatformEngineering #CloudArchitecture