Agent operating system infrastructure for reliable, scalable AI agents
Build an operating system layer between AI agents and their underlying computers, AI models, databases, and tools. The layer manages scheduling, memory, tool access, identity, observability, guardrails, and human approvals so agents can handle real customer interactions, money, and decisions more reliably.
online BOTH AI Agents & Automation
From IBM Technology — Why AI Agents Need an Operating System at 04:29
Problem: AI agents can forget previous work, lack clear tool permissions, act without sufficient safeguards, fail to explain their decisions, and interfere with one another when multiple agents run together. This creates unreliable and inefficient systems that can mishandle data, money, or production resources.
For: Teams deploying AI agents for customer interactions, expense handling, flight booking, coding, email, and other business decisions.
Examples
- A customer service agent handles a live chat while another agent summarizes the previous day's tickets; the scheduler keeps the live customer from waiting while the background task uses resources.
Behind this: 12 build steps · how to validate demand · 5 more real examples · 10 things the video never answers.
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