IBM : The identity problem for agentic AI security - marketscreener.com
<a href="https://news.google.com/rss/articles/CBMiowFBVV95cUxPZ1RoNVRvZXpVNmNqWk1WOEgtT2VYTmZkSFltTUZsRUlWSmYzbk1KcHBKUzctZkxwVVdzWHV5cjcwQU4tVG1kUDVvVXg3SWRxSWtIaTVVZmRJT1lMZ25tbjNfNy1ITk5FYlpodEVhdmJsMGtVOHJ1R25BUlN2YmNtb3NMNXdaNVNad0xHdnRmZDlwN1hQSl84TUJBb3M5eUNRSG9r?oc=5" target="_blank">IBM : The identity problem for agentic AI security</a> <font color="#6f6f6f">marketscreener.com</font>
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The Agent Orchestration Problem Nobody Talks About
Everyone building agents eventually hits the same wall: one agent calls another, which calls another, and suddenly you have a chain of models all hallucinating off each other. Its the telephone game, but every participant is confidently making things up. The naive approach that fails: Agent A extracts data. Agent B summarizes. Agent C formats. Agent D sends. Each step compounds error. By the time Agent D acts, the original intent has mutated beyond recognition. This is why most multi-agent demos work great in controlled scenarios but fall apart in production. What actually works: The fix isnt smarter models. Its grounded handoffs . Structured state, not natural language. Agents should pass JSON schemas or typed objects, not paragraphs of text. Natural language is lossy. Structured data is
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