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You already know the routine: The IT business, pushed as a lot by vendor ambition as by necessity, develops many competing requirements to unravel a easy downside. At present’s perpetrator: agent-to-agent communication in AI.
The latest rise of so-called “requirements” for the way clever brokers ought to talk echoes previous points with service-oriented architecture, net providers, and varied messaging middleware conflicts. The important thing distinction is that now, this confusion might stop probably the most promising areas in enterprise know-how—agentic AI—from ever offering actual worth.
Let’s set the scene. Clever brokers, whether or not they’re specialised large language models (LLMs), service-brokering bots, Internet of Things digital twins, or workflow managers, want to speak effectively, securely, and transparently. This can be a typical interoperability concern. A well-established business might, in principle, create an easy, sensible protocol and transfer ahead. As a substitute, we see a flood of rising requirements from too many “knowledgeable” voices with an underlying agenda, every accompanied by a white paper, a group name, a sponsored convention, and, in fact, an ecosystem. That is the core downside.