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From AI to Agents to Agencies
Two years ago, I wrote about the transformative potential of AI Agents - autonomous systems that could break down complex tasks and execute them without constant human intervention.
What I'm witnessing is the birth of what I believe should be called Agencies - systems that tackle individual tasks by dynamically orchestrating different types of intelligence, each optimized for specific subtasks, all working toward completing a single overarching objective. When given a task like "build a web application," the Agent would use one primary intelligence source (say, GPT-4) for all aspects - planning, coding, debugging, documentation - supplemented by external tools for specific functions. This evolution makes AI task completion more efficient, cost-effective, and higher quality by ensuring each piece of work gets handled by the type of intelligence best suited for it, while maintaining coherent progress toward a single objective.
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