The trick to designing agentic AI is learning how to think like a manager
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The trick to designing agentic AI is learning how to think like a manager
"The main challenge isn't the interface. It's management. What is an agent hired to do, what can it decide on its own, and when does it need to come find you?"
"Customers wanted to upload a job description and get an appropriate salary range, including location and years of experience, from our database."
"They were going outside to ChatGPT. They wanted to do it in our product, in just a few seconds."
Designing agentic AI involves unique challenges primarily related to management rather than interface design. Key questions include the agent's responsibilities, its autonomous decision-making capabilities, and when it should seek human input. A practical example illustrates this, where users desired a feature to upload job descriptions and receive salary ranges quickly, indicating a demand for integrated solutions within existing products rather than relying on external tools like ChatGPT.
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