Agentic Problem Structuring: Cases for How Human-AI Judgment Transforms Complex Problems into Action

by Anchao Chi

When AI can generate summaries, recommendations, and polished language in seconds, the real challenge of modern work is no longer output alone. The harder question is how to turn that output into decisions that people, teams, and institutions can actually stand behind. In Agentic Problem Structuring, Chi Anchao argues that the missing capability of the agentic age is not simply better prompting or more automation, but a disciplined way of transforming messy, high-stakes problems into bounded human-AI workflows for inquiry, decomposition, delegation, verification, judgment, and action.

Through five applied cases spanning market entry, hiring, research, editorial judgment, and operating governance, this book shows how AI-supported work can become not only faster, but more reliable, inspectable, and decision-ready. Rather than treating AI as either a convenience tool or a replacement for human judgment, Chi offers a practical method for making complex work clarifying the real decision, designing the workflow, assigning bounded roles, preserving intermediate artifacts, and ensuring that synthesis does not outrun responsibility. Written for researchers, analysts, managers, policy professionals, institutional leaders, editors, and advanced students, Agentic Problem Structuring is a book for readers who want more than fluent output. It is a method for making human-AI collaboration worthy of trust.

227 pages, Kindle Edition

Published March 29, 2026