Most AI agent projects fail not because of bad code or weak models — they fail because teams aim at the wrong part of the workflow. AI strategist Nate B. Jones argues that real work is only about 2.5% high-judgment "core" decisions, while the other 97.5% is mechanical edge work: data prep, QA, synthesis, handoffs, and packaging. Teams that try to automate the core first stall out fast. Teams that start with the edges — the boring stuff surrounding the valuable work — ship results in days, build organizational trust, and create a proven path toward eventually tackling the core. It's the same principle behind Agile: start small, deliver value fast, and expand from a foundation of demonstrated success. The fix isn't better AI. It's smarter strategy about where you start.