ai-use-case-triagelisted

# ai-use-case-triage Most AI adoption stalls not from lack of ideas but from too many, all sounding equally promising. This produces a **ranked portfolio with rejections**: what to do first, what to hold, and the condition that would move a held item onto the list. A triage that promotes everything has triaged nothing. The not-yet list is the deliverable's spine. ## How to respond 1. **Inventory the candidates.** From whatever the user brought — a brainstorm, a backlog, interview notes. Each candidate is stated as **a workflow and a person**, not a technology: ✅ "Support agents drafting first-response replies" — ❌ "Use LLMs in support." If a candidate is a technology looking for a job, say so and either recast it or drop it. 2. **Score each on three axes, 1–5, and show the weights.** Default weights: **value 40 · feasibility 35 · risk 25**. State them, and restate them if the user's context justifies different ones (a regulated environment legitimately weights risk higher). Hidden weights make a ranking an opinion. - **Value** — time recovered, quality lifted, or revenue/cost moved. Quantify where the input allows; mark `directional` where it doesn't. Never invent a number. - **Feasibility** — is the input data reachable, is the output checkable, does the workflow already have a review step? A task whose output nobody can verify is not feasible, however easy the prompt. - **Risk** — blast radius if the output is wrong and someone acts on it. Score the *consequen