Prioritize features by user desirability and technical feasibility. Identify MLP features. Uncover hidden assumptions about user needs and team capabilities. Encourage productive discussions on feature positioning.

A prioritized feature list. A visual representation of features on a lovability vs. viability matrix. A shared understanding of user needs and technical constraints. Documented assumptions about feature desirability and feasibility.

This works best with user research; don't guess at lovability. Even brief customer conversations help. Expect debate. If everyone agrees too easily, play devil's advocate: "What if users don't care?" or "What if this is harder than we think?" Keep momentum. Good-enough placement is fine. Ask: "What assumption causes different views?" If someone says "it depends," push for specifics. Teams often hedge, so push for relative positioning: "Compared to Feature X, is this more or less lovable?" The middle ground is where insights often stall. If uncertain, mark it. Engineers might overstate viability, so ask: "What's achievable with our resources?" Distinguish "hard to build" from "we don't know how." Product people might overstate lovability, so ask: "What evidence do we have?" Reference user research. If features cluster, break them down: "Social sharing" becomes "share to Twitter," etc. Redirect dominant voices; silent plotting can help. Teams often treat viability as binary, so remind them it includes effort, risk, and unknowns. Teams avoid cutting features, so force choices. For better results: have individuals plot silently before discussion, create matrices for different user personas, and use sticky note size to show confidence. If you lack user research, stop and get some. If features are poorly defined, clarify them. If politics block honesty, regroup. Good signs: debate, user feedback, assumption questions, changed minds. Bad signs: one person dominates, defaulting to the middle, no movement, avoiding discussion. The real value is discovering unwanted features, recognizing missing evidence, aligning on "viable," and deprioritizing invested work. Immediately after: photograph the matrix, share insights, and list assumptions. Within one week: translate features into user stories, create a research plan, and communicate decisions. Within one month: validate assumptions and re-run if new info emerges. Common mistakes: plotting without definitions, letting one voice dominate, rushing placement, making viability binary, wishful thinking, perfect placement paralysis, not deprioritizing, and forgetting assumptions. Don't treat the matrix as permanent truth.