Many solo builders, indie makers and early founders waste weeks or months starting features before they know whether an idea has real demand, and this problem affects an estimated 50 million potential builders who could benefit from faster go/no-go signals. Existing routes—manual market research, long customer interviews, or expensive consultant reports—are slow and inconsistent, leaving builders to guess on TAM, competitors and likely traction. A practical product would be a quiz-driven pre-build validation app that converts 8–12 targeted answers into a concise, evidence-backed report in under 10 minutes: competitor landscape, rough TAM estimate, top 3 MVP features, monetization sensitivity, and a unified confidence score. Built from an LLM-guided questionnaire, automated web scans and simple heuristics, it could offer a free tier for exploration and a $120/year paid plan, addressing a $6.0B market (50M builders × $120/year) with a revenue potential score of 78/100 and an overall market attractiveness of 95/100. This market is unusually receptive right now because the indie-maker surge and maturing no-code tooling compress build cycles, while generative AI makes low-cost automated analysis credible and scalable. To stand out you’d need transparent assumptions, reproducible sources (live scraping or linked citations), a defensible question tree validated with A/B testing, and a smooth path from insight to prototype; strengths are speed, low price and iterative utility, while clear challenges include managing data quality, limiting misleading LLM outputs, and competing in a medium-competition field where trust and conversion funnels must be earned.