Founders stuck on idea discovery — AI quiz + GPT filtering pipeline

Executive Summary

Many founders and solo builders stall at idea discovery: they waste weeks on vague brainstorming, suffer from noisy feedback, and lack a reproducible way to prioritize market-fit concepts. That problem affects roughly 1.5 million early-stage startups, which together spend about $12,000 per year on idea validation, tools and mentorship — a roughly $18.0B addressable market. You could build a guided AI quiz that captures a founder’s skills, constraints, customer archetypes and success metrics, then feed structured answers into a multi-stage GPT filtering pipeline that generates, scores and ranks 5–10 candidate ideas by market size, technical feasibility, time-to-MVP and monetization path. The product would produce investor- and builder-ready 1‑pagers, prioritized validation experiments, and turnkey no‑code prototype templates, and optionally surface human expert reviews for high-intent customers. This market is unusually attractive right now because LLM commoditization has raised generative quality to the point where ideation workflows can be productized, the Micro‑SaaS boom has increased demand for fast, low-capex ideas, and platformization (no-code, marketplaces, APIs) shortens time‑to‑MVP; the concept earns a market score of 92/100 and revenue potential of 88/100 in preliminary assessment. To stand out you’ll need more than raw GPT outputs: combine structured input (the quiz) to reduce prompt noise, deterministic scoring and evidence-based filters to avoid fanciful ideas, integrations with no‑code builders and a human-in-the-loop validation marketplace to raise credibility. Strengths are scalability and clear monetization levers, but challenges include medium competition, the risk of commoditizing ideas, maintaining output quality, converting users into recurring customers, and legal/IP ambiguity around generated concepts.