Instant AI MVP scoping + tech-stack generation

Founders, solo makers, micro‑agencies and small engineering teams routinely spend days to weeks and often thousands to tens of thousands of dollars on ambiguous MVP scoping, with poor handoffs and rework when requirements hit engineering. This problem is especially acute for the estimated 20 million early‑stage makers, agencies and dev teams who lack repeatable processes or senior product/engineering bandwidth. You could build an Instant AI MVP scoping product that turns a short brief or URL into a prioritized spec, acceptance criteria, task‑level backlog with effort estimates, suggested tech stack and a scaffolded starter repo, plus one‑click exports to GitHub, Jira, Figma and CI templates. Offer a human‑in‑the‑loop validation tier, vertical templates (SaaS, marketplace, e‑commerce), and pricing aligned to self‑serve and small‑team plans with a $600 ARR anchor for buying behavior. This market looks attractive now: a $12.0B addressable market (20M × $600 ARR), a Market Score of 92/100 and strong tailwinds from AI‑assisted product development, an indie/startup surge and demand for API‑first integrations. Technically, higher‑quality LLMs and mature integration tooling make automated, exportable scopes feasible today in ways they weren’t 18 months ago. To stand out, prioritize trust and measurable outcomes: deterministic templates, testable acceptance criteria, automated scaffolding plus verification hooks (unit tests, linting) and transparent effort math, backed by paid human reviewers and a marketplace for vetted engineers. Be honest about the challenges—LLM hallucinations, integration maintenance and earning agency trust—and plan to invest in continuous evaluation, security options (VPC/on‑prem) and strong partner integrations; if you can reliably reduce scoping turnaround from days to under an hour for simple projects, this can be a compelling, low‑competition commercial play.