What is Real Problem AI?

Real Problem AI is a curated directory of 100 real problems worth building an AI startup around. Each problem is scored honestly on severity, AI feasibility, market signal, and competition gap. We're for builders looking for what to build, not for ethics debates about AI.

What is the difference between Real Problem AI and AI ethics or AI risks indexes?

Real Problem AI catalogues problems AI can solve — productive, commercial opportunities for builders. AI ethics indexes catalogue problems with AI itself (bias, environmental cost, copyright, consciousness). Different intent, different audience: founders and indie hackers vs researchers and policy folks.

What should I build with AI in 2026?

Look for problems with high severity (it costs people hours, sleep, or revenue every week), high AI feasibility (LLMs, vision or voice are great at this today), strong market signal (Reddit threads + willingness to pay), and a clear competition gap (incumbents miss the same obvious thing). Real Problem AI scores 100 such problems for you on those four axes.

Where do Real Problem AI's startup ideas come from?

From three sources, scanned each cycle: 1) Reddit threads where people describe a real friction in their own words, 2) podcasts and talks of founders young builders trust (Nikhil Kamath, Aman Gupta, Ankur Warikoo, Raj Shamani, Andrej Karpathy, Greg Isenberg), and 3) a continuous 1,000+ source scan covering forums, app store reviews, regulator filings, and field interviews.

Is Real Problem AI free?

Yes. Browsing every problem, opening every score breakdown, raising your hand on a co-founder match, and the founder vault are all free. There is no paywall.

How is each problem scored?

Four axes, each 1-10, weighted: Problem Severity (30%), AI Feasibility (25%), Market Signal (25%), Competition Gap (20%). Weighted average is the Opportunity Score on each card. Only problems clearing 7.0+ make the live list.

Why does vibe-coding ship a prototype in an hour and a bug graveyard in a week?

v0, Lovable, Bolt and Replit Agent ship a working demo by Friday. By Wednesday the codebase is unmaintainable, untested, and silently shipping prod bugs.

Category: AI / Agents · Trend: Agents · Opportunity score: 8.1 / 10

What is the “Why does vibe-coding ship a prototype in an hour and a bug graveyard in a week?” problem in 2026?

v0, Lovable, Bolt and Replit Agent ship a working demo by Friday. By Wednesday the codebase is unmaintainable, untested, and silently shipping prod bugs.

Who has this problem?

Solo founders and product designers shipping v0/Lovable/Bolt apps to real users.

Recorded source context

Dataset source note: I shipped in 4 hours. By week two I had 30 paying users and I couldn't fix a payment bug because the codebase is 14 files of AI spaghetti.

This note may summarize the referenced material rather than quote it verbatim. Source label: r/SideProject and r/SaaS "my Lovable app is breaking and I can't fix it" threads (April-May 2026), IndieHackers vibe-coding regret posts, Hacker News debates on AI-generated codebases..

Existing players in this space

v0 / Lovable / Bolt: Build forward, not refactor backward
Cursor / Claude Code: Great at edits but assume you already understand the code

What existing players are missing

A "vibe-debt cleanup" agent: ingest a vibe-coded repo, identify dead code, missing tests, security holes, and ship a clean refactor that a human can own. Plus a continuous health score so founders know when to call in a senior engineer.

How Real Problem AI scores this opportunity

Aggregate score: 8.1 / 10. Four-axis rubric:

Problem severity: 8 / 10
AI feasibility today: 8 / 10
Market signal: 9 / 10
Competition gap: 7 / 10

How to build a solution: stack hints

AST-level repo analysis
Test generation with mutation testing
Security scanner pipeline (Semgrep, gitleaks)
PR-driven refactor agent on Claude Code or Cursor