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 do I need a lawyer to read my own auto policy before I file a claim?

Drivers don't know what their policy actually covers (rental? OEM parts? diminished value?) until the adjuster says no.

Category: Automotive & Mobility · Trend: LLM · Opportunity score: 8.2 / 10

What is the “Why do I need a lawyer to read my own auto policy before I file a claim?” problem in 2026?

Drivers don't know what their policy actually covers (rental? OEM parts? diminished value?) until the adjuster says no.

Who has this problem?

Policyholders at the moment of a loss, too late.

Recorded source context

Dataset source note: Found out after the accident I had aftermarket-parts coverage but no diminished-value clause in NC. Lost $2,800 on resale.

This note may summarize the referenced material rather than quote it verbatim. Source label: r/Insurance, r/personalfinance, App Store reviews of Allstate/Progressive..

Existing players in this space

Insurify
The Zebra
Policygenius (all shopping
not policy comprehension)

What existing players are missing

Upload your declarations page; ask plain English questions ("if I hit a deer in Ohio, do I get a rental?"); get a state-law-aware answer with citation to the policy section, plus a "weak spots vs. peers" diff.

How Real Problem AI scores this opportunity

Aggregate score: 8.2 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Long-context LLM over policy PDFs
State insurance-code retrieval
Carrier-form templates (ISO standard)
Diff-vs-benchmark comparator

Why this problem is archived

Swapped out in AI-tool-builder content refresh (2026-08-26): generic vertical problem replaced by a more current, builder-relevant one.