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 is Amazon sitting on $2,000 of my lost inventory and only refunding pennies on the dollar?

FBA sellers lose $1,500 to $3,000 a year on units Amazon lost or damaged, and since the Nov 2025 policy change reimbursements pay manufacturing cost, not retail, so even filed claims recover a fraction.

Category: E-commerce & Retail · Trend: Agents · Opportunity score: 7.3 / 10

What is the “Why is Amazon sitting on $2,000 of my lost inventory and only refunding pennies on the dollar?” problem in 2026?

Who has this problem?

Amazon FBA sellers doing their own operations without an audit team.

Evidence this problem is real

“Most sellers don't realize they're leaving $1,500-$3,000 per year unclaimed because they don't know what to look for or how to file properly.”

Sourced from NovaData 'Amazon FBA Reimbursement Guide 2026'; seller reports on the Nov 15 2025 manufacturing-cost policy. (link)

Existing players in this space

GETIDA / Refully: Take a cut, focused on filing, weak on the new cost-basis math
Amazon auto-reimbursement: Now pays manufacturing cost, silently underpays
Manual spreadsheet audits: 18-month window, evidence rots, sellers give up

What existing players are missing

An agent that reconciles inventory ledgers, reimbursement reports, and settlement data continuously, flags every lost, damaged, and mis-valued unit inside the 18-month window, and files with the cost evidence needed to fight the manufacturing-cost lowball.

How Real Problem AI scores this opportunity

Aggregate score: 7.3 / 10. Four-axis rubric:

Problem severity: 7 / 10
AI feasibility today: 8 / 10
Market signal: 8 / 10
Competition gap: 6 / 10

How to build a solution: stack hints

SP-API inventory and settlement ingestion
Discrepancy detection across ledgers
Cost-basis evidence assembler
Automated case filing and tracking

Why this problem is archived

Trimmed to 100-cap (lowest opportunity_score)