What is Real Problem AI?

Real Problem AI is a curated directory of 200+ 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 200+ 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 US student loan borrowers re-upload the same pay stubs every year just to recertify IDR?

Income-Driven Repayment recertification on studentaid.gov requires re-entering AGI, family size, and uploading pay stubs annually, and a single missed deadline jumps the borrower from $100 to $1,400 monthly.

Category: EdTech · Trend: Agents · Opportunity score: 9.0 / 10

What is the “Why do US student loan borrowers re-upload the same pay stubs every year just to recertify IDR?” problem in 2026?

Who has this problem?

US borrower on SAVE or PAYE, household income under $80k, missed recert at least once.

Evidence this problem is real

“I recertified IDR in November 2024. MOHELA processed it 4 months late. My payment jumped from $89 to $1,402 for three months because the IRS data tool 'could not verify' my AGI even though I uploaded the same 1040 they have. I had to call MOHELA 11 times.”

Sourced from r/StudentLoans threads on IDR recertification after the 2024 SAVE injunction.

Existing players in this space

studentaid.gov IDR portal — Does not remember prior submissions, no proactive reminders 60 days out.
Summer (meetsummer.com) — Decent reminders, does not actually file recertification or follow up with the servicer.
Servicer apps (MOHELA, Nelnet, EdFinancial) — Each different, none coordinate when loans were split mid-cycle.

What existing players are missing

A vault that stores pay stubs, IRS transcript, household info, and prior IDR plan, then auto-files recertification 75 days before deadline using borrower credentials, escalates servicer disputes with CFPB templates, and routes around SAVE-vs-PAYE rule changes.

How Real Problem AI scores this opportunity

Aggregate score: 9.0 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Browser agent for studentaid.gov and servicer portals
IRS Get Transcript API automation
CFPB complaint template generator
Court-ruling-aware plan recommender via LLM