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 does every Common App teacher recommendation request feel like begging four times for the same letter?

Seniors applying to 12 colleges chase two teachers across Naviance, Common App, SlideRoom, and Coalition for the same letter, with no shared status view and no polite way to nudge.

Category: EdTech · Trend: Agents · Opportunity score: 8.5 / 10

What is the “Why does every Common App teacher recommendation request feel like begging four times for the same letter?” problem in 2026?

Seniors applying to 12 colleges chase two teachers across Naviance, Common App, SlideRoom, and Coalition for the same letter, with no shared status view and no polite way to nudge.

Who has this problem?

High school senior applying to 8 to 15 colleges, or the AP teacher writing 40 recs.

Evidence this problem is real

“My AP Lit teacher said yes in September. It is now December 28 and I still do not know if she submitted to Common App, Coalition, or the UC system. Naviance says submitted, Common App says pending, she stopped replying three weeks ago. UMich deadline is in 4 days.”

Sourced from r/ApplyingToCollege and College Confidential threads on rec letter chaos.

Existing players in this space

Naviance — School-side tool, no cross-platform sync, status often stale.
Common App teacher portal — Only shows Common App submissions.
SCOIR — Replacement for Naviance, same single-platform blindness.

What existing players are missing

An agent that logs into all four portals as the student, reconciles submission status per teacher per school, drafts polite tone-matched nudge emails, and gives counselors a single dashboard 72 hours before each deadline.

How Real Problem AI scores this opportunity

Aggregate score: 8.5 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Browser agent for Naviance, Common App, Coalition, SCOIR
LLM for tone-matched nudge drafting
Deadline parser across application portals
Multi-tenant student plus parent view