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 cancelling a subscription still take fifteen minutes after click-to-cancel?

FTC click-to-cancel partially survived court challenges but enforcement is uneven. Half the SaaS and DTC brands still bury cancel inside a chat widget that opens at 9am ET. Consumers eat the next charge.

Category: FinTech · Trend: AI · Opportunity score: 7.8 / 10

What is the “Why does cancelling a subscription still take fifteen minutes after click-to-cancel?” problem in 2026?

Who has this problem?

US consumers tracking 20+ recurring charges; small business operators auditing software spend.

Evidence this problem is real

“My gym makes me cancel in person. My SaaS makes me schedule a Calendly. Rocket Money cancels three apps and gives up on the rest. I'm paying for two streaming services I forgot exist.”

Sourced from FTC Click-to-Cancel rule history (vacated July 2025, partial reinstatement 2026), Consumer Reports subscription-trap reporting. (link)

Existing players in this space

Rocket Money — Cancels easy ones, hands the hard ones back to the user
Trim — Negotiation focus, cancel as a bolt-on, often slow
DoNotPay — Reputation hit after FTC settlement, scope shrinking

What existing players are missing

An AI agent that actually completes the cancellation: dials the retention line on speaker, fills the cancel form, screen-records the confirmation, and files an FTC complaint if blocked. Charges only on successful cancel with receipt.

How Real Problem AI scores this opportunity

Aggregate score: 7.8 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Voice agent for retention calls with a transferable consent log
Browser-use agent for cancel flows behind login walls
Receipt verification via bank-feed disappearance
Auto-generated FTC and state AG complaint drafts