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.

$1M revenue and I just paid tax penalties because I can't keep up with the bookkeeping.

Owner-operators past $1M revenue still run the books themselves in a once-a-year scramble, miss deadlines, and pay penalties because real bookkeeping help is either a cheap VA or an expensive firm with nothing useful in between.

Category: FinTech · Trend: Agents · Opportunity score: 8.0 / 10

What is the “$1M revenue and I just paid tax penalties because I can't keep up with the bookkeeping.” problem in 2026?

Who has this problem?

Owner-operators of $500k to $2M service businesses doing their own books.

Recorded source context

Dataset source note: I run a small IT services company, about $1M revenue, 5 employees. I have been doing the same chaotic thing every year and I just paid tax penalties because I can't keep up.

This note may summarize the referenced material rather than quote it verbatim. Source label: r/smallbusiness, 2026: the owner of a ~$1M IT services company who paid tax penalties from falling behind on the books. (reference).

Existing players in this space

QuickBooks: Records transactions, does not keep you current or warn on deadlines
Bookkeeping VAs / firms: Cheap-and-unreliable or expensive-and-slow, little in between
Doing it once a year: The scramble that caused the penalty

What existing players are missing

An always-current bookkeeping agent that categorizes transactions weekly, reconciles automatically, and pushes deadline and cash-set-aside alerts, so a busy owner never discovers they are behind at tax time.

How Real Problem AI scores this opportunity

Aggregate score: 8.0 / 10. Four-axis rubric:

Problem severity: 8 / 10
AI feasibility today: 7 / 10
Market signal: 9 / 10
Competition gap: 6 / 10

How to build a solution: stack hints

Bank and accounting feed ingestion
Continuous categorization and reconciliation
Deadline and tax-set-aside alerts
Owner-friendly weekly summary

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.