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 do stacked Black Friday discounts quietly ship orders below cost?

An automatic collection discount, an emailed BFCM code and a free shipping threshold all applied to the same carts, the store shipped orders at a loss, and nobody noticed until reconciliation weeks later because nothing flags a margin-negative order at checkout.

Category: Marketing, Sales & CRM · Trend: Agents · Opportunity score: 8.0 / 10

What is the “Why do stacked Black Friday discounts quietly ship orders below cost?” problem in 2026?

Who has this problem?

Small e-commerce owners and marketers planning Black Friday and Cyber Monday promotions.

Recorded source context

Dataset source note: On a handful of carts all three landed at once and we shipped orders below cost.

This note may summarize the referenced material rather than quote it verbatim. Source label: Shopify Community thread asking what broke in stores last BFCM, 21 September 2026, 24 posts. (primary source).

Existing players in this space

Shopify discount combinations settings: Control which discounts may combine, with no view of what that does to margin.
Discount Ninja: Promotion builder for complex offers, not a margin simulator.
Manual test orders: The advice in the thread, which covers only the carts someone thinks to try.

What existing players are missing

A pre-launch promo checker that reads every active discount, code and shipping rule, simulates realistic carts against product costs, lists the combinations that go margin-negative, and watches live orders for the same pattern during the sale.

How Real Problem AI scores this opportunity

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

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

How to build a solution: stack hints

Shopify discounts and orders API
Cart combination simulation
LLM explanation of risky rule interactions
Live order margin alerts