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 did one company end up with 2,000 vibe-coded apps in a few weeks and no idea what's in production?

Enterprises handing out free vibe-coding licenses are accumulating a decade's worth of custom-app tech debt in months, with no lifecycle tracking of which app is a prototype and which is live.

Category: AI / Agents · Trend: LLM · Opportunity score: 7.2 / 10

What is the “Why did one company end up with 2,000 vibe-coded apps in a few weeks and no idea what's in production?” problem in 2026?

Enterprises handing out free vibe-coding licenses are accumulating a decade's worth of custom-app tech debt in months, with no lifecycle tracking of which app is a prototype and which is live.

Who has this problem?

Enterprise IT and platform leads managing AI-assisted app sprawl.

Recorded source context

Dataset source note: We got a free vibe-coding license from one of the leading players, and I opened it up to my whole company. Within a couple of weeks we had close to 2,000 apps. Now I don't know what's in production and what's prototype... Whatever custom-app debt we collected over the last ten years, I think we'll collect again in three months.

This note may summarize the referenced material rather than quote it verbatim. Source label: The AI Sailor (Siva Surendira), 7 Oct 2025, citing a Fortune-500 CIO. (reference).

Existing players in this space

Manual app inventories: Can't keep pace with vibe-coding app creation rate.
Cloud asset management tools: Track infrastructure, not app provenance or prototype-vs-production status.

What existing players are missing

An AI-app lifecycle registry that auto-discovers vibe-coded apps as they're created, tags them by data access and privilege level, and flags which are still prototypes versus quietly serving real users.

How Real Problem AI scores this opportunity

Aggregate score: 7.2 / 10. Four-axis rubric:

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

How to build a solution: stack hints

App discovery/crawling agent
Data-access and privilege scanner
Lifecycle status classifier
Enterprise dashboard