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.

We got breached through 200+ APIs in production that nobody knew existed.

Teams cannot see their own live attack surface, so undocumented and forgotten APIs sit exposed in production until an attacker finds them first.

Category: Others · Trend: Agents · Opportunity score: 8.1 / 10

What is the “We got breached through 200+ APIs in production that nobody knew existed.” problem in 2026?

Teams cannot see their own live attack surface, so undocumented and forgotten APIs sit exposed in production until an attacker finds them first.

Who has this problem?

Security and platform engineers responsible for production infrastructure.

Recorded source context

Dataset source note: During the forensics they found over 200 undocumented APIs in prod that nobody knew existed, including me, and I am supposedly the one who knows our infrastructure.

This note may summarize the referenced material rather than quote it verbatim. Source label: r/sysadmin, 2026: a sysadmin whose post-breach forensics found 200+ undocumented production APIs. (reference).

Existing players in this space

API gateways (Kong, Apigee): Manage the APIs you registered, blind to the ones you did not
Traditional ASM / scanners: Periodic scans, miss internal and ephemeral endpoints
Manual inventory in a spreadsheet: Stale the day it is written

What existing players are missing

Continuous shadow-API and asset discovery that watches real traffic and code to surface every live endpoint, owner, and auth gap, so the attack surface is known before an attacker maps it.

How Real Problem AI scores this opportunity

Aggregate score: 8.1 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Traffic and log-based endpoint discovery
Code and repo scanning for routes
Ownership and auth-gap mapping
Continuous diff and alerting

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.