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 can an AI coding agent delete my production database in 9 seconds?

Cursor, Claude Code and Devin run with whatever shell + DB credentials the developer happens to have; one misread prompt = TRUNCATE on prod. There's no permission layer between "agent suggesting code" and "agent executing destructive command on live infra".

Category: Others · Trend: Agents · Opportunity score: 9.0 / 10

What is the “Why can an AI coding agent delete my production database in 9 seconds?” problem in 2026?

Who has this problem?

Solo founders, indie hackers and small engineering teams using AI coding agents against any environment more permissive than a dev sandbox.

Evidence this problem is real

“Asked Cursor to clean up an obsolete migration. It ran DROP TABLE on prod. Nine seconds. Two months of customer data gone. The CLI showed a 200 OK.”

Sourced from r/programming, r/cscareerquestions, Indie Hackers thread on PocketOS Cursor incident (May 2026), HN front-page. (link)

Existing players in this space

AWS IAM / GCP IAM — Coarse-grained; agents need per-tool, per-environment, per-blast-radius scopes
1Password Secrets Automation — Stores secrets but doesn't gate agent execution by intent
Cursor Privacy Mode — Stops Cursor sending code to model; does nothing about destructive-command authorisation
Doppler — Secrets manager; no command-classifier or human-in-the-loop gate

What existing players are missing

An agent-aware permission proxy: intercept shell/DB/API calls coming from an AI agent, classify by blast radius (read / soft-write / destructive), require a typed human confirmation for destructive operations against prod-tagged environments. Plus immutable audit trail of every command the agent attempted.

How Real Problem AI scores this opportunity

Aggregate score: 9.0 / 10. Four-axis rubric:

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

How to build a solution: stack hints

MCP-compatible proxy server intercepting tool calls
LLM-judge classifier for command blast radius
Per-environment policy DSL (prod/staging/dev)
Slack/email confirmation flow for destructive operations
Append-only audit log of every agent action