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 does my AI agent have the same production access as my senior engineer but none of the judgment?

Agents are handed static god-mode API keys and standing IAM roles because scoped, short-lived, per-task credentials for non-human identities barely exist yet.

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

What is the “Why does my AI agent have the same production access as my senior engineer but none of the judgment?” problem in 2026?

Agents are handed static god-mode API keys and standing IAM roles because scoped, short-lived, per-task credentials for non-human identities barely exist yet.

Who has this problem?

Platform and security engineers putting agents next to live infrastructure.

Evidence this problem is real

“Your senior engineer has admin access but uses it carefully. Your AI agent has the same access and uses it indiscriminately.”

Sourced from Hacker News discussion 'AI agent has more production access than your senior engineers' (item 46966307); emerging agent-auth tools (Pomerium, AgentVisa). (link)

Existing players in this space

OAuth / API keys: All-or-nothing scopes, long-lived, built for humans and apps
Pomerium / AgentVisa (early): Just-in-time agent identity, still nascent and infra-heavy
Vault / secrets managers: Store the key, do not constrain how an agent uses it

What existing players are missing

A least-privilege broker that issues short-lived, task-scoped credentials to an agent, enforces per-operation approval on destructive actions, and gives one audit trail of what every non-human identity actually touched. The agent must not be able to widen its own scope.

How Real Problem AI scores this opportunity

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

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

How to build a solution: stack hints

Agent identity broker (work-visa style tokens)
Just-in-time scoped credential issuance
Policy engine immune to agent self-modification
Non-human-identity audit log