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 browser agent fail on the cookie banner every single time?

Computer Use, Operator, and Claude in Chrome trip on the same mundane web furniture: cookie banners, captchas, modal popups, hover menus. Reliability hovers below 50%.

Category: AI / Agents · Trend: Agents · Opportunity score: 7.6 / 10

What is the “Why does my browser agent fail on the cookie banner every single time?” problem in 2026?

Computer Use, Operator, and Claude in Chrome trip on the same mundane web furniture: cookie banners, captchas, modal popups, hover menus. Reliability hovers below 50%.

Who has this problem?

Devs building agent automations (Browse AI, Skyvern, custom Playwright + Claude).

Recorded source context

Dataset source note: Ran the same booking flow 20 times. 9 succeeded. The cookie banner alone killed 4. The captcha killed 3. The rest were modal stack-ups.

This note may summarize the referenced material rather than quote it verbatim. Source label: r/ChatGPT Operator failure videos, Browse AI customer support tickets, Anthropic Computer Use cookbook issues..

Existing players in this space

Skyvern: Open source, still trips on banners
Browse AI: Templates, not general
Operator / Computer Use: General, low reliability

What existing players are missing

A "web furniture" pre-handler: detect and resolve banners, modals, captchas before the agent thinks. Plus a flake-replay dashboard that surfaces the top 10 failures across the user's workflows and patches them.

How Real Problem AI scores this opportunity

Aggregate score: 7.6 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Vision + DOM hybrid banner detector
Captcha solver routing (humans, services)
Workflow replay + auto-patch
Agent reliability scorecard