What is Real Problem AI?

Real Problem AI is a curated directory of 200+ 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 200+ 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't a tech employee model an RSU sell-to-cover shortfall before the vest hits?

Fidelity and E*Trade withhold a flat 22 percent on RSU vests, but the employee is in the 35 percent bracket, creating a surprise April tax bill of $40k+ that nothing warns about in real time.

Category: FinTech · Trend: LLM · Opportunity score: 8.3 / 10

What is the “Why can't a tech employee model an RSU sell-to-cover shortfall before the vest hits?” problem in 2026?

Fidelity and E*Trade withhold a flat 22 percent on RSU vests, but the employee is in the 35 percent bracket, creating a surprise April tax bill of $40k+ that nothing warns about in real time.

Who has this problem?

Senior IC at FAANG or post-IPO startup with $300k+ RSU vest events.

Evidence this problem is real

“My March vest dropped 1,200 shares, E*Trade sold 264 for taxes at 22 percent, and my CPA just told me I'm short $38k because my real bracket is 35. Why didn't anyone tell me to sell more on vest day?”

Sourced from r/fatFIRE, Blind, r/personalfinance recurring "I owe $50k in April" threads.

Existing players in this space

Carta — Models grants pre-vest but not post-vest withholding gap.
Secfi — Focused on pre-IPO ISO/NSO exercise, not public RSU.
Compound — Shut down 2023.

What existing players are missing

A live agent that watches the brokerage vest event, computes marginal-bracket shortfall against YTD W-2 withholding, and recommends or executes a same-day supplemental share sale to plug the gap.

How Real Problem AI scores this opportunity

Aggregate score: 8.3 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Plaid plus E*Trade and Fidelity Stock Plan account sync
LLM bracket projector pulling YTD paystubs
Estimated payment scheduler with EFTPS integration
Wash-sale and AMT cross-check