What should I build? A founder's guide to finding real problems

The single most common question from a first-time founder in 2026 is some version of: "I want to build something. What should I build?" The honest answer is that "what to build" is the wrong question. The right question is: "where do I look for problems people are already paying to solve, badly?"

This essay is the method we used to assemble 200+ evidence-backed startup ideas. You can run it in a weekend and end up with three or four strong candidates of your own.

Step 1: pick a habitat, not a topic

Most "what to build" guides tell you to pick a topic you care about. That advice fails because it pushes you toward your own assumptions. Pick a habitat instead: a place online where a specific group of people complain in long, specific paragraphs about specific problems.

A good habitat has three properties:

• The complaints are concrete. "I hate my landlord" is useless. "My landlord auto-charged me $50/month for renters insurance I already had" is gold.
• The complaints repeat. One angry post is anecdote. Forty similar posts in twelve months is a pattern.
• The complainers can afford to pay something. Subreddits for low-income high-school students are full of pain. They are not a market.

Our highest-yield habitats: r/personalfinance, r/smallbusiness, r/Frugal, r/ecommerce, r/sales, r/k12sysadmin, r/Teachers, r/legaladvice, r/Plumbing, r/medicine, r/Cardiology, r/talesfromtechsupport, IndieHackers, Hacker News "Ask HN: what do you wish existed", App Store one-star reviews of category leaders, Trustpilot for legacy software.

Step 2: read sideways, not down

The trap when you sit on a subreddit is to read top-of-feed: the trending posts. That is recency bias. The signal lives in the long tail of posts with five comments and zero upvotes, where someone described a real problem precisely enough that no one bothered to react.

For each habitat, sort by "new" and read fifty posts. Then sort by "top, all time" and read another fifty. The overlap is your candidate set.

Step 3: score on four axes

Every candidate problem gets four numbers, each 1-10. We weight them equally into an opportunity score.

1. Problem severity. How much pain does this cause, in hours or dollars, to the affected person? A weekly 30-minute frustration is a 4. A monthly $300 surprise charge is a 7. A six-month lost-deal cycle for a small business is a 9.
2. AI feasibility. How well-suited is the current state of AI to solving this? Categorising bank transactions is a 9. Diagnosing a rare disease from a photo is a 4.
3. Market signal. How many people credibly experience this? "Tech founders" is a 5. "Anyone with a credit card" is a 9. Read the platform numbers, not just the post count.
4. Competition gap. How wide is the space between the leading existing solution and what the user actually wants? Big gap is good. If a category leader already does 80% of what users want, the gap is a 3.

Step 4: stress-test with the "five names" rule

Before you commit to building anything, find five real people who have this problem. Not five hypothetical buyers. Five named people with email addresses, who agree to talk to you for fifteen minutes.

If you cannot find five people in two weeks, the habitat was noisier than the market is real. Drop the problem and pick the next one on your scored list.

If you find five and the first three calls confirm the problem in the exact words you read online, the problem is real. The next two calls should be about willingness to pay, not "is this a problem."

Step 5: pick the wedge, not the platform

A common mistake among first-time founders is to pitch the eventual platform. "An AI ops layer for small healthcare practices." That is the destination. The wedge is one specific painful workflow.

For each scored problem, ask: what is the smallest, sharpest thing I can build in eight weeks that takes one painful workflow from five hours to fifteen minutes? That is the wedge. The platform is what you build after the wedge has paying customers.

The three traps to avoid

Building from your own life. Your own problems are not unique. They are usually problems shared with you and your three closest friends. Three friends is not a market.

Conflating "interesting" with "valuable." AI for art curation is interesting. AI for sales-tax tracking is valuable. The interesting problems are crowded. The valuable problems are not.

Mistaking platform shifts for new markets. "ChatGPT exists, therefore X needs to be rebuilt" is a thesis, not a problem. The problem still has to be the problem first. The new platform just changes the feasibility score.