How to validate a startup idea before you write any code
Short answer: validate the problem before the product. Score the idea on five axes (severity, AI feasibility, market signal, competition gap, defensibility), use the top competitors yourself, then find five named people who confirm the problem in their own words. Only build if it scores 7 or more on every axis and three of the five confirm.
The most expensive thing a founder builds is the wrong product. Not because of the engineering cost, but because of the twelve months you cannot get back. Validation done well costs a weekend. Validation skipped costs a year.
This essay covers the four axes we score every problem in our directory of validated startup ideas on, a fifth axis worth adding for AI products, and the weekend workflow that turns a vague idea into a go/no-go decision before you commit a single sprint.
The 5-axis rubric
Each axis is scored 1 to 10. A score of 7+ on all five is rare; that is the bar for "build it." Average around 6 is "interesting, keep looking." Below 5 on any axis is a kill signal. For comparison, a problem has to clear 7.0 out of 10 on our weighted four-axis score to make the live list at all, and only the top 100 stay live (how the scoring works).
Axis 1: problem severity
How much does this hurt? Measure in hours per week or dollars per month, not in subjective complaint volume. A 30-minute weekly frustration is a 4. A $300 surprise charge a month is a 7. A six-month sales cycle stalled by a single workflow is a 9.
The trap: founders confuse the volume of complaint with the severity of pain. A Reddit thread with thousands of upvotes can describe a mild annoyance. Look for the language of urgency: "I had to," "I lost," "I cancelled."
Axis 2: AI feasibility today
Not "is AI plausibly going to solve this someday." Can a competent engineer ship a working v1 in 8 to 12 weeks with current models? Categorising bank transactions is a 9. Diagnosing a rare disease from a photo is a 4. Reading a legal redline is an 8.
The trap: scoring on next year's models. You are not building for a model that has not shipped; you are building for the model you can call today.
Axis 3: market signal
How many real people credibly experience this problem? "Tech founders" is a 5. "Anyone with a credit card" is a 9. Read the platform numbers, not the post count: Sensor Tower for app markets (it acquired data.ai, formerly App Annie, in March 2024), the US Census Bureau's business statistics, and the Bureau of Labor Statistics for occupations. These are dull and they are authoritative.
Axis 4: competition gap
How wide is the space between what the leading existing solution does and what the user actually wants? Big gap is good. If a category leader already does 80% of the job, the gap is a 3 and you are entering a re-skin fight you will lose.
To score this honestly, install the top three competitors and use them on a real task. Note what frustrated you in the first 20 minutes. Those frustrations are the gap. For every problem in our directory, the tools page shows what already exists and the gap it leaves.
Axis 5: defensibility (the axis we add for AI products)
What stops a competitor with twice your funding from copying you in six weeks? This is where AI-era validation diverges from classic SaaS. Possible moats include:
- Proprietary data. You have a corpus nobody else has access to.
- Workflow lock-in. You are inside a workflow that costs the user real switching pain.
- Distribution. You have a community or audience competitors cannot rent.
- Speed of iteration. You can ship faster than a bigger team can decide.
"We use Claude" is not a moat. Neither is "we fine-tuned on internal data" unless that data is genuinely hard to acquire.
The weekend workflow
Friday evening: collect
Pick one habitat (subreddit, IndieHackers community, HN "Ask HN" archive). Read 50 posts. Note every concrete complaint with the user's exact words. Goal: 8 to 12 candidate problems. Our guide on how to find startup ideas from real problems lists habitats worth reading.
Saturday morning: score
Run each candidate through the 5-axis rubric. Be honest. Anything below 5 on any axis falls off the list. You should have 2 to 4 candidates left.
A quick desk check helps here. Build or Skip takes a one-line description of the problem and counts how many Show HN launches already exist, how much Ask HN demand there was in the last 12 months, and whether it matches a problem in our catalogue, then returns build, maybe or skip. It is a prototype and a first filter, not the decision.
Saturday afternoon: install competitors
For each remaining candidate, install the top 2 to 3 existing solutions and use them on a real task for 30 minutes each. This is where the competition-gap score gets refined into a number you trust.
Sunday morning: five-name test
For your top candidate, find five real people with this problem. Not five hypothetical buyers. Five named humans with email addresses. Direct messages, IndieHackers, X, LinkedIn, friends of friends.
Ask about the last time the problem happened and what they did about it. Avoid "would you use this?"; people are polite, and politeness is not demand.
Sunday evening: decide
You have one candidate, five names and a 5-axis score. If the score is 7+ across all five axes and three of the five names confirm the problem in the next week, you build. Otherwise, you go back to Friday with a different habitat.
Validation signals that count, and ones that do not
| Counts | Does not count |
|---|---|
| A stranger describes the problem before you do | A friend says it is a great idea |
| They already pay for a workaround or spend hours on it | They say they "would definitely use it" |
| A pre-order, paid pilot or letter of intent | Likes, upvotes or waitlist sign-ups alone |
| They ask when they can try it | They ask you to "keep them posted" |
What this saves you from
Three failure patterns the rubric catches early:
The interesting-but-tiny market. AI tooling for music producers is interesting. The market may be too small to support a venture-backed business. The rubric flags this on axis 3.
The valuable-but-saturated market. AI for sales emails is valuable, and many funded players already sell it. Axis 4 flags this immediately.
The valuable-but-not-yet-feasible market. AI medical diagnosis sounds high-impact. Reality is regulatory and feasibility blockers that fail axis 2. Founders can lose a long time learning this the slow way.
The rubric is boring. That is the point: it makes you write down why you believe each number.
Questions founders ask
How do you validate a startup idea without spending money?
Read 50 to 100 posts where your target users complain, score the problem on five axes, try the top competitors yourself, and message people until five named strangers confirm the problem in their own words. None of that costs money; it costs a weekend.
How many customer interviews do you need to validate an idea?
Five conversations are enough to tell whether a problem is real, if at least three people describe it in the words you read online. Willingness to pay needs more evidence: a pre-order, a paid pilot or a letter of intent beats any number of compliments.
Can AI validate a startup idea?
AI can speed up the desk research: finding complaints, counting existing launches and summarising competitors. It cannot confirm that real buyers will pay. Use an AI check as a first filter, then talk to people before you write code. If you work in Claude Code, Cursor or VS Code, our MCP server lets your agent search the scored problems and check demand from the editor.
See 100 startup ideas from real problems, scored on the four core axes, with sources where available, personas and the missing wedge for each.
Browse the directory