Idea Validator

What It Does

Turns raw ideas into testable hypotheses. Instead of falling in love with an idea and building it in a vacuum, this skill runs it through a validation gauntlet — surfacing assumptions, identifying risks, and designing the smallest possible test to learn whether the idea has legs before you commit significant resources.

The Validation Funnel

                 ┌─────────────┐
                 │  RAW IDEA   │
                 └──────┬──────┘
                        │
                 ┌──────▼──────┐
                 │  CANVAS IT  │  ← Problem, Solution, Audience, Channel
                 └──────┬──────┘
                        │
                 ┌──────▼──────┐
                 │ CHECKLIST   │  ← 20-point viability screen
                 └──────┬──────┘
                        │
                 ┌──────▼──────┐
                 │ RISK MAP    │  ← What could kill this?
                 └──────┬──────┘
                        │
                 ┌──────▼──────┐
                 │ TEST DESIGN │  ← Smallest experiment that teaches most
                 └──────┬──────┘
                        │
                 ┌──────▼──────┐
                 │ GO / PIVOT  │
                 │   / KILL    │
                 └─────────────┘

The 20-Point Validation Checklist

Rate each factor as ✅ Strong / ⚠️ Moderate / ❌ Weak

Problem & Need

• 1. Is this a real problem? Not a "nice to have" — would people pay to solve it?
• 2. Is the problem widespread? Does enough of your target audience have it?
• 3. Is the problem urgent? Are people actively searching for solutions right now?
• 4. Are people already trying to solve it? What workarounds exist?
• 5. Is the problem getting worse? Trend tailwinds?

Solution & Product

• 6. Can you solve this better than existing alternatives? 2-10× better?
• 7. Is there a clear "must-have" feature set? Or is the scope fuzzy?
• 8. Can you build a minimum version in < 4 weeks? Speed to test matters
• 9. Does the solution have a clear "why now?" Timing advantage?
• 10. Is it legally/ethically clear? Any regulatory risks?

Market & Audience

• 11. Can you name 20 real people who would buy this? Not "people like that"
• 12. Is there a clear, reachable channel to find them? SEO, ads, communities?
• 13. Is the market growing? Expanding, flat, or shrinking?
• 14. Is the market big enough? Can it support a sustainable business?
• 15. Is the competition healthy (not too crowded, not nonexistent)? No competition usually means no market

Business & You

• 16. Can this be profitable? Rough unit economics work?
• 17. Do you have unfair advantage? Why can't 10 others copy this tomorrow?
• 18. Will this be personally sustainable? Do you actually want to work on this for years?
• 19. Can you test this without quitting your day job? Low-risk validation path?
• 20. If this fails, what's the downside? Acceptable loss?

Score interpretation:

Risk Map: The 5 Ways Ideas Die

Lean Validation Experiments

Tier 1: Low Effort (Days)

Tier 2: Medium Effort (Weeks)

Tier 3: Higher Effort (Months)

Trigger Phrases

Step-by-Step Instructions

Step 1: Clarify the Idea

Get it into a single sentence:

"I want to build [solution] for [audience] who struggle with [problem], so they can [outcome]."

If you can't complete this sentence, the idea isn't clear enough yet.

Step 2: Surface Assumptions

List everything you're assuming to be true. Group into:

Key insight: The assumption that would hurt most if wrong is your riskiest assumption. Test that one first.

Step 3: Run the Checklist

Score all 20 items. Identify which areas score lowest — those are your focus areas for testing.

Step 4: Design the Experiment

Follow the experiment tier table above. Rules:

• Smallest test first: Start with Tier 1. Don't build anything until you've talked to customers.
• Define success criteria upfront: "I want 20 email signups from a $50 ad spend" — not "let's see what happens."
• Time-box: 1-2 weeks per test. If you can't get a signal in 2 weeks, the signal might be "no."

Step 5: Run, Measure, Decide

Step 6: Document Learnings

Even for ideas you kill, document what you learned. Future you will benefit from knowing:

• Which assumptions were wrong
• What customers actually said
• What the market signals showed

Examples

Example 1: Validating a Paid Newsletter Idea

Idea: "A paid newsletter teaching designers how to use AI tools"

Clarified: "I want to build a paid weekly newsletter for mid-career designers who struggle with keeping up with AI tools, so they can stay relevant without spending hours researching."

Riskiest Assumptions: 1) Designers are willing to pay for this. 2) I can consistently find valuable content.

Experiment (Tier 1):

1. Post on LinkedIn/X: "Designers — what's your #1 question about AI tools?" (tests problem)
2. If engagement is strong → create a free 5-email mini-series with a "Subscribe for full version" CTA (tests willingness to pay)
3. Success signal: 1,000 free subscribers within 2 weeks

If < 100 signups: Problem not urgent enough or audience not reachable. Kill or narrow niche further. If 100-500: Interesting but weak. Try paid ads to test willingness to pay more directly. If 500+: Proceed. Build the paid tier.

Example 2: Validating a SaaS Tool

Idea: "A tool that auto-generates social media posts from blog content"

Risk Map:

• Solution Risk (HIGH): Will the output be good enough to use without heavy editing?
• Market Risk (MEDIUM): Do content creators feel this pain enough to pay?
• Execution Risk (LOW): Buildable with existing AI APIs

Experiment (Tier 1):

1. Build a manual concierge: Offer to take 5 bloggers' posts and manually create their social content for free
2. Ask: "If this were automated, what would you pay?"
3. Success signal: 3/5 say "I'd pay $20+/month"

Learning: If users love the output but won't pay, pivot to free + ads. If they won't use the output even for free, solution risk is confirmed — kill or redesign.

Pro Tips

• Validation is not about proving you're right — it's about learning the truth as cheaply as possible. If you're trying to prove your idea works, you're doing it wrong.
• Nobody cares about your idea as much as you do. The first 10 conversations will be polite. Push past politeness — ask "Would you pay for this?" directly. If they hesitate, that's data.
• A "maybe" is a "no". In validation, ambiguous responses usually mean no. People who really want something will show clear enthusiasm.
• Kill early, kill often. The best entrepreneurs don't have the best ideas — they kill bad ideas fastest. A dead idea is tuition paid for the next one.
• Validation never ends. Even after launch, every feature, pricing change, and channel is a new hypothesis to test. Build validation into your workflow, not as a one-time event.