How to Find and Validate Startup Ideas With AI [Templates Included]
Use Perplexity and Claude AI to find startup ideas and generating solution
I've spent 100+ hours experimenting with AI tools.
And 16+ years of helping founders design SaaS start-ups.
AI has become integral to my startup design process in recent months.
Here's what I've learned about finding validated startup ideas.
Common Mistakes in Startup Ideation
Many first-time founders fall into predictable traps when searching for startup ideas:
1. Starting with Solutions, Not Problems
Building something cool without validating if anyone needs it
Getting excited about technology rather than user pain points
Assuming others have the same problems you have
2. Targeting Overcrowded Markets
Building "another X for Y" without clear differentiation
Entering markets dominated by well-funded competitors
Choosing ideas based on current trends rather than lasting problems
3. Insufficient Market Research
Relying on friends and family for validation
Not talking to potential customers before building
Making assumptions about user behavior without data
4. Poor Problem Selection
Solving "nice to have" instead of "must have" problems
Targeting problems without clear monetization potential
Choosing problems where users have no budget or buying power
Characteristics of High-Potential Startup Ideas
Strong startup opportunities typically share these traits:
1. Problem Characteristics
Frequent and painful enough to demand immediate attention
Affects users with purchasing power
Currently solved through expensive or inefficient workarounds
Growing in importance due to market trends
2. Market Characteristics
Large enough to support significant growth
Expanding or evolving due to industry changes
Clear path to monetization
Limited but not zero competition (validates market exists)
3. Solution Potential
Technical feasibility with current technology
Clear competitive advantage possible
Reasonable customer acquisition costs
Strong unit economics potential
Step 1: Finding Problems Using Reddit and Perplexity
Use this prompt with Perplexity to mine Reddit for valuable problems:
Search Reddit for people expressing significant frustration, pain points, and "I wish" statements in [INSERT YOUR INDUSTRY/DOMAIN].
Focus on subreddits where your target users hang out, especially professional/industry-specific ones like r/developers, r/consulting, r/sales, etc.
Look for:
- Posts starting with "How do you deal with..."
- Comments containing "I hate that I have to..."
- Phrases like "The worst part of my job is..."
- Recurring complaints about existing tools/processes
- People describing manual/repetitive tasks
- Comments about "wasting time on..."
- Posts asking "Is there a tool that can..."
For each significant problem found:
PROBLEM 1:
- Pain Point: [Describe the core frustration/challenge]
- Audience Profile: [Job roles/industries expressing this pain]
- Current Solutions: [How people are currently handling this]
- Impact Level: [Time wasted/costs/emotional frustration described]
- Mention Frequency: [Number of unique users expressing this pain]
- Representative Quotes:
* [Include 2-3 detailed problem descriptions]
* [Focus on quotes that quantify the impact]
PROBLEM 2:
[Repeat format]
Prioritize problems where:
- Multiple users express strong emotional frustration
- People are currently using hacky/manual workarounds
- The problem costs significant time/money
- Users mention they'd "pay anything" for a solution
- The pain point affects a specific professional audience
- The problem appears unsolved despite existing tools
Sort by problem impact and frequency. Only include problems from the last 6 months.
Analyzing Perplexity Results
When reviewing the results, focus on:
1. Problems mentioned frequently across different communities
2. Clear patterns in user frustrations
3. Quantifiable impact (time/money wasted)
4. Evidence of current workarounds
5. Signs of willingness to pay
Step 2: Ideating Solutions
Once you've identified a promising problem, use this prompt with Claude to explore potential SaaS solutions:
CONTEXT:
[Insert problem description, target audience, and current workarounds found through Perplexity]
Please generate 3 potential SaaS solutions with:
1. SOLUTION OVERVIEW
- Core value proposition
- Key features for MVP
- Main differentiator
- Target price point
2. VALIDATION PATH
- Quickest path to first customer
- Manual MVP approach
- Key metrics to track
- Initial distribution channel
3. RISKS & CHALLENGES
- Main technical hurdles
- Competition risks
- Critical resource needs
Prioritize solutions that can be:
- Built with minimal initial resources
- Validated quickly with real users
- Monetized early
Step 3: Validation Without Building
Before writing any code, validate your chosen solution through:
1. Landing Page Test
Create a simple landing page describing your solution
Run minimal ads to drive traffic
Measure email signups and engagement
Analyze which value propositions resonate
2. Customer Interviews
Find 20+ potential customers
Focus on understanding their workflow
Present solution concepts (not features)
Ask for pre-commitments or letters of intent
3. Fake Door Testing
Add "Buy Now" or "Sign Up" buttons
Measure click-through rates
Capture email addresses of interested users
Test different pricing tiers
4. Manual MVP
Deliver the service manually to early customers
Use existing tools to cobble together solutions
Focus on learning what users truly value
Validate willingness to pay
Success Indicators
Your idea is worth pursuing when:
1. Problem Validation
Multiple users express strong interest
Clear pattern in pain points emerges
Users are actively seeking solutions
Current solutions are inadequate
2. Market Validation
Significant market size confirmed
Clear path to monetization
Reasonable customer acquisition costs
Strong unit economics potential
3. Solution Validation
Users excited about proposed solution
Pre-commitments or letters of intent secured
Strong landing page conversion rates
Successful manual MVP tests
4. Business Validation
Clear competitive advantage identified
Sustainable business model possible
Reasonable development costs
Path to scale visible
Key Takeaways
Start with real problems, not solution ideas
Use data-driven research to validate problems
Generate multiple solution approaches
Validate before building
Focus on problems where users have both pain and budget
Look for opportunities to start small but scale big
The goal isn't to find a perfect idea, but rather to identify a promising problem space where you can create significant value for users while building a sustainable business.