Let's talk about the elephant in the room – building a product alone is tough. While mentoring solo founders, I've seen the same challenges come up again and again:
- You're making every decision alone (and sometimes the echo in your head gets pretty loud)
- Your budget is tight (or maybe nonexistent)
- You need to move fast before your savings run out or someone else builds your idea
- You're wearing all the hats – researcher, designer, developer, marketer, and janitor
Sound familiar? That's exactly why I started advising founders to use AI strategically. Not as a replacement for real work, but as your virtual assistant that:
- Helps you move faster (without cutting corners on research)
- Scales your thinking (so you can focus on what matters)
After running my own user research for a food photography app and helping numerous clients in creative industries, I've developed a practical approach to using AI that actually works for solo founders. No fluff, no fancy theories – just practical tools and techniques that help you validate ideas, build products, and get to market faster.
Let me share what actually works, where AI can be your best friend, and where you need to be careful.
Learning From My Own Journey
When I was doing user research for a food photography app, I talked to both restaurant owners and photographers. Here's how I used AI to make sense of all that information – and how you can too.
The Real Talk About AI Tools
Let me break down the tools that have actually worked for my clients and me:
Finding & Understanding Your Users
1. Smart User Recruitment
- Use ChatGPT to generate LinkedIn outreach messages:
Prompt: "Help me write a LinkedIn message to [user type] that:
- Shows I understand their pain points
- Offers clear value for their time
- Keeps it under 300 characters
- Doesn't sound salesy"
- Use Claude to identify where your users hang out:
Prompt: "I'm looking for [user type]. Help me identify:
1. Top 5 online communities they participate in
2. Professional groups they belong to
3. Events they likely attend
4. Publications they read
5. Social media hashtags they follow"
2. Creating User Personas (That Actually Help)
Instead of making up personas, use AI to analyze real conversations:
Prompt for Claude/GPT:
"Based on these 5 user interviews, help me identify:
1. Common frustrations that came up repeatedly
2. Shared workplace challenges
3. Tools they currently use
4. Language/terms they use naturally
5. Surprising patterns in their behavior"
Real Example: When I did this for photographers, I discovered they all used the same phrases about "workflow hell" and "client revision chaos" - this became our marketing language.
3. Community Research Shortcuts
- Use Claude to analyze Reddit/Discord discussions:
Prompt: "Analyze these 10 Reddit threads about [your problem space].
Identify:
1. Common complaints
2. Solutions people are cobbling together
3. Price points mentioned
4. Feature requests
5. Emotional triggers"
4. User Interview Efficiency
Quick prep for each interview:
Prompt: "Based on this person's LinkedIn/social profile:
1. Draft 3 personalized questions
2. Identify their likely pain points
3. Suggest topics to explore
4. Flag potential objections
5. Note their professional context"
5. Interview recording and analysis
I used to frantically take notes during interviews, missing all the good stuff. Now? I chat naturally and let AI do the heavy lifting.
Dovetail (Pro: $20/month) - elaborated research tool for massive research projects
- AI-powered research hub for user insights
- Automated themes & patterns detection
- Video/audio transcription
- Highlights key moments in interviews
- Generates research insights & reports
Otter.ai ($16.99/month) - My go-to
- Live transcription
- Speaker identification
- Easy sharing and searching
- Mobile app for in-person meetings
Lifehack: cobine transcription tools with analysis via GPT/Claude
5. Market Research
- Perplexity.ai (Free tier works great)
- Perfect for quick market size checks
- Finding competitor feature sets
- Industry trend validation
6. Competitor Research
Prompt: "For these 3 competitors:
1. List their key features
2. Identify gaps in their offering
3. Analyze their pricing strategy
4. Find common user complaints
5. Spot market opportunities"
Making Decisions Faster
7. Feature Prioritization
Instead of endless pro/con lists:
Prompt: "Given these user insights and our resources, help prioritize these features by:
1. Impact on user pain points
2. Development complexity
3. Time to implement
4. Market differentiation
5. Revenue potential"
8. Quick Market Validation
Before building anything:
Prompt: "For this product idea targeting [market]:
1. List potential red flags
2. Identify minimum validation criteria
3. Suggest quick experiments
4. Draft hypothesis to test
5. Estimate market size signals"
Time-Saving Templates
9. User Research Templates
Have AI create your standard documents:
- Interview scripts
- Feedback surveys
- Follow-up emails
- Thank you notes
- Case study formats
The Reality Check Section
Remember:
- AI is great for preparation and analysis, terrible for empathy
- Use AI to scale what's working, not to avoid real user contact
- Always verify AI insights with real users
- Keep the human touch in your communications
Quick Wins vs. Time Wasters:
✅ Good Use of AI:
- Analyzing interview transcripts
- Generating outreach templates
- Finding patterns in feedback
- Drafting follow-up emails
- Creating interview questions
❌ Don't Waste Time:
- Having AI create fictional user stories
- Relying solely on AI market research
- Using AI to avoid user conversations
- Letting AI make strategic decisions
- Over-automating personal communications
Lessons Learned (The Hard Way)
What Actually Works:
AI is great for scaling research, terrible for replacing it
Use AI to prepare and analyze, not to avoid user contact
Mix AI insights with human intuition.
Where I Messed Up:
Initially relied too much on AI-generated market research. Go deeper, talk to market players and experts, validate numbers with industry-specific research and primary sources. There were times, when I didn't validate AI insights with real users, and got caught up in AI's capability hype.
What I'd Do Differently: Start with more manual processes to understand the workflow. Use AI to scale what works, not to guess what might work. Focus more on user stories than AI-generated personas
Quick Start Guide
- Week 1: Setup Get Claude or ChatGPT Plus subscription. Set up Otter.ai for interviews or just record them in google meet. Create basic research templates
- Week 2-3: Research Conduct 5 user interviews. Use AI to analyze patterns. Create hypothesis for solutions
- Week 4: Prototype Use AI tools to generate mockups. Test with users. Iterate based on feedback
The Human Touch (Important!)
Remember, while AI is incredible for scaling and analysis, your superpower as a founder is your human connection with users. I've seen too many founders hide behind AI tools instead of talking to users.
Keep it real:
- Meet users in person when possible
- Build genuine relationships
- Use AI to enhance, not replace, your instincts
Need Help?
If you're stuck or want to bounce ideas around, feel free to reach out. I've helped founders navigate this journey, and I'm happy to share more specific examples or templates.
Remember: AI is your assistant, not your replacement. Your understanding of your users' needs is what will make your business successful.
Let's build something amazing together! 🚀