Summary:
Validate real demand before building by testing with a simple, manual version to confirm people will pay.
Experiment with pricing models to ensure financial sustainability, avoiding assumptions about what users prefer.
Focus on distribution risks: find your audience, earn their attention, and convert them cost-effectively.
Use free tools or trials to warm up users and drive conversions without high costs.
Answer three key questions: demand, payment, and reach, to avoid wasting time and resources on unproven ideas.
Too many founders jump straight into product development, driven by excitement, only to later scramble to find out if anyone actually wants what they've built. I nearly fell into the same trap. It all began with me generating silly AI images of my boss to amuse coworkers, but I quickly saw the potential in the accessible AI tools I was using. Without a background in AI or deep learning, I realized that open-source tools like Stable Diffusion could empower anyone to create something magical.
Instead of rushing to code, I paused and asked myself three critical questions. This simple checklist became the bedrock of my business, saving me from wasting months and money on a product with no market. These questions are universal, applicable whether you're launching a SaaS, a consumer product, a service, or an AI tool.
Is There Real Demand?
Before investing in product development, I set up a basic test: an Etsy store selling AI-generated pet portraits during the holidays. It was manual and clunky—every order required me to train models and fulfill them by hand. But people paid and loved the results. This early signal proved that I could deliver value and that customers were willing to pay. For any founder, this means validating demand through methods like selling a simplified version, pre-selling, or running a paid pilot before scaling up.
Will People Pay Me—and How?
After confirming interest, I experimented with pricing. We tested $15 and $25, ran ads on Reddit, and tried subscriptions. However, the high costs of custom-trained models made recurring plans unsustainable early on. I switched to a one-time payment model starting at $9.99, which saw strong conversions. Over time, we added higher tiers, but from day one, the business had to be financially viable. I avoided freemium due to GPU costs and instead created a free tool that mimicked our main offering—an AI headshot generator—but was actually a low-cost background remover. This gave users a taste and warmed them up to purchase, driving conversions. The key takeaway: revenue models must prioritize sustainability over ideal user scenarios.
Can I Actually Reach People?
I had no audience, connections, or media buzz, but I leveraged Reddit. By joining threads on AI headshots, adding value, answering questions, and eventually sharing my product, I gained our first 100 customers. Google Ads helped scale to 1,000. It wasn't viral or glamorous, but it worked because I focused on the hardest parts of distribution: earning attention and trust. When planning your go-to-market, think in terms of risk: Can you find the right people, earn their attention, and convert them without overspending? If not, even the best product will fail.
Don't build until you can answer these three questions. A rough product based on real answers will always outperform a polished one built on hope. Before investing heavily, ask: Who wants this right now? Will they pay? Can I reach them profitably? Everything else can wait.
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