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Too many founders start with the product. They get excited, build something, and then scramble to figure out if anyone actually wants it.
I almost did the same. Technically, I started by generating silly AI images of my boss to make my coworkers laugh. But when I saw the potential of the tools I was playing with — and how accessible they were becoming — I realized I could turn it into something real.
I didn’t have a background in AI or deep learning. But with open-source tools like Stable Diffusion suddenly available, people like me could build things that felt like magic.
And like most entrepreneurs, I wanted to move fast. But instead of rushing to build, I gave myself a reality check. I asked three hard questions before writing a line of code. That checklist became the foundation of my business — and helped me avoid wasting months (and money) on a product no one wanted.
These same questions apply whether you’re launching a SaaS company, a consumer product, a service-based business, or, yes, an AI tool.
Related: AI Isn’t Plug-and-Play — You Need a Strategy. Here’s Your Guide to Building One.
1. Is there real demand?
Before investing anything in product development, I set up a test. I opened an Etsy store selling AI-generated pet portraits during the holidays. It was clunky. Every order meant I was manually training models and fulfilling them by hand.
But people paid. They loved the results. It wasn’t scalable — yet — but that didn’t matter. It gave me proof:
- I could deliver something people genuinely valued
- They were willing to pay for it
This kind of early signal is more important than a sleek prototype or a detailed roadmap. For you, it might mean selling a simplified version of your offer, pre-selling a service, or running a paid pilot. The goal is the same: confirm there’s real demand before you build at scale.
2. Will people pay me — and how?
After validating interest, I started experimenting with pricing. We tested $15, then $25. We ran ads on Reddit. Some worked, most didn’t. I tried subscriptions — but quickly realized that running custom-trained models on demand was too expensive to support recurring plans at an early stage.
So I switched to a one-time payment model. Simple, low-friction, no complicated onboarding. We started at $9.99, and conversions were strong. Over time, we added higher-tier pricing — but from day one, the business had to make financial sense.
Many people advised offering a freemium version. I considered it, but GPU costs made that unrealistic. Instead, I built a free tool that looked like our main offering (an AI headshot generator) but was actually a low-cost background remover. It gave users a taste of the experience and warmed them up to buy. And it converted.
The takeaway? Revenue models aren’t just about pricing — they’re about sustainability. Founders often over-index on what’s ideal for the user and forget what’s viable for the business.
3. Can I actually reach people?
I didn’t have an audience. I didn’t have connections or media buzz. But I had Reddit.
I started joining threads where people were talking about AI headshots. I added value, offered comparisons, answered questions — and eventually, shared my own product. That got us our first 100 customers. We used Google Ads to scale to 1,000.
It wasn’t viral. It wasn’t pretty. But it worked. Why? Because I focused on solving the hardest part of distribution first: attention and trust.
When people think about go-to-market, they think channels. But it’s better to think in terms of risk:
- Can you find the right people?
- Can you earn their attention?
- Can you convert them — without overspending?
If the answer is no, it doesn’t matter how good the product is.
Related: AI Will Define Your Brand If You Don’t — Here’s How to Take Control
Don’t build until you can answer these three questions
Every founder wants to build something great. But building too early — or on shaky assumptions — can kill even the best ideas.
A rough product built on real answers will always beat a polished one built on hope.
So before you start building or investing heavily in a new product or service, ask yourself:
- Who wants this right now?
- Will they pay?
- Can I reach them profitably?
Everything else can wait.
Too many founders start with the product. They get excited, build something, and then scramble to figure out if anyone actually wants it.
I almost did the same. Technically, I started by generating silly AI images of my boss to make my coworkers laugh. But when I saw the potential of the tools I was playing with — and how accessible they were becoming — I realized I could turn it into something real.
I didn’t have a background in AI or deep learning. But with open-source tools like Stable Diffusion suddenly available, people like me could build things that felt like magic.
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