I Built 50+ AI Products in 4 Years — Here's What I Wish I Knew at the Start

Since 2021, our team at Autor has shipped over 50 AI products across healthcare, fintech, logistics, and SaaS. Some of them are running in production right now, handling thousands of automated calls per month. Others failed spectacularly — and those are the ones that taught us the most. Where This Comes From I started Autor in Toronto as a one-person AI development shop. The original thesis was simple: companies needed custom AI but couldn't hire fast enough to build it themselves. Four years and 50+ products later, we're a senior-only studio with a production voice AI platform (Loquent) serving healthcare and dental clients 24/7. Along the way, we've impacted over 5 million users, helped clients raise more than $10 million in funding, and shipped across 10+ countries. This isn't a highlight reel. This is the unvarnished list of things I got wrong, figured out the hard way, or wish someone had told me before I wrote my first line of production AI code. 1. Your First AI Product Should Be Boring Our first few products were ambitious. Multi-modal pipelines, complex reasoning chains, novel architectures. Most of them took twice as long as estimated and required constant babysitting in production. The products that actually made money and kept clients happy? A straightforward document classifier. A simple intent router. A basic FAQ bot with good fallback logic. I used to think "boring" meant "not innovative." Now I know boring means "reliable enough that I don't get paged at 3am." Our most successful product, Loquent, handles healthcare scheduling calls. It's not doing anything architecturally exotic. It picks up the phone, understands what the caller needs, books or reschedules an appointment, and hangs up. The magic isn't in the model — it's in the 200+ edge cases we've handled around it. If you're building your first AI product, pick the most boring version of your idea and ship that. You can add complexity later. You cannot add reliability later. 2. Prompt Engineerin