Just want to clarify, this is not my Substack, I’m just sharing this because I found it insightful.
The author describes himself as a “fractional CTO”(no clue what that means, don’t ask me) and advisor. His clients asked him how they could leverage AI. He decided to experience it for himself. From the author(emphasis mine):
I forced myself to use Claude Code exclusively to build a product. Three months. Not a single line of code written by me. I wanted to experience what my clients were considering—100% AI adoption. I needed to know firsthand why that 95% failure rate exists.
I got the product launched. It worked. I was proud of what I’d created. Then came the moment that validated every concern in that MIT study: I needed to make a small change and realized I wasn’t confident I could do it. My own product, built under my direction, and I’d lost confidence in my ability to modify it.
Now when clients ask me about AI adoption, I can tell them exactly what 100% looks like: it looks like failure. Not immediate failure—that’s the trap. Initial metrics look great. You ship faster. You feel productive. Then three months later, you realize nobody actually understands what you’ve built.
I built a MAL clone using AI, nearly 700 commits of AI. Obviously I was responsible for the quality of the output and reviewing and testing that it all works as expected, and leading it in the right direction when going down the wrong path, but it wrote all of the code for me.
There are other MAL clones out there, but none of them do everything I wanted, so that’s why I built my own project. It started off as an inside joke with a friend, and eventually materialized as an actual production-ready project. It’s limited more by design of the fact that it relies on database imports and delta edits rather than the fact that it was written by AI, because that’s just the nature of how data for these types of things tend to work.