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.
Depends on how demanding you are about your application deployment and finishing.
Do you want that running on an embedded system with specific display hardware?
Do you want that output styled a certain way?
AI/LLM are getting pretty good at taking those few lines of Bash, pipes and other tools’ concepts, translating them to a Rust, or C++, or Python, or what have you app and running them in very specific environments. I have been shocked at how quickly and well Claude Sonnet styled an interface for me, based on a cell phone snap shot of a screen that I gave it with the prompt “style the interface like this.”