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.
And all they’ll hear is “not failure, metrics great, ship faster, productive” and go against your advice because who cares about three months later, that’s next quarter, line must go up now. I also found this bit funny:
Well you didn’t create it, you said so yourself, not sure why you’d be proud, it’s almost like the conclusion should’ve been blindingly obvious right there.
The top comment on the article points that out.
It’s an example of a far older phenomenon: Once you automate something, the corresponding skill set and experience atrophy. It’s a problem that predates LLMs by quite a bit. If the only experience gained is with the automated system, the skills are never acquired. I’ll have to find it but there’s a story about a modern fighter jet pilot not being able to handle a WWII era Lancaster bomber. They don’t know how to do the stuff that modern warplanes do automatically.
It’s more like the ancient phenomenon of spaghetti code. You can throw enough code at something until it works, but the moment you need to make a non-trivial change, you’re doomed. You might as well throw away the entire code base and start over.
And if you want an exact parallel, I’ve said this from the beginning, but LLM coding at this point is the same as offshore coding was 20 years ago. You make a request, get a product that seems to work, but maintaining it, even by the same people who created it in the first place, is almost impossible.
Well, to be fair, different skills are acquired. You’ve learned how to create automated systems, that’s definitely a skill. In one of my IT jobs there were a lot of people who did things manually, updated computers, installed software one machine at a time. But when someone figures out how to automate that, push the update to all machines in the room simultaneously, that’s valuable and not everyone in that department knew how to do it.
So yeah, I guess my point is, you can forget how to do things the old way, but that’s not always bad. Like, so you don’t really know how to use a scythe, that’s fine if you have a tractor, and trust me, you aren’t missing much.
I agree with you, though proponents will tell you that’s by design. Supposedly, it’s like with high-level languages. You don’t need to know the actual instructions in assembly anymore to write a program with them. I think the difference is that high-level language instructions are still (mostly) deterministic, while an LLM prompt certaily isn’t.