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.
Wait so I should just be manually folding all these proteins?
Do you not know the difference between an automated process and machine learning?
The thing with being cocky is, if you are wrong it makes you look like an even bigger asshole
https://en.wikipedia.org/wiki/AlphaFold
Cool, now do an environmental impact on it.
Cool, now do an environmental impact on the server hosting your instance while you pollute by mindlessly talking shit on the Internet.
I’ll take AI unfolding proteins over you posting any day.
Hilarious. You’re comparing a lemmy instance to AI data centers. There’s the proof I needed that you have no fucking clue what you’re talking about.
“bUt mUh fOLdeD pRoTEinS,” said the AI minion.
Yes? Machine learning has been huge for protein folding and not because anyone is stupid, it’s because it’s a task uniquely suited for machine learning, of which there are many. But none of that is what this AI bubble is really about, and even though I find the underlining math and technology fascinating, I share the disdain for how the bulk of it is currently being used.