this post was submitted on 07 Dec 2025
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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.

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[–] victorz@lemmy.world 10 points 3 days ago (32 children)

What kind of small things have you vibed out that you needed?

[–] utopiah@lemmy.world 10 points 2 days ago (25 children)

FWIW that's a good question but IMHO the better question is :

What kind of small things have you vibed out that you needed that didn't actually exist or at least you couldn't find after a 5min search on open source forges like CodeBerg, Gitblab, Github, etc?

Because making something quick that kind of works is nice... but why even do so in the first place if it's already out there, maybe maintained but at least tested?

[–] jj4211@lemmy.world 1 points 2 days ago (8 children)

So if it can be vibe coded, it's pretty much certainly already a "thing", but with some awkwardness.

Maybe what you need is a combination of two utilities, maybe the interface is very awkward for your use case, maybe you have to make a tiny compromise because it doesn't quite match.

Maybe you want a little utility to do stuff with media. Now you could navigate your way through ffmpeg and mkvextract, which together handles what you want, with some scripting to keep you from having to remember the specific way to do things in the myriad of stuff those utilities do. An LLM could probably knock that script out for you quickly without having to delve too deeply into the documentation for the projects.

[–] MangoCats@feddit.it 1 points 1 day ago

I'll put it this way: LLMs have been getting pretty good at translation over the past 20 years. Sure, human translators still look down their noses at "automated translations" but, in the real world, an automated translation gets the job done well enough most of the time.

LLMs are also pretty good at translating code, say from C++ to Rust. Not million line code bases, but the little concepts they can do pretty well.

On a completely different tack, I've been pretty happy with LLM generated parsers. Like: I've got 1000 log files here, and I want to know how many times these lines appear. You've got grep for that. But, write me a utility that finds all occurrences of these lines, reads the time stamps, and then searches for any occurrences of these other lines within +/- 1 minute of the first ones.... grep can't really do that, but a 5 minute vibe coded parser can.

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