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.



So there’s actual developers who could tell you from the start that LLMs are useless for coding, and then there’s this moron & similar people who first have to fuck up an ecosystem before believing the obvious. Thanks fuckhead for driving RAM prices through the ceiling… And for wasting energy and water.
I can least kinda appreciate this guy’s approach. If we assume that AI is a magic bullet, then it’s not crazy to assume we, the existing programmers, would resist it just to save our own jobs. Or we’d complain because it doesn’t do things our way, but we’re the old way and this is the new way. So maybe we’re just being whiny and can be ignored.
So he tested it to see for himself, and what he found was that he agreed with us, that it’s not worth it.
Ignoring experts is annoying, but doing some of your own science and getting first-hand experience isn’t always a bad idea.
And not only did he see for himself, he wrote up and published his results.
100% this. The guy was literally a consultant and a developer. It’d just be bad business for him to outright dismiss AI without having actual hands on experience with said product. Clients want that type of experience and knowledge when paying a business to give them advice and develop a product for them.
Except that outright dismissing snake oil would not at all be bad business. Calling a turd a diamond neither makes it sparkle, nor does it get rid of the stink.
I can’t just call everything snake oil without some actual measurements and tests.
Naive cynicism is just as naive as blind optimism
With all due respect, you have not understood the basic mechanic of machine learning and the consequences thereof.
Problem is that statistical word prediction has fuck-all to do with AI. It’s not and will never be. By “giving it a try” you contribute to the spread of this snake oil. And even if someone came up with actual AI, if it used enough resources to impact our ecosystem, instead of being a net positive, and if it was in the greedy hands of billionaires, then using it is equivalent to selling your executioner an axe.
Terrible take. Thanks for playing.
It’s actually impressive the level of downvotes you’ve gathered in what is generally a pretty anti-ai crowd.
They are useful for doing the kind of boilerplate boring stuff that any good dev should have largely optimized and automated already. If it’s 1) dead simple and 2) extremely common, then yeah an LLM can code for you, but ask yourself why you don’t have a time-saving solution for those common tasks already in place? As with anything LLM, it’s decent at replicating how humans in general have responded to a given problem, if the problem is not too complex and not too rare, and not much else.
Thats exactly what I so often find myself saying when people show off some neat thing that a code bot “wrote” for them in x minutes after only y minutes of “prompt engineering”. I’ll say, yeah I could also do that in y minutes of (bash scripting/vim macroing/system architecting/whatever), but the difference is that afterwards I have a reusable solution that: I understand, is automated, is robust, and didn’t consume a ton of resources. And as a bonus I got marginally better as a developer.
Its funny that if you stick them in an RPG and give them an ability to “kill any level 1-x enemy instantly, but don’t gain any xp for it” they’d all see it as the trap it is, but can’t see how that’s what AI so often is.
As you said, “boilerplate” code can be script generated - and there are IDEs that already do this, but in a deterministic way, so that you don’t have to proof-read every single line to avoid catastrophic security or crash flaws.
And then there are actual good developers who could or would tell you that LLMs can be useful for coding, in the right context and if used intelligently. No harm, for example, in having LLMs build out some of your more mundane code like unit/integration tests, have it help you update your deployment pipeline, generate boilerplate code that’s not already covered by your framework, etc. That it’s not able to completely write 100% of your codebase perfectly from the get-go does not mean it’s entirely useless.
If it’s boilerplate, copy/paste; find/replace works just as well without needing data centers in the desert to develop.
Other than that it’s work that junior coders could be doing, to develop the next generation of actual good developers.
Yes, and that’s exactly what everyone forgets about automating cognitive work. Knowledge or skill needs to be intergenerational or we lose it.
If you have no junior developers, who will turn into senior developers later on?
At least it isn’t my problem. As long as I have CrowdStrike, Cloudflare, Windows11, AWS us-east-1 and log4j… I can just keep enjoying today’s version of the Internet, unchanged.
AI, duh.
Al is a pretty good guy but he can’t be everywhere. Maybe he can use some A.I. to help!
The only people who believe that are managers and bad developers.
You’re wrong, whether you figure that out now or later. Using an LLM where you gatekeep every write is something that good developers have started doing. The most senior engineers I work with are the ones who have adopted the most AI into their workflow, and with the most care. There’s a difference between vibe coding and responsible use.
There’s also a difference between the occasional evening getting drunk and alcoholism. That doesn’t make an occasional event healthy, nor does it mean you are qualified to drive a car in that state.
People who use LLMs in production code are - by definition - not “good developers”. Because:
This already means the net gain with use of LLMs is negative. Can you use it to quickly push out some production code & impress your manager? Possibly. Will it be efficient? It might be. Will it be bug-free and secure? You’ll never know until shit hits the fan.
Also: using LLMs to generate code, a dev will likely be violating copyrights of open source left and right, effectively copy-pasting licensed code from other people without attributing authorship, i.e. they exhibit parasitic behavior & outright violate laws. Furthermore the stuff that applies to all users of LLMs applies:
We have substantially similar opinions, actually. I agree on your points of good developers having a clear grasp over all of their code, ethical issues around AI (not least of which are licensing issues), skill loss, hardware prices, etc.
However, what I have observed in practice is different from the way you describe LLM use. I have seen irresponsible use, and I have seen what I personally consider to be responsible use. Responsible use involves taking a measured and intentional approach to incorporating LLMs into your workflow. It’s a complex topic with a lot of nuance, like all engineering, but I would be happy to share some details.
Critical review is the key sticking point. Junior developers also write crappy code that requires intense scrutiny. It’s not impossible (or irresponsible) to use code written by a junior in production, for the same reason. For a “good developer,” many of the quality problems are mitigated by putting roadblocks in place to…
When it comes to making safe and correct changes via LLM, specifically, I have seen plenty of “good developers” in real life, now, who have engineered their workflows to use AI cautiously like this.
Again, though, I share many of your concerns. I just think there’s nuance here and it’s not black and white/all or nothing.
While I appreciate your differentiated opinion, I strongly disagree. As long as there is no actual AI involved (and considering that humanity is dumb enough to throw hundreds of billions at a gigantic parrot, I doubt we would stand a chance to develop true AI, even if it was possible to create), the output has no reasoning behind it.
A good developer has zero need for non-deterministic tools.
As for potential use in brainstorming ideas / looking at potential solutions: that’s what the usenet was good for, before those very corporations fucked it up for everyone, who are now force-feeding everyone the snake oil that they pretend to have any semblance of intelligence.
Maybe they’ll listen to one of their own?
The kind of useful article I would expect then is one exlaining why word prediction != AI
Don’t worry. The people on LinkedIn and tech executives tell us it will transform everything soon!
I really have not found AI to be useless for coding. I have found it extremely useful and it has saved me hundreds of hours. It is not without its faults or frustrations, but the it really is a tool I would not want to be without.
That’s because you are not a proper developer, as proven by your comment. And you create tech legacy that will have a net cost in terms of maintenance or downtime.
I am for sure not a coder as it has never been my strong suite, but I am without a doubt an awesome developer or I would not have a top rated multiplayer VR app that is pushing the boundaries of what mobile VR can do.
The only person who will have to look at my code is me so any and all issues be it my code or AI code will be my burden and AI has really made that burden much less. In fact, I recently installed Coplay in my Unity Engine Editor and OMG it is amazing at assisting not just with code, but even finding little issues with scene setup, shaders, animations and more. I am really blown away with it. It has allowed me to spend even less time on the code and more time imagineering amazing experiences which is what fans of the app care about the most. They couldn’t care less if I wrote the code or AI did as long as it works and does not break immersion. Is that not what it is all about at the end of the day?
As long as AI helps you achieve your goals and your goals are grounded, including maintainability, I see no issues. Yeah, misdirected use of AI can lead to hard to maintain code down the line, but that is why you need a human developer in the loop to ensure the overall architecture and design make sense. Any code base can become hard to maintain if not thought through be is human or AI written.
Look, bless your heart if you have a successful app, but success / sales is not exclusive to products of quality. Just look around at all the slop that people buy nowadays.
Two issues with that
I do not understand your point you are making about my particular situation as I am not making slop. Plus one persons slop is another’s treasure. What exactly are you suggesting as the 2 issues you outlined see like they are being directed to someone else perhaps?
I didn’t say your particular application that I know nothing about is slop, I said success does not mean quality. And if you use statistical pattern generation to save time, chances are high that your software is not of good quality.
Even solar energy is not harvested waste-free (chemical energy and production of cells). Nevertheless, even if it were, you are still contributing to the spread of slop and harming other people. Both through spreading acceptance of a technology used to harm billions of people for the benefit of a few, and through energy and resource waste.
I am sure my code could be better. I am also sure the SDKs I use could be better and the gam engine could’ve better. For what I need, they all work good enough to get the job done. I am sure issues will come up as a result as it has many times in the past already, even before LLMs helped, but that is par for the course for a developer to tackle.