Gaslights, gaslights everywhere
"...almost nobody's doing manual coding anymore"
They can keep pushing this line, but it doesn't make it true. It's gaslighting, plain and simple.
21 publicly visible posts • joined 18 Sep 2025
It feels like the people using Claude Code break down into two types:
- Engineers with experience, who are using it (and vetting what it produces) to assist in their work;
- People with no experience and no clue what they're doing.
The first category is all well and good, until those experienced engineers retire. Then what? A whole load of garbage code that nobody understands, with 10x inefficiencies, laziness and general dreck baked in by good old Claude.
AI coding produces fast code, not good code. Software was already on a downward trajectory, in terms of producing things that met user needs, but it's now heading into a full on dark age.
When you flick a light switch, a series of deterministic steps take place to ensure the light comes on. That process has been refined over many years, is tried, tested and works. Sure, some electrical systems may have quirks, but usually these are shortcuts or bodges where the person implementing them knows it isn't *ideal* but has to get the job done. My problem with using an analogy like this to AI-based code is that it is not deterministic - it will come up with any number of different approaches each time you ask it, and you'll never get to the "best" solution unless you are already proficient enough in the output it produces to be able to tell what that looks like. As we gradually moved from machine code to assembly to C to other languages and frameworks, I accept the increasing layers of abstraction have meant none of us now are proficient at every layer of the stack. But the crucial point is that thought and experience and understanding went into creating those abstractions. Just blindly asking AI to "make code do thing" and accepting whatever it gives you means we're going to raise a generation of "engineers" who understand nothing at all. At the sight of the first bug, what are they going to do? Ask the AI to fix it? Good luck with that, because the likelihood is, it will try and refactor the entire repo to fix each individual bug, no doubt generating more bugs in the process. The maintainability, extensibility and overall long term stability of anything built this way seems highly doubtful. It would be, to use your original analogy, like flicking a light switch and sometimes getting a light come on and other times starting a fire in the upstairs bathroom; and so you flick the switch a few more times to see whether that will put out the fire, but that then causes the garage door to open and the fridge to turn off. But hey, the light came on.
I'm genuinely not sure governments will be able to afford the size and scale of such a bailout. The banking one in 2008 is going to seem tiny by comparison. What's more, this would be a bailout without any clear demarcation. The banks had debts of X amount, so governments stepped in to buy up that debt. The big tech firms are just burning billions of dollars on compute, continuously. I don't think any government will want to sign up to an indefinite bailout of that magnitude...
The "if used correctly" bit is crucial, and I think often gets lost in the hype surrounding this technology. You still need quality, experienced engineers who know what good software looks like to be able to make effective use of coding assistants. People posting on LinkedIn about how they built a SaaS company in 4 hours using Claude Code are really doing nothing more than spinning up toy apps that would fail spectacularly in any real production scenario. Even the CEO of Cursor has come out today saying we should be "wary" of vibe coding and not use it for important workloads. In my own line of work, I use coding assistants very occasionally, but mainly because googling for code examples is increasingly difficult (what Google has done to their own search engine in borderline criminal, but that's another thought for another day). I don't believe they can replace engineers and I think it's a bad idea to use them instead of training up good juniors to become tomorrow's experienced devs.
Agree entirely with your final paragraph, except to add that I don't reckon all of the big tech firms will survive. OpenAI's finances, in particular, are shonky. I suspect Microsoft will buy them out and absorb them, if only to save face, considering how unpopular Copilot has proven to be.
Absolutely. And the cynic in me wonders if that isn't all a part of a wider play by companies like OpenAI to eventually make a case for government bailouts when that time comes, as they can then paint a far darker picture of the consequences of their going bust ("look at all the other businesses who will fold without us" etc.)
What gets lost in a lot of the discourse about post-bubble AI is "who will pay for it?" Right now, enterprises are cruising on a wave of free money, essentially meaning all of their pet AI projects and code assistants are being massively subsidised by OpenAI, Anthropic, Meta, Microsoft and Google. Eventually those companies will want to see their own ROI (or will go bust in the attempt). When that happens, all the froth about "efficiency" and how much AI is "helping" businesses is going to quickly dissipate as the costs rapidly outweigh the benefits. Sure, a $200 a month subscription to Cursor sounds OK, and is cheaper than hiring an extra engineer. But what happens when that Cursor subscription rises to $2000 a month? Today, you can make the argument that using AI tools will boost productivity (I don't believe it does, personally, but the argument can be made) at little-to-no cost. Once the bubble bursts, that argument just isn't going to cut it. And all those data centres stuffed full of Nvidia chips are going to look pretty darn silly.
Driving a car is akin to using a computer, not being a programmer of said computer. I would agree that in the past, using a computer required some basic (or even BASIC) programming skill to get it to do what you wanted, whereas nowadays to use a computer really doesn't. But programming a computer - and programming it well - still requires the same fundamentals that it has done for decades. You can skip over those fundamentals, and to be honest, most bootcamp-style tuition aimed at new "coders" does exactly that. I just don't believe you'll ever master the craft that way.
The best programmers in my experience are the ones who understand the guts of the machine. Being able to program - as distinct from being able to "code", which isn't really a verb I like to use - is intrinsically tied to the knowledge of how a computer works, not merely smashing tokens together to produce a toy application. I get tired of people (often on LinkedIn) saying things like "hey, remember how we used to think you needed to know assembly language to be able to program? haha wow, we've moved on since then!" as if they've said something insightful. Being able to program in assembly is still important, not so much because you need to use it (though there are still some high performance computing jobs that need it) but because of what it teaches you about how a computer works. Skipping over those fundamentals doesn't "let you focus on what matters" as a lot of these so-called thought leaders like to claim, it just makes you a sloppy programmer who will never improve.
The only mindblowing thing is how vastly disconnected Microsoft leaders - and the rest of the Silicon Valley bigshots - are from their users. Microsoft used to be a software company that cared about making products users wanted, now it's just a funnel for whatever daft trend has taken hold on Wall Street.
Another article citing the "golden rule" of AI assistants, namely to check the output. But if you're not already well versed in the subject matter of the thing you've asked it to help you with, how are you going to be in a position to reliably check its outputs properly? And if you *are* already an expert, why do you need to use an AI assistant in the first place?
The reasoning in this piece amounts to "we should build the data centers anyway", assuming that they will serve some purpose beyond the initial investment being ploughed into them by the tech behemoths. I disagree: a data center custom designed to suit GPUs isn't going to be a whole lot of use several years later. Even if the AI bubble doesn't burst (which I strongly suspect it will within the next 1-2 years) the data centers being built now are not going to be any good for the next generation (or generation after that) of chips. Building AI data centers is hugely wasteful and isn't in any way comparable to the build out of data centers in the past for general cloud services. When both energy and water are at a premium, and leather jacket wearing clowns are telling us to use fossil fuel to power these data centers for their precious GPUs, we should be taking a step back and asking what it's all really for. It certainly isn't for the benefit of ordinary Brits.