The long-term popularity of any given tool for software development is proportional to how much labour arbitrage it enables.

Right. Because if you quote $700,000 to do a job in C/C++, and someone else quotes $70,000 to do the same job in JavaScript… no prizes for correctly guessing who wins the contract.

But that’s not the whole story. Where C really falls to shit is if you compare it to giving the JavaScript project $500,000. At that point, it’s still far cheaper than C, but you can hire a 7x larger team. Hire twice as many coders and also give them a whole bunch of support staff (planning, quality assurance, user experience design, a healthy marketing budget…)

JavaScript is absolutely a worse language than C/C++. But if you compare Visual Studio to Visual Studio Code (with a bunch of good plugins)… then there’s no comparison VSCode is a far better IDE. And Visual Studio has been under active development since the mid 90’s. VSCode has existed less than half that long and it has already eclipsed it, despite being backed by the same company, and despite that company being pretty heavily incentivised to prioritised the older product (which they sell for a handsome profit margin, while the upstart is given away for free).

I learned C 23 years ago and learned JavaScript 18 years ago. In my entire life, I’ve written maybe 20,000 lines of C code where I was actually paid to write that code and I couldn’t possibly estimate the number of lines of JavaScript. It’d be millions.

I hate JavaScript. But it puts food on the table, so turn to it regularly.

Large Language Models are a remarkable discovery that should, in the long term, tell us something interesting about the nature of text. They have some potentially productive uses. It’s destructive uses and the harm it represents, however, outweigh that usefulness by such a margin that, yes, I absolutely do think less of you for using them. (You can argue about productivity and “progress” all you like, but none of that will raise you back into my good opinion.)

Yeah you’re way off the mark. Earlier today I added this comment to my code:

// remove categories that have no sales

For context… above that comment was a fifty lines of relatively complex code to extract a month of sales data from several database tables, and summarise it down to a simple set of figures which can be used to generate a PDF report for archival/potential future auditing purposes. Boring business stuff that I’d rather not work on, but it has to be done.

The database has a bunch of categories which aren’t in use currently (e.g. seasonal products) and I’d been asked to remove them. I copy/pasted that comment from my issue tracker into the relevant function, hit enter, and got six lines of code. A simple map reduce function that I could’ve easily written in two minutes. The AI wrote it in a quarter of a second, and I spent one minute checking if it worked properly.

That’s not a “potential” productivity boost, it’s a big one. Does that make me worse at my job? No - the opposite. I’m able to focus all of my attention on the advanced features of my project that separate it from the competition, without getting distracted much by all the boring shit that also has to be done.

I’ve seen zero evidence of LLM authored code being destructive. Sure, it writes buggy code sometimes… but humans do that too. And anyone with experience in the industry knows it’s easier to test code you didn’t write… well guess what, these days I don’t write a lot of my code. So I’m better equiped to catch the bugs in it.

What really baffles me is how bad we (as an industry) are at actually using engineering to leverage these frameworks.

It seems to me, like 90% of the regular, boring business software falls into a handful of categories, where in each category the same problems get solved again and again and again. Frameworks do help, but by far not as much as I’d expect.

Just think about how much software is essentially form>validation>transformation>persistence>messaging. It’s always the same, yet if you’d want to write one of these apps, you’d start with a rather bare bones Spring Boot/Quarkus app and maybe a React frontend, that doesn’t have any connection to the backend, so you have to manually plug them into each other.

The components sourced from an intern fixing ChatGPT’s output just enough for it to run and the exhaustively tested ones from a senior developer are equivalent in the eyes of management.

Um. What? This is not normal. Seek better management.