Comment The Newspeak police is watching you. (Score 1) 122
EOM
EOM
... any external access. Annoying to quickly get results, but generally regarded as "secure by default". This entails that any decision about access has to be deliberately made by the programmer. The progger can still screw up, but then it's his/her fault, not the fault of the software used.
No need for all this Next.js cruft to patch up Nodes shortcomings. Deno is the official successor to Node and has been around for quite long already. Secure by default, native TypeScript (no transpiling needed), Browser API fully supported, no context switching required or SSR stunts required
Looking through thousands of codefiles and detecting errors and antipatterns is one of those things AI has really surprised me with. Especially with FOSS code and APIs it knows really well. Another one of those definite AI game-changers.
The argument proffered by management appears to boil down to nothing more than, "Well, everyone else is jumping off the Empire State Building, so what's your problem?
Also: These lemmings are in for a FAFO-fueled rude awakening when they discover all the slop they've checked in and shipped/deployed, being machine-generated, is uncopyrghtable. "Um, actually... It's just like using a C compiler, transforming the programmer's intent to runnable code, so..." *SMACK!* Wrong. Compilers are deterministic. You can draw a straight line between the source code (and therefore the programmer's creative choices and intent) and the resulting binary and, given the same input, will generate the same output every time (indeed, if you do get different output, it's a bug) LLMs are anything but -- they'll give you different answers depending on what you may or may not have asked before, the phase of the moon, and which vendor paid to have the LLM preferentially yield responses using their commercial framework.
In short, this is a bone-headed move, and when it came time for the managers' performance review, I'd give a negative score to anyone imposing mandatory LLM use.
Children and teens don't get digitally competent by handing them electronic gadgets. They get competent by learning the difference between a value and a variable, what conditions are and what a loop is.
Obviously. If the state of things and the current rate of change are anything to go by, entry level coding jobs aren't the only jobs to "worry" about.
No tolerance for those either? Yeah? Nice, good stuff. Keep going.
If not, good luck!
Obviously. Yeah, they spread themselves a little to thin and tried everything and the kitchen sink for current gen, right after initially botching their last gen launch epic style, but it's still a console and anybody who knows anything about videogaming knows this. This sensationalist headlining is super-annoying, isn't it?
... totally next level. The amount of science, engineering and precision that go into these is mind-boggling. The shoot 50k tin microdropplets per second and hit each one with a laser, with an error margin of 0 (zero). Quite impressive.
Looking at bizarre shit-show that is morning and evening commute here in Germany and the insane waste caused by the infrastructure required to keep office workers "working" and those countless bullshit-jobs afloat, I have to say he has a point. How heavy that one weighs or how valid it finally is I can't say just now, but he does have a point.
I feel totally confident solving problems with PLs I wouldn't have touched with a ten-foot pole just a year back, due to AI.
Example: The legacy application I am currently maintaining and replacing is totally borked with piles of spagetti-code and shitty, amateurish or simply non-existent architecture. However, I do have to add logic to this already unmaintainable system so I often just push larger portions of that logic further down into the DB and SQL.
SQL _is_ turing complete, but actually developing applications using mostly or only SQL is reserved for very strange/special people still stuck in the 70ies mainframe era or something. Beyond some joins I would never do anything with this PL and move all more complex logic into the application layer.
But with AI writing SQL I feel confident to do such a thing. I _can_ understand what the code does and fix smaller mistakes the AI makes, but actually looking up the syntax and writing it myself would be a complete waste of time and energy to me. With AI absolutely not. It is strange using this PL I normally wouldn't and in this specific scenario it is a stop-gap for reasons unrelated to the tech-stack, but the AI puts out solid code and even corrects my SQL quick-hacks for commits I did myself.
For me the state of things right now is the following: Current AI is basically an API documentation you can talk to, with a premium expert attached. For all PLs that have enough documentation and demo-code available online and enough code-repos of functioning open-source projects for AIs to source information from, AI is a totally viable main programmer if you take your time to lead it well, hand-hold it along the way and double-check the code it generates and avoid any "vibe-coding" bullsh1t.
I would totally feel confident in taking on projects and tasks with APIs or PLs I haven't used yet but am interested in and consider wide-spread enough for AI to know well. I've actually considered doing something like that, like some Rust CLI project or something, just to learn the PL along the way.
And I expect all this AI progging to only improve even further, and quite quickly so.
And his AI off machine.
Got one of those in my pocket already, thanks.
"To IBM, 'open' means there is a modicum of interoperability among some of their equipment." -- Harv Masterson