The most compelling argument I heard is that WASM can’t manipulate the DOM and a lot of people don’t want to deal with gluing JS code to it, but aside from that

But other than that, Mrs. Lincoln, how was the play?

You’ve gotten several other answers that are true and correct - the pain of implementation at this point is greater than the pain points that WASM solves. But this is also a non trivial one - most of what Javascript should be doing on a webpage is DOM manipulation.

At some point, WASM will either come out with a killer feature/killer app/use case that Javascript (and all the libraries/frameworks out there) hasn’t figured out how to handle, and it will establish a niche (besides “Javascript is sort of a dumb language let’s get rid of it”), and depending on the use case, you might see some of the 17.4 million (estimated) Javascript developers chuck it for…what? Rust? Kotlin? C? C#? But the switching costs are non-trivial - and frankly, especially if you still have to write Javascript in order to manipulate the DOM…well, what are we solving for?

If you’re writing a web app where one of the WASM languages gives you a real competitive advantage, I’d say that’s your use case right there. But since most web applications are basically strings of api calls looped together to dump data from the backend into a browser, it’s hard to picture wider adoption. I’ve been wrong before, though.

I’m a web dev turned DevOps (with the front end design eye and CSS knowledge of a DevOps! Lol) but this seems like a great place to use a css grid, no?

Like the SEAL who became a doctor and then went to space. Don’t feel like you have to limit yourself, you know?

Oh yeah, well I’ll make my own community! With blackjack! And hookers! You know what, forget the community and the blackjack! Aw, forget the whole thing.

I watched it in Vim, mostly because I don’t hate myself enough.

Not to spoil the ending either, but the nuclear device goes off because Oppenheimer smashes a bunch of keys and then finally remembers :wq.

Just because it’s ‘the hot new thing’ doesn’t mean it’s a fad or a bubble. It doesn’t not mean it’s those things, but…the internet was once the ‘hot new thing’ and it was both a bubble (completely overhyped at the time) and a real, tidal wave change to the way that people lived, worked, and played.

There are already several other outstanding comments, and I’m far from a prolific user of AI like some folks, but - it allows you to tap into some of the more impressive capabilities that computers have without knowing a programming language. The programming language is English, and if you can speak it or write it, AI can understand it and act on it. There are lots of edge cases, as others have mentioned below, where AI can come up with answers (by both the range and depth of its training data) where it’s seemingly breaking new ground. It’s not, of course - it’s putting together data points and synthesizing an output - but even if mechanically it’s 2 + 3 = 5, it’s really damned impressive if you don’t have the depth of training to know what 2 and 3 are.

Having said that, yes, there are some problematic components to AI (from my perspective, the source and composition of all that training data is the biggest one), and there are obviously use cases that are, if not problematic in and of themselves, at very least troubling. Using AI to generate child pornography would be one of the more obvious cases - it’s not exactly illegal, and no one is being harmed, but is it ethical? And the more societal concerns as well - there are human beings in a capitalist system who have trained their whole lives to be artists and writers and those skills are already tragically undervalued for the most part - do we really want to incentivize their total extermination? Are we, as human beings, okay with outsourcing artistic creation to this mechanical turk (the concept, not the Amazon service), and whether we are or we aren’t, what does it say about us as a species that we’re considering it?

The biggest practical reasons to not get too swept up with AI is that it’s limited in weird and not totally clearly understood ways. It ‘hallucinates’ data. Even when it doesn’t make something up, the first time that you run up against the edges of its capabilities, or it suggests code that doesn’t compile or an answer that is flat, provably wrong, or it says something crazy or incoherent or generates art that features humans with the wrong number of fingers or bodily horror or whatever…well then you realize that you should sort of treat AI like a brilliant but troubled and maybe drug addicted coworker. Man, there are some things that it is just spookily good at. But it needs a lot of oversight, because you can cross over from spookily good to what the fuck pretty quickly and completely without warning. ‘Modern’ AI is only different from previous AI systems (I remember chatting with Eliza in the primordial moments of the internet) because it maintains the illusion of knowing much, much better.

Baseless speculation: I think the first major legislation of AI models is going to be to require an understanding of the training data and ‘not safe’ uses - much like ingredient labels were a response to unethical food products and especially as cars grew in size, power, and complexity the government stepped in to regulate how, where, and why cars could be used, to protect users from themselves and also to protect everyone else from the users. There’s also, at some point, I think, going to be some major paradigm shifting about training data - there’s already rumblings, but the idea that data (including this post!) that was intended for consumption by other human beings at no charge could be consumed into an AI product and then commercialized on a grand scale, possibly even at the detriment of the person who created the data, is troubling.

My first wifi network post-college was “viruses_and_goat_porn”.

It still didn’t stop free loaders….but in their defense, there were no viruses. 👀🐐

Good advice already in this thread, but I’d add: ask smart questions, and when you’re engaging with a senior/mentor, build the picture for them. Everyone (including your mentor) expects you to have questions - they want you to ask questions, rather than just spinning your wheels for days and days. But they also want to know what you’ve tried and what you’ve looked at for resources. And despite appearances, they don’t always have the entire code base committed to memory. :)

For instance - suppose you’d been asked to, using the UI, return a piece of information from an external API and display it within the UI.

Bad question: “Hey, so I tried to integrate that third party API, but I’m not getting a return.”

“Okay - what kind of code are you getting? And what do the docs say?”

🤷‍♂️

Good question: “Hey, so I tried to integrate that third party API, but the return I’m getting from it is a 401 error. That should be an authentication error - but just in case, I pinged their server from our server, and they can reach each other. The documentation says that I have to use our key to get a JWT, but hitting the endpoint it says gives me a 401 error. I double checked our token; I’ve got the right one. And I’m sending it in the header as ‘auth’ like the documentation says. Where else should I look?”

“Oh yeah, that’s a tricky one - you have to encode the token before you send it; let me see if I’ve got an example where you can see what that looks like…”

One of the things that will happen over time, based on the questions that more senior SDEs ask, you’ll be able to ‘rubber ducky’ problem solve by asking yourself the questions that they would usually ask you, and it’s shockingly effective to help you sort your own problems out and clear your own blockers.

This was my first thought.

I do this for a living and it’s literally built into Linux.

Set their permissions carefully, ensure that the permission set does what you want (and not a bunch of stuff you don’t want), and keep on keeping on.