0xpgm

> Either way, that won't change the ongoing layoffs while trying to pursue the AI dream from management point of view.

I think most companies doing layoffs are bloated to begin with, AI is just the scapegoat to do the layoffs.

In short, it is simply a click-bait title.

And the goal of the article is to draw attention to their project.

Right now majority of beginners start programming with a high-level language, say Python or JavaScript - then for more advanced system-level tasks pickup C/C++/Rust/Zig etc.

If Mojo succeeds, it could be the one language spanning across those levels, while simplifying heterogeneous hardware programming.

But do companies really know how to use AI? I think most of it is experimentation - throwing things to the wall and seeing what sticks.

It's the practitioner who eventually figures out what really works. I see this the same way the agile movement emerged. It was initiated by people who were hands-on programmers and showed enough benefit at minimizing software waste before it took a life of its own and started getting peddled by people who didn't really understand the underlying principles.

However, curious programmers who develop in high level languages will dabble with assembly maybe for fun, and will be much better off for it than those who treat parts of the stack like a black box never to be opened.

Perhaps a viable approach might be to vibe code the translation tool itself and observe that for every input it gives the expected output. Then once the translation is done, the translation tool can be discarded.

This would require a robust test suite though.

One of the cases where vibe coding might actually be useful, writing a throwaway tool.

> Engineers who refuse to, or can't, or won't utilize the benefits that LLMs bring will be left behind. It's just the way it is. I'm already seeing it happening.

Any examples how you see some engineers being left behind?

I wonder, how should an AI company be accountable for non-deterministic nature of AI, which is a fundamental property of the said AI?

People have been drinking too much hopium they have lost touch with reality.

Everyone needs to properly understand these tools before they use them for anything serious.

> This kind of forgetting is normal

Just as shift in power and the rise and fall of nations is normal.

Programmers in non-western countries may not be able to afford $100 per month on vibe coding.

They may keep taking the longer and harder route of a mixture of AI and hand coding.

An extension to Zawinski's Law, every web service attempts to expand until it becomes a social network.

Instead of getting more dependant on Big Tech's AI products, I think the perfect use for AI is develop tools and workflows that decouple one from Big Tech.

Not specifically about your case, but some people are usually just more verbose than others and tend to say the same thing more than once, or perhaps haven't found a clear way of articulating their thoughts down to fewer words.

Quite a nice insight there!

I should probably be thinking more in this direction.

Yeah, structured data implies some processing on raw data to improve its meaning. Alan Kay seems to want to push this idea to encapsulate data with rich behaviour.

Sure, static typing adds some sort of process that provides a coarse interpretation of the data.

Reminded me of this thread between Alan Kay and Rich Hickey where Alan Kay thinks "data" is a bad idea.

My interpretation of his point of view is that what you need is a process/interpreter/live object that 'explains' the data.

https://news.ycombinator.com/item?id=11945722

EDIT: He writes more about it in Quora. In brief, he says it is 'meaning', not 'data' that is central to programming.

https://qr.ae/pCVB9m

To beat to death a well-known quote:

You may be able to go fast with AI, but you can only go far with humans.

As a mostly Python programmer and partly TypeScript programmer, my subjective thought is that a bit more 'noise' with TypeScript than Python.

Just a little more to parse with my eyes and a little more to type with TypeScript.

But hey, with all these cool kids with their AI coding agents, reading and handwriting code may soon be obsolete!

Yup, since around 2016 HN and other tech spaces got infested with people who cannot separate their political ideology from technical discussions.

When it comes to FOSS they claim that FOSS has always been political to justify the politicization of everything they touch.

Things used to be much better when the people adhered to the age-old wisdom "Keep politics and religion out of the office" and carried this attitude to neutral spaces online.

In part, some of us got into tech because it was one of the places where meritocracy ruled and you could get away from those who thrive by overwhelming others with BS.

I apologize for the rant.

A good reason is that Lisp has almost no syntax. So it can act as a neutral language that is easy to learn for developers from other languages.

There is such a thing as a distinct LLM writing style that is not just good structure. Anyone who's read more than five books can tell that.

And the comment itself seems completely LLM generated.

Is there such a thing as a modern Linux stack?

Isn't it by design that linux has many optional components and one can pick and choose as they desire to create their distribution?

I guess it happens when engineers stop driving decisions and the finance people take over. Won't be too good for the company's valuation if people can access the content elsewhere.

I guess that's why Discord is also locked down as much. They have community content that is inaccessible anywhere else but Discord.

To me, it's better than spending months of your free time grinding leetcode to get past an interview (everyone wants to hire like FAANG now).

You get a small reward in return if the contribution is accepted and you get to contribute to the world corpus of knowledge.

I don't think they intend to supplant cPython, but to make it easier for someone to take a piece of software written in high-productivity Python and make it more performant on specialized hardware by using a similar syntax.

Long term it can find applications outside of ML-specific hardware.

Eating your own dogfood is good validation.

I think it's part of the "AI replacing software developers" hype.

Many beginners or aspiring developers swallow this whole and simply point an AI to a problem and submit the generated slop to maintainers.

I believe just as human experts do peer review, someone will need to review the AI's work.

The people who do this review will have to know enough to follow along.

And their cited example was students. I think students would struggle at something new until they 'get it'. Would a software developer who does FPGA development professionally struggle more than, say, a hardware engineer?