ingonealan3

Don't stop there: it's not just that LLMs are "internally different", there is no inside there. There is no internal experience taking place. There is no thinking, and probably more importantly, no understanding.

But the result that the algorithm generates tickles our language pattern recognition, which our brains interpret as an interaction with an intelligent, conscious actor.

First of all, the public conversation is weird, because people conflate all kinds of different things under the term "AI". This term is slowly becoming meaningless, like "chemicals" or "drugs".

Secondly, your crazy uncle having dumb conversations with ChatGPT does not have any real connection, in practice, to Palantir supplying the US Military with flawed intelligence.

"How do you cope with knives being used to stab people? Your house is full of these weapons, that create so much suffering! You're basically guilty by proxy of all stabbing crimes. You should feel bad!"

Why? It does, after all, reduce a collection to a single value.

OP must be an LLM

It's funny when these executives, on one side, will happily lay people off, implement attrition policies, or engage in morally-questionable behaviors, all with the purpose of maximize profits, while on the other hand blame the employees that they don't care about the company, and are only in it for the money. It's a thinly veiled way of saying "only I am allowed to play the game as the ruthless capitalist".

So, business as usual? The mighty have always influenced the less powerful. The US has just as much incentive to influence European elections, as do Russia or China. It's not surprising that they act on these incentives.

Also, in one of their points they argue that, in the case of non-programmers, the more domain expertise one brings to the table, the higher the chances of a successful outcome. Well sure, but what's the quality of the output? Someone with little to no coding ability cannot meaningully judge a piece of source code. It might not matter when we're talking about one-off scripts and such, but for anything more serious, somebody really needs to be in the driver's seat, 'cause this ain't a Waymo yet.

You can't tell me what to do; you're not my real mother!

Not exactly overthinking, more like misinterpreting. Claude is not a person. LLMs don't think, want, feel, or have any kind of inner experience whatsoever. They just generate words (or tokens, to be more precise) based on a complex statistical algorithm. The algorithms tries to generate along the same patterns it saw in its training data. This means that the responses you saw are nothing but echoes of the impatience of other people, as captured in diverse forms of text (for example reddit conversations).

This guy deletes!

Your line of thinking rests on the assumption that "AI enables machines to understand English", but this is false. AI, or more precisely LLMs, are a class of algorithms that take a string as input, and return a new string generated through statistical black magic. They don't enable the machine to do anything in particular. You can't ask the LLM to run some arbitrary computation directly on the CPU, for example. If that were possible, your argument would hold some water, at least to some extent.

It's called anchoring, and it's a negotiation tactic. Also extensively used in marketing.

Small startup. I don't use a laptop. I prefer work/home separation, so I use a workstation, and I'm in the office 5 days a week. I have three screens attached to my PC. A main 27" (slightly curved) screen in the middle, horizontally, and two 24" screens turned vertically, on each side. I also use a tiling WM for managing desktops and windows. I have arrived at this setup, that I really enjoy using, because I have a lot of screen real-estate, but I don't really need to rotate my head much, just glance a little to one side or another. Tiling WMs also allow you to create muscle memory for where each one of your tools is, and you can get there instantly, rather than having to cycle through everything all the time.

It's a bit of an over-generalization, though. Tech stack matters more and more, the larger a project gets, and the more people join it. Some languages and frameworks lend themselves better at long-term maintainability, as the code base gets larger. Other put so many foot-guns at your disposal, that you need a lot of discipline to keep things manageable. And, of course, once you start working together with others, the choice of language and framework becomes much more consequential, as it will limit who can join the project, how quickly they can become productive once they join, etc.

There are a few layers to this problem. They're not entirely wrong about developments in AI-assisted coding – it is progressing quickly. But for now, LLMs doing "any software engineer job" is still far off. At least in the way people like your brother mean it: that some non-technical person can just tell an AI "build <this or that> for me," and the AI handles it end-to-end.

Until we reach that stage (if ever), technical people will still be needed in the loop – to check that the AI's work is correct, integrates properly with the rest of the system, and meets the requirements. And this leads to the main role of any engineer: figuring out the requirements. In other words, determining what exactly needs to be built.

People, in general, aren’t great at describing things in a precise, unambiguous way – and non-technical people even less so. I don't see this part of the equation being automated anytime soon.

As long as you enjoy figuring things out, solving technical problems, architecting software systems, and understanding software at a deep level, I think there will be work for you for the foreseeable future – no matter how "AI-assisted" it becomes.