As software engineer, we should collectively realize that this is all cope. Every article or comment about how AI will never be smart enough, etc, etc will only be true until its not. One of our main valuable skill sets is now partially automated. Some of us are completely obsolete and its coming for the specialists and more experienced ones within a decade tops. You're not going to convince anyone that "um actually we're better because we bike shed more".
Stuff like this is ridiculous and comes off as frantically trying to save your ass. Its pretty obvious at this point that we will just throw more matmuls at it until it can do this or something equivalent.
> Agents cannot do osmosis. They do not get context by being in the room, by half-hearing the planning conversation, or by carrying the memory of the last incident.
Yeah, you're definitely right about the shifting goalposts ("it's a stochastic parrot" -> "it hallucinates all the time, it can't even get APIs right" -> "it can generate functions but can't reason about the codebase" -> "the bottleneck was never shipping code")
At the same time, humans can move up the abstraction ladder faster than the LLMs can. At least, some humans. Agents can produce lots of code. They can also do the entirely wrong thing. The impact of wrong decisions have been massively write-amplified with more and more intelligent LLMs. With earlier ones, it got a sentence or a function wrong, you reprompted, the cost of a mistake was 10 seconds. Now, you can burn hours or even days of work on the entirely wrong thing without a competent human operator stepping in and course-correcting.
The trajectory of agents have been bigger and bigger context windows, bigger autonomy, but at the same time, a bigger blast radius. In this context, I don't think the human experts will be out of their jobs any time soon.
> At the same time, humans can move up the abstraction ladder faster than the LLMs can
This was kind of the point, its only true for now. I agree with you that this kind of stuff will take longer. I don't think there's probably good training data for it right now. Handling abstractions and course correcting is probably the job now, and it also happens to be exactly the data that we will be typing in our prompts. They'll train on it or something like it.
Unless something radical changes (and that isn't unprecedented! I'm just writing this as of today), the trend is still "just" a bigger hammer. It's bigger, you can get way more done, but the blast radius is also larger.
Take the strawman: even if AI can one-shot basically any application below let's say, 1MLoC, if your prompt is 4 lines, it will generate something. It can't read your mind. If you make proper specs, then you'll get what you want - but many people don't know what they want. And even if they do, they might have contradictions in their requirements, might be asking for something impossible, etc.