[mmcdermott]

Adoption takes time, for sure, especially when dealing with fixed assets like a factory. The difference I'm poking at is that electricity had a clear value proposition and improved over time. I see people looking for the value proposition in GenAI/LLMs, which brings me to the original question.

If GenAI now was like early electricity, we would know what we wanted to use it for, even if we weren't there yet. That isn't what it looks like to me, but I'd be curious to know if that's just where I'm sitting, metaphorically speaking.

Every company I have worked for had more work than hands for programming and other knowledge work. Capacity is valuable. Does anyone here see GenAI teams being spun up for "management" by a human? Or do we see fancy Google search / code completion?

[eru]

> Adoption takes time, for sure, especially when dealing with fixed assets like a factory.

I was talking about the need to re-imagine and re-organise how factories work, not about the physical factories themselves. So it's more like a 'software' problem.

> Does anyone here see GenAI teams being spun up for "management" by a human? Or do we see fancy Google search / code completion?

How would the two cases look different? If you have a human worker that uses GenAI to help her complete tasks (via something like fancy auto-completion of text, code etc) that previously took a whole human team, that's exactly how you would 'spin up a team of GenAI for management by a human' would look like, wouldn't it?

It's just our framing that's different, and perhaps who that human is: you take someone who's familiar with the actual work and give her the tools to be faster, instead of taking someone who's more familiar with the meta-level work of managing humans.

I suspect that's because managing humans is a rather specialised skill in the grand scheme of things, and one that doesn't help much with telling GenAI what to do. (And, human managers are more expensive per hour than individual contributors.)

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In any case, I agree that GenAI at the moment is still too immature to be trusted with much on its own. I hope more globally optimising AI like AlphaGo etc comes back in style, instead of essentially 'greedy' contemporary GenAI that just produces one token after another.

[mmcdermott]

What I'm picturing is two divergent paths with very different impacts on human interaction.

1) Every human programmer becomes the surgeon in Fred Brooks's surgical team model (https://en.wikipedia.org/wiki/The_Mythical_Man-Month#The_sur...) and AI provides the rest. In effect, all working human programmers are software architects in the sense that they exist in large companies. The unstated assumption here is that going from vague user input to a solution is roughly equivalent to AGI, and so is further out than anything on the immediate horizon.

2) GenAI is used as a sort of advanced template/snippet/autocomplete system.

The first one is a fundamental paradigm shift. Professional programmers don't cease to exist, but the profession becomes inherently smaller and more elite. The bar is higher and there isn't room for many perfectly intelligent people who work in the field today.

The second one is a force multiplier and is helpful, but is also a much more banal economic question, namely whether the tool generates enough value to justify the cost.

I have no complaint either way and I'm definitely interested in the next step beyond what we've seen so far. The hype implies that the first branch above is where everything is headed, hence the "death of programming as a profession" type articles that seem to be making the rounds, but that isn't what I've seen day-to-day, which is what prompted the original thought.