The bet seems to be that the seniors are next.

I doubt that (depending on what "senior" means).

The skills to drive AI are much the same as they were for business analysts in the old days. Domain knowledge, insight into user requirements, knowledge of modern UI paradigms, ability to write detailed, consistent requirements docs/ design docs.

There is a deep bench in the industry of these senior-ish people. Many have left to become baristas, dive instructors or hobby farmers, scarred by the pain of building large complex software systems using human labour and absurd Agile rituals. But they could slot straight back in, it's like riding a bike.

AI development is the new waterfall. Its just that the lower level that the BA hands off to, which used to be roomfuls of devs, is now a superhuman who can implement those designs at lighting speed and come back hungrily for more.

But if by senior you mean someone who is just a junior with more experience, someone who's not really in touch with the business's needs and who just works off stuff fed to them by PMs or the like - then yeah, agreed.

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cosmic_cheese a day ago | parent | next [-]

Another thing is that orgs will want to keep around somebody who 1) can be held responsible when things go wrong 2) has a reasonable understanding of the system that's their domain end-to-end 3) can reliably diagnose failures and fix them, regardless of how the code was written.

That's not a role that can reasonably be filled by a junior and management armed with agents doesn't really fit either.

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marcus_holmes a day ago | parent | prev [-]

> But they could slot straight back in, it's like riding a bike.

Yeah, not quite. There's a ton to learn about how to control an LLM while it's writing code, and even more to learn about how to manage a set of agents.

9 months ago I was comparing it to running a dev team, but now it has changed and there are practices and processes that are unique to managing agents.

e.g. a team of software devs have the self-awareness to not take a single marginally-relevant point in a spec document and spend 20% of their team effort to build an entire subsystem to meet it without checking. The process and rituals that we used to use to make sure that a software dev team was making progress and would hit the project deadline are now largely useless, but we need new ones to make sure the agents are not heading off into unnecessary rabbit holes.

I'm not saying those ex-seniors would not be able to get back in the saddle. I'm just saying there's been more change in the last 9 months than there has in the last 30 years, so it may take a period of adjustment.

But I don't think the things that burned them out before will have changed. Dealing with non-tech executives was always the worst part of the job, and LLMs can't help with that, and are even making it worse ("ChatGPT says this should only take a couple a hours and you're using Typescript instead of Go! Why? Fix it!").

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Ferret7446 5 hours ago | parent | next [-]

The "a ton to learn about how to control an LLM" is remarkably similar to learning how to work with a new team of humans, perhaps easier. LLMs though eccentric are far more predictable than most humans.

	▲	beachy 4 hours ago \| parent [-]
		What I love most about AI development is the lack of pushback when you see a completed new feature, realise it was a dumb idea and just pivot hard to something different. A human would (rightfully) call you out for wasting time and resources. AI slurps up your feedback and dives in again with the same vigour.

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lelanthran 19 hours ago | parent | prev [-]

> There's a ton to learn about how to control an LLM while it's writing code, and even more to learn about how to manage a set of agents.

So? The experts have a only few months of experience anyway, gained the slow way (via experimentation). It's not like someone can't pick up those skills in a week.

	▲	marcus_holmes an hour ago \| parent [-]
		A week seems a tad optimistic. But quicker than it took us to learn as we went along, sure.