aphyrThe Future of Everything Is Lies, I Guess: New Jobs
https://aphyr.com/posts/419-the-future-of-everything-is-lies-i-guess-new-jobs
I am personally of the opinion that ML will end up being 'normal technology', albeit incredibly transformative.
I think you can combine 'Incanters' and 'Process Engineers' into one - 'Users'. Jobs that encompass a role that requires accountability will be directing, providing context, and verifying the output of agents, almost like how millions of workers know basic computer skills and Microsoft Office.
In my opinion, how at-risk a job is in the LLM era comes down to:
1: How easy is it to construct RL loops to hillclimb on performance?
2: How easy is it to construct a LLM harness to perform the tasks?
3: How much of the job is a structured set of tasks vs. taking accountability? What's the consequence of a mistake? How much of it comes down to human relationships?
Hence why I've been quite bullish on software engineering (but not coding). You can easy set up 1) and 2) on contrived or sandboxed coding tasks but then 3) expands and dominates the rest of the role.
On Model Trainers -- I'm not so convinced that RLHF puts the professional experts out of work, for a few reasons. Firstly, nearly all human data companies produce data that is somewhat contrived, by definition of having people grade outputs on a contracting platform; plus there's a seemingly unlimited bound on how much data we can harvest in the world. Secondly, as I mentioned before, the bottleneck is both accountability and the ability for the model to find fresh context without error.
> Hence why I've been quite bullish on software engineering (but not coding). You can easy set up 1) and 2) on contrived or sandboxed coding tasks but then 3) expands and dominates the rest of the role.
Why can't LLMs and agents progress further to do this software engineering job better than an actual software engineer? I've never seen anyone give a satisfactory answer to this. Especially the part about making mistakes. A lot of the defense of LLM shortcomings (i.e., generating crappy code) comes down to "well humans write bad code too." OK? Well, humans make mistakes too. Theoretically, an LLM software engineer will make far fewer than a human. So why should I prefer keeping you in the loop?
It's why I just can't understand the mindset of software engineers who are giddy about the direction things are going. There really is nothing special about your expertise that an LLM can't achieve, theoretically.
We're always so enamored by new and exciting technology that we fail to realize the people in charge are more than happy to completely bury us with it.
> It's why I just can't understand the mindset of software engineers who are giddy about this brave new world. There really is nothing special about your expertise that an LLM can't achieve, theoretically.
They’re stupid or they’re already set up for success. The general ideas seems to be generalists are screwed, domain experts will be fine.
> domain experts will be fine
But I don't see how this holds up to even the slightest amount of scrutiny. We're literally training LLMs to BE domain experts.
I think these arguments tend to reach impasse because one gravitates to one of two views:
1) My experiences with LLMs are so impressive that I consider their output to generally be better than what the typical developer would produce. People who can't see this have not gotten enough experience with the models I find so impressive, or are in denial about the devaluation of their skills.
2) My experiences with LLMs have been mundane. People who see them as transformative lack the expertise required to distinguish between mediocre and excellent code, leading them to deny there is a difference.
Not sure that's what I was getting at. People in camp 2 don't think an LLM can take over the job of a real software engineer.
It's people in camp 1 that I wonder about. They're convinced that LLMs can accomplish anything and understand a codebase better than anyone (and that may be the case!). However, they're simultaneously convinced that they'll still be needed to do the prompting because ???reasons???.
I was thinking today that I need to pivot to making and selling shovels, but then other issue is is anyone going to need shovels in the future.
I was at 2) until the end of last year, then LLM/agent/harnesses had a capability jump that didn't quite bring me to be a 1) but was a big enough jump in that direction that I don't see why I shouldn't believe we get there soonish.
So now I tend to think a lot of people are in heavy denial in thinking that LLMs are going to stop getting better before they personally end up under the steamroller, but I'm not sure what this faith is based on.
I also think people tend to treat the "will LLMs replace <job>" question in too much of a binary manner. LLMs don't have to replace every last person that does a specific job to be wildly disruptive, if they replace 90% of the people that do a particular job by making the last 10% much more productive that's still a cataclysmic amount of job displacement in economic terms.
Even if they replace just 10-30% that's still a huge amount of displacement, for reference the unemployment rate during the Great Depression was 25%.
An enormous amount of domain expertise is not legible to LLMs. Their dependence on obtaining knowledge through someone else's writing is a real limitation. A lot of human domain expertise is not acquired that way.
They still have a long way to go before they can master a domain from first principles, which constrains the mastery possible.
> Why can't LLMs and agents progress further to do this software engineering job better than an actual software engineer?
Because a machine can never take accountability. If a software engineer throughout the entire year has been directing AI with prompts that created weaker systems then that person is on the chopping block, not the AI. Compared to another software engineer who directed prompts to expand the system and generate extra revenue streams.
> Because a machine can never take accountability.
A business leader can though.
> Compared to another software engineer who directed prompts to expand the system and generate extra revenue streams.
I think you're missing the point. Why can't an LLM advance sufficiently to be a REAL senior software engineer that a business person/product manager is prompting instead of YOU, a software engineer? Why are YOU specifically needed if an LLM can do a better job of it than you? I can't believe people are so naive to not see what the endgame is: getting rid of those primadonna software engineers that the C-suite and managers have nothing but contempt for.
why would it be a manager? hire a cheap intern to be the scapegoat, if the job market is bad enough. no reason for liability to fall on the suits
That's how things work already in every workplace where there's any real danger. The companies construes its policies and paper trail in bad faith so that the employees are always operating contradictory to policy/training and then when something happens blame can be shifted on them.
You can say this about every single role.
Why can't VCs feed your pitch deck into an AI and get a business they own 100%?
If the only thing you're paying for is compute time...
Some.people are claiming it's about taste. Why can't an AI learn taste?
It's not about whether they make mistakes (they do! although the exact definition of a mistake is nuanced), but whether they can take accountability if the software fails and millions are lost or people die. A large part of the premium paid on software engineers is to take accountability for their work. If a "business person" directs their agent to build some software and takes accountability -- congrats! They are also now a software engineer :)
The lines between a software engineer / business person / product / design and everything else will blur, because AI increases the individual person's leverage. I posit that there will be more 'software engineers' in this new world, but also more product people, more business people, more companies in general.