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.

We're literally trying to build an intelligence to replace us.

The biggest failure of imagination, I think, is the assumption we'd use humans for most (or *any) of these jobs--for example, the work of the haruspex is better left to an LLM that can process the myriad of internal states (this is the mechanical interpretation field).

My implementation speed and bug fixing my typed code to be the bottleneck - now I just think about an implementation and it then exist - As long as I thought about the structure/input/output/testability and logic flow correctly and made sure I included all that information, it just works, nicely, with tests.

Unix philosophy works well with LLM too - you can have software that does one thing well and only one thing well, that fit in their context and do not lead to haphazard behavior.

Now my day essentially revolves around delivering/improving on delivering concentrated engineering thinking, which in my opinion is the pure part about engineer profession itself. I like it quite a lot.

Spoilers for "How I Met Your Mother" ... but there's a character who has that kind of job, as a legal meat-shield. Now, ~10 years after airing, this funny clip feels like it would only need slight adjustments.

https://www.youtube.com/watch?v=8u62HptZ6TE

If you go fast, you are bound to come across AI bugs later. Then you ultimately slow down to fix them. Which takes more time.

That black box will keep evolving. The AI interpreter will have to keep catching up with it.

Anyway: The new job types might seem overspecialized now but history shows us this is indeed what happens as new industries open up. I think these predictions look quite solid.

"Specialization is for insects." (Or for someone pushing the boundaries of human knowledge.)

Someone noting it is unavailable in the UK.

Someone posting an archive.is link.

Someone asking why the above posted an archive link to a static site.

An answer that it is because the content is otherwise unavailable in the UK.

Do we really need to see this every single time?

I realize I am also not adding to the real discussion now as well, but Jesus Christ, this is irritating. Can we get a new rule that an author posting their own content, knowing it is unavailable in the UK, has to post their own archive link and explain why they're doing so as part of the submission?