[sanderjd]

Continuing to learn new ones, like what?

To me, "how do contemporary AI systems work and interact with contemporary hardware and how can I best take advantage of their capabilities?" is the set of skills that are worth learning at this moment.

What else is there? New / additional programming languages? New / additional database systems? frameworks? orchestrators? cloud provider / infra tooling? architectural patterns?

I dunno, all of this seems really boring and "been there done that" to me at this moment in time!

[not_kurt_godel]

Yes, that all tracks, and all of those skills are worth maintaining and improving. Great to tinker with LLMs locally hands-on to learn, and having a powerful enough machine to enable that to a reasonable degree is just one of many reasons why it's worth it. I'm just saying that IMO "how can I best take advantage" lands firmly in the bucket of only cloud-hosted frontier models being worth my time. I would speculate that holds true for a large portion of the wider HN audience but YMMV of course.

[sanderjd]

Maybe. I felt this way a year ago and definitely two years ago. But now my sense is that it's played out at this point, and the valuable thing to build expertise on now - precisely because I think it's coming rather than here - is local / open weights / hybrid models and harnesses.