There are two pinnacles in a traditional CS program - building a compiler and a DBMS. They are umbrella topics that prepare you for building pretty much any kind of software.
If you came to programming because you liked computers you'll find building an interpreter a fascinating topic in its own right. Building a compiler frontend is comprehensible and reading a modern/practical textbook (e.g. based on ANTLR or whatever is the latest parser generator in the wild) will illuminate so much for you.
You're highly unlikely to find a job with this skillset though. There are very few companies that do it, very small core teams, and there's competition with PhDs from top tier schools. The current leetcode fashion will ignore your niche knowledge right off the bat. So from this perspective the utility of knowing this stuff has always been a grey area regardless of the AI.
If you like money more than you like computers surely aim for an MLE position instead of SE/DE. But that's kind of a selective club too I imagine.
If you came to programming because you liked computers you'll find building an interpreter a fascinating topic in its own right. Building a compiler frontend is comprehensible and reading a modern/practical textbook (e.g. based on ANTLR or whatever is the latest parser generator in the wild) will illuminate so much for you.
You're highly unlikely to find a job with this skillset though. There are very few companies that do it, very small core teams, and there's competition with PhDs from top tier schools. The current leetcode fashion will ignore your niche knowledge right off the bat. So from this perspective the utility of knowing this stuff has always been a grey area regardless of the AI.
If you like money more than you like computers surely aim for an MLE position instead of SE/DE. But that's kind of a selective club too I imagine.