Ultimately it's still the same thing - problem solving in specific domains.
Languages and frameworks and libraries and IDEs and agent systems are all - in the end - just some new tooling, they were always the lower-hanging fruit. Cool, fancy, do novel magic, open paths previously unknown or thought impractical or unrealistic, but still - it's just some new ideas and instruments and ways how to use those efficiently - all to write programs that match our needs and fulfill our expectations, making things happen.
Nothing about underlying principles of software engineering had changed - some methods became more feasible, ML got really hot (and very rightfully so), but overall software projects are still software projects. Just recently I've looked at some machine-assisted software development courses and it was just the same good old "use your head, try your best to do things right or bad things happen, and here are the important gotchas of the day that you're best to constantly stay mindful about" material, just with "the machine can very rapidly produce code now, but it's not your code until you comprehend it" flavor, followed with a showcase of capabilities and features of newest tools on the market.
In my understanding, the eternal hustle still stays the same: find a passion, get into something, keep up with others, continuously learn new stuff, try to think something of your own and share, try to produce valuable things that others are willing to pay for, repeat until you can't anymore. Current state of "AI" doesn't disrupt this at all. Although it pushes the tempo up, and the times are stressful even without it.
Languages and frameworks and libraries and IDEs and agent systems are all - in the end - just some new tooling, they were always the lower-hanging fruit. Cool, fancy, do novel magic, open paths previously unknown or thought impractical or unrealistic, but still - it's just some new ideas and instruments and ways how to use those efficiently - all to write programs that match our needs and fulfill our expectations, making things happen.
Nothing about underlying principles of software engineering had changed - some methods became more feasible, ML got really hot (and very rightfully so), but overall software projects are still software projects. Just recently I've looked at some machine-assisted software development courses and it was just the same good old "use your head, try your best to do things right or bad things happen, and here are the important gotchas of the day that you're best to constantly stay mindful about" material, just with "the machine can very rapidly produce code now, but it's not your code until you comprehend it" flavor, followed with a showcase of capabilities and features of newest tools on the market.
In my understanding, the eternal hustle still stays the same: find a passion, get into something, keep up with others, continuously learn new stuff, try to think something of your own and share, try to produce valuable things that others are willing to pay for, repeat until you can't anymore. Current state of "AI" doesn't disrupt this at all. Although it pushes the tempo up, and the times are stressful even without it.