There's a joke that's not entirely a joke that the job of a Google SWE is converting from one protobuf to another. That's generally not very fun code, IMO (which may differ from your opinion and that's why they're opinions!). Otoh, figuring out and writing some interesting logic catches my brain in a way that dealing with formats and interoperability stuff doesn't usually.
We're all did but we all probably have things we like more than others.
But those aren't the stories you hear about with people coding with AI, which is what prompted my response.
I do agree that this:
> What’s gone is the tearing, exhausting manual labour of typing every single line of code.
seems more than a little overblown. But I do sympathize with not feeling motivated to write a lot of glue and boilerplate, and that "meh" often derails me on personal projects where it's just my internal motivation competing against my internal de-motivation. LLMs have been really good there, especially since many of those are cases where only I will run or deal with the code and it won't be exposed to the innertubes.
Maybe the author can't touch type, but that's a separate problem with its own solution. :)
I've written professional code in production for the past 15+ years in VB, C# (MVC2/MVC3 + Razor), Php(Yii, Yii2, Symfony), Perl, Python(Flask, Cherrpy), Java(Spring MVC, Spring boot, JSF, J2EE), Golang, Rust, Ruby. I've worked on build/ci pipelines from Jenkins, CircleCI, Github, Gitlab, Teamcity, etc. I've had to deploy/manage infrastructure from bare metal to the cloud with Ansible, Puppet, Saltstack, Terraform, Cloudformation. I've had to run on MySQL, Postgres, Mariadb, SQL Server and use ActiveMQ, RabbitMQ, Kafka, SQS, SNS, MSK, Kinesis (of all flavors). I could literally keep going and going and going.
I'm tired. It's way easier to prompt than keep track of all this shit at this point. I don't need to know how to implement $feature or $tool in each and every framework, I'll let the machines worry about that.
This also just feels like we're solving the wrong problem. Using AI doesn't fix any of it, it just makes it easier to make the problem worse faster.
I guess if you specialise in maintaining a code base with a single language and a fixed set of libraries then it becomes easier to remember all the details, but for me it will always be less effort to just search the names for whatever tools I want to include in a program at any point.
Similar to how you outlined multi-language vs specialist, I wonder if "full stack" vs "niche" work unspokenly underlies some of the camps of "I just trust the AI" vs "it's not saving me any time".
