Did GitHub Copilot increase my productivity?

One thing I've found about Copilot is that it introduces me to novel ways to solve problems and more obscure language features. It makes me a better coder because I'm constantly learning. But do I want to be spending my time learning or do I want to make that deadline that's coming up?

I think, their ROI model is much different and subtle. Few decades back, everything ran on-premises and costed ok ... Then a huge investment had been shovelled into fancy frameworks and pushing strange paradigms (microservices, distributed systems, monoliths whatever flavour works for the tech giants) so now people just put together whatever and needs massive _cloud_ to run basic things that used to run on few MHz devices.

In the end, the ROI is NOT from these models, those are just gambles in case one actually becomes a king maker. The actual ROI is from the _cloud_ where innocent people will rent expensive hardware to try and utilise these models and funneling wealth to the actual investments(cloud operators, hardware vendors) which are already part of portfolio of these investors. Basically, $1MM invested in random shiny startup will inspire other shiny startups to also spend similar in race to become unicorn, all the while the cloud operators and GPU vendors are laughing to the bank preparing their shareholders(usually same investors) dividends.

My problem is running into it's limitations, mostly around resources. I have tried giving it larger tasks and it takes bloody forever.

"Given this unstructured data, create CSV output for all platforms, with each line containing the manual, and model, ignoring the text in parenthesis."

Works great except for God-awful performance and stopping half way through. I had to break out each section and paste it into the prompt and let it work on small pieces. We need to get to the next level with this, especially for paying customers.

More concerning is that I see a clear pattern in smaller companies of hiring seniors and turning them loose with AI assistants instead of hiring junior devs. The prospect is attractive to nearly every stakeholder and the propensity to put off hiring "until next quarter" in light of this is a constant siren song. There is a lot of gravity pulling in this direction with the short-term thinking and distractions that are thoroughly soaked into the business world these days. Supposedly, one third of Gen Z (20-25 yrs old) are sitting at home, up from 22% in 1990.

I'm one of those seniors happily putting off hiring, but I find the situation and it's wider impact on the future very unnerving.

Traditionally, though, SQL generation was known as query building. The query was executed via database engine or database driver, depending on the particulars. ORM, as the name originally implied, was the step that converted the relations into structured objects (and vice versa). So, yes, technically if you maintain your data as tuples end to end you are not utilizing ORM. Lastly, there once was what was known as the active record pattern that tried to combine all of these distinct features into some kind of unified feature set.

But we're in a new age. Tradition has gone out the window. Computing terms have no consistency to speak of, and not just when it comes to databases. Indeed, most people will call any kind of database-related code ORM these days. It's just funny that ORM no longer means object-relational mapping.