When learning on my own, I I prefer to learn things that will last decades rather than years or months. Examples: Linux (bash, core utils, containers), CS (algorithms, data structures), compilers, other paradigms (functional, logic, oop), hardware architecture (logic gates, cpu design, assembly), encryption algos, Vim, etc.

Stuff that I think will only last a few years I will learn as needed on the job or at least on the clock.

I think the answer is obvious. Start looking for another job NOW. Work is out there, if you can code.

Depends on what metric you are looking and how. A warmed up JVM will run nearly as fast as Go or Rust, but many benchmarks fail to take JVM warmup into account and erroneously show Rust/Go as orders of magnitude faster, which is unfair. That said, it would be nice if warm up wasn’t required. Graalvm helps in that area, but now you have to do something special.

However, JVM startup time is terrible. It’s gotten better and there are ways to deploy a trimmed image, but it’s still not as good as most other solutions unless you go into annoying extra steps.

The JVM is a beast, and it’s very inefficient with memory esp strings.

You will lose the best candidates with an onerous coding challenge.

Our process, which has been heavily influenced by debate on r/experiencedevs on reddit involves a short phone screen, a 30 MINUTE coding challenge, a tech interview consisting of pair programming, and a non-tech interview with management. Very light.

The coding challenge is a FILTER only. It’s not to evaluate who to hire, but instead it’s to filter who not to continue interviewing.

You learn a lot during pair programming in a short period of time, including personality and team fit. We let them drive and we just watch and discuss. The assignment is to fix a bug, and refactor the code the caused the bug.

I wouldn’t consider the bugs chatgpt’s fault, per se. The same could happen by blindly copy/pasting from SO or a template Github project. If you are copy/pasting from anywhere, it’s even more important that you have good automated tests with good coverage, and that you take extra time to understand what you pasted.

One of the things I do is generate high level tests first, and then the implementation code. This way I know it works, and I can spend extra time reviewing the test code first to make sure it has the correct goal(s).

Learning is another matter. Personally, ChatGPT has greatly accelerated my learning of libraries and other languages. I’ve also used it to help me grok a block of complex code, and to automatically comment and refactor complex code into something more understandable. But it can also be used as a crutch.

Look into “Hexagonal Architecture”, similar/synonymous to clean/ports&adapters/onion. As someone else said, combine it with “Repository” pattern.

I use hex arch in front end and back end. It adds a couple of layers, but it makes apps much easier to test and maintain.

Yes, but it’s a very rare event. Maintaining state (form fields) makes it less of an issue. As I said, most deploys are at 4am at extremely low usage (usu zero), and even then a refresh is only needed if the backend has had breaking changes. A severe bug requires a mid-day deploy, but in my experience most severe bug fixes are only a few lines and therefore aren’t a breaking change so don’t require a refresh.

Our way wouldn’t work well if you had 24 hours of heavy load, but most apps I’ve written have been US-only with low nightly usage (HR, K-12 admin, power grid, medical).

Zero downtime deployments can get very complex for heavy usage apps, such as blue-green deployment.

We decided to avoid the complexity with some practical workarounds.

• Most deployments happen at 4am. “develop” branch merges deploy at 4am, and “master” branch merges deploy immediately.
• We force browser refresh if the front end detects the back end has had breaking changes. We attempt to re-populate form field values.
• During database migrations, we send 503 with Retry-After header in response to POSTs. Our client code knows to wait for that time and try again. If the time is too long, the user gets a friendly message that it will try again in X seconds. GETs are handled by an available read-replica, if possible.