I'm an experienced SSE and I'm about to hunt for a new job for the first time in a few years. I've so far been able to avoid most AI use, with the exception of testing out some code completion with copilot a couple years ago.
Basically every job listing I'm seeing expects some level of AI adoption ("we'll set you up with either Claude or Copilot, so much choice!") so I figured it's time.
What's the best way to get an intro to these tools? I'm curious how people are actually using them in their workflows successfully. I want to give it a fair shake and form my first-hand opinion on these things as tools.
EDIT: I'd also like to hear from those downvoting this post.
I can't give you much advice about Claude or Copilot since I refuse to use either, but I do use open weight models which I can run on my own hardware.
If you're interested in exploring LLMs from that angle, download llama.cpp and some models that'll fit on whatever hardware you've got and start poking at it. I got started a few months back, and it's been an interesting experience. llama-server (which is one of the tools that comes with llama.cpp) includes a web UI. You can also use llama-cli on the command-line (but that gets old pretty quick).
Gemma and Qwen are the two most popular open weight model families right now since they're small enough to run on local hardware and give good enough results that they can be useful.
I've found them to be useful for:
If you try to do batch processing with them, it's helpful to think about them like a flaky distributed system -- i.e. use timeouts, retries, error handling mechanisms that account for invalid output, etc.
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