Ask HN: Looking for a job after layoff and burnout. What should I focus on
5 pointsby jacAtSea3 hours ago5 comments
  • jacAtSeaan hour ago
    Thank you everyone for your kind comments.

    I didn't 'code' or read any CS related for almost a year. I agreed that now I didn't need more 'input' course material, but rather a 'learn and output' way to rebound.

    Since last October, I have been using github co-pilot(because its free, unemployed) to write little python project helper for my finance admin and other daily stuff. Initially I had to 'plan' with AI, broke tasks into smaller tasks and modified a few things. I haven't 'written' a single line of code since January as the model is so powerful they can step thru the changes and debugging. Granted this is a very small project.

    I aslo think contributions to the opensource projects would be helpful, for the sake of mental health and having 'real' practice.

    I am also thinking about might be start with some opensource project that I have used, e.g. like pyarrows, pandas, jupyter for python, and spark for scala. However, I think I am actually more interested in building a system together, rather than writing 'libraries'.

    Do you know how I can find one? I had tried searching via google but its not effective. I guess I don't know how.

    I have also tried to find 'volunteer jobs' but not very successful. Again, I think I might not know 'where' to look.

    I think my mind is still all over the place after the burnout so would need some brain power from the community.

    Thank you!

  • jacAtSea23 minutes ago
    I just want to add I am interested if there are any opensource or volunteer project contributing to medicine/health/public good area.
  • softwaredoug3 hours ago
    Most important thing: you need to absolutely feel rock solid working with an AI coding tool (Claude Code, Open Code, Codex). It's the biggest shift in the industry in decades, and has become more real in the last few months.

    People can debate the merits of LLM coding, but that's something every hiring manager will want you to know.

    • codingdave3 hours ago
      Only in some industries, and only on modern stacks. Those of us who work on legacy platforms in enterprise environments don't need it at all. On the contrary, the younger folks who use it can't get good info out and are trashing systems when they try.

      I do use basic LLM assistance, at a chatbot level. It is close enough and quick enough to give me a good head start when writing something new, and its problems are fairly quick to see and fix. But the fully baked tools are overkill for the value they offer, at least where I work.

      I'd say that you need to know your environment, know what AI tools are available, and know which ones work best in your particular slice of the industry. Because if I ever go back to modern stacks, I know the AI tolls will have far more value.

    • rkomorn3 hours ago
      100% agree. I'm currently out of tech (and not all that likely to return) but this is the one thing I feel certain about if I do decide to come back: there will not be a place for me as some sort of artisanal, non-"AI-first/fluent" engineer (whether I like it or not).

      Even in adjacent roles (design, PM, etc), I'm confident "how do you leverage AI?" will be one of the central evaluation questions.

      Edit: for emphasis, again: whether I like it or not.

  • ahmed-fathi3 hours ago
    A decade on systems that couldn't fail didn't teach you syntax it taught you consequences. That's rarer than any skill on your resume. You need harder problems and primary sources not more material. Kleppmann's Designing Data-Intensive Applications if you're going data. Ousterhout's A Philosophy of Software Design if you're going engineering. Then pick one system you respect, read its internals, and form opinions. The next level of growth doesn't come with a syllabus. You have to construct it yourself. That's not a gap. that's what senior actually means.
  • JSR_FDED3 hours ago
    Some good advice in the comments. Perhaps you could take some important open source systems in the data science space, and then use AI to help you deeply understand how they’re built and why they were built that way.

    That will give you hands-on with the new AI tools, and deepen your understanding of key open source systems - far more than going through online tutorials. That might even lead you to making some contributions to the projects, which in turn will help you answer the interview question “so what have you been up to?”