To be honest, I don't think the space between GPL/MIT and commercial closed source is explored enough. I'm aware there's a few examples of things in between, but they are not common knowledge and they don't satisfy everyone. It is not a space that is easy to search online for established wisdom and comparisons in.

I imagine because we're talking about a subcategory of "bad guys" who still like to stay within the confines of the law (supposedly at least).

Does that entail that LLMs are not in fact erasing our societal voices, only making it easier to adopt bland-corporate en-mass?

https://rmoff.net/2025/11/25/ai-smells-on-medium/

He doesn't link many examples, but at the end he gives the example of an author pumping out +8 articles in a week across a variety of topics. https://medium.com/@ArkProtocol1

I don't spend time on medium so I don't personally know.

Zig team ought to probably write about it in that manner.

Definitely looks like it.

Remote: Prefered, but open to in-person (depending on offer and location)

Technologies: Julia, Python, Rust, CUDA, C#, C, valgrind, gdb, SciML, low level performance profiling, scientific computing, Linux admin and scripting, Docker, ...

Resume: https://omar-elrefaei.github.io?source=HN (pdf upon request)

Email: omar02295+hn [at] gmail

I'm an experienced Julia developer with an appetite for performance challenges.

I'd be extra interested if the work involves any of the following:

  - Assessing different parallelization or threading strategies
  - Increasing testing coverage to help with maintainability and robustness
  - Cleaning up prototype code to prepare for production or publishing as a package
  - Contribute to open source dependencies

I'm a swift learner, if you get me excited about your product/project, I'm confident I can pick up whatever technologies you use quickly.

I can help if you're looking for Julia expertise to help with any of the following:

  - Investigating long compilation or start-up times
  - Profiling and identifying performance bottlenecks
  - Low-level performance optimization for your simulation code
  - Assessing different parallelization or threading strategies
  - Increasing testing coverage to help with maintainability and robustness
  - Cleaning up prototype code to prepare for production or publishing as a package
  - Contribute to a dependency upstream to ease a pain point in your use case

Email: omar02295+hn@gmail.ca

I'm an experienced Julia developer with a enthusiasm for solving performance and optimization challenges.

I can help if you're looking for Julia expertise to help with any of the following:

  - Investigating long compilation or start-up times
  - Profiling and identifying performance bottlenecks
  - Low-level performance optimization for your simulation code
  - Assessing different parallelization or threading strategies
  - Increasing testing coverage to help with maintainability and robustness
  - Cleaning up prototype code to prepare for production or publishing as a package
  - Contribute to a dependency upstream to ease a pain point in your use case

  - Rewriting or redesigning from R/MATLAB to Julia/Python/Rust.
  - Having performance problems with your Python, Rust, MATLAB, or C code.
  - Want to investigate if leveraging GPU compute (CUDA) could be useful for your computations.

Think I might be able to help? Shoot me an email and let's find out.

Email: omar02295+hn@gmail.ca

treesitter tech always seemed cool, but never felt I had access to it on my finger tips. one such tool is https://github.com/Wilfred/difftastic (semantic diff)

will definitely be trying this out.

After getting used to it with Julia I found it really jarring to go back to plain Jupyter (when I need python) where I have to keep re-executing the cells.

This is going to make that much less painful.

He's gonna have a wild career.

But I guess theoretically someone could design one (╯°□°）╯ ┻┻ they are releasing hardware and software interface docs on github.