When I hired people I looked for enthusiasm and passion. Devoting some time into things she's interested and personally invested in will make her stand out.
Even a fun COBOL program might make all the difference.
Try focusing on software architecture and organisation/factoring since AI is an incredible force multiplier for these skills currently and foreseeably.
The most important skills post-AGI is a "proof of a track record":
* Showing open-source contributions to respected projects shows you know how to code, reasoning your patches in code-reviews and the ability to understand how to solve the problem which is a very strong signal.
* Building something that makes a significant amount of money, makes getting hired optional and shows you are aware of market demand, identifying a problem and being able to monetize it.
* Publishing research papers proves your ability to go beyond academia and to build on top of other's research areas to advance the field or come up with something original to show in conference meet-ups (NeurIPS, SIGGRAPH, CVPR)
Unless it is a research career, the degree and where it came from matters far less.
When I hired people I looked for enthusiasm and passion. Devoting some time into things she's interested and personally invested in will make her stand out.
Even a fun COBOL program might make all the difference.
Try focusing on software architecture and organisation/factoring since AI is an incredible force multiplier for these skills currently and foreseeably.
The most important skills post-AGI is a "proof of a track record":
* Showing open-source contributions to respected projects shows you know how to code, reasoning your patches in code-reviews and the ability to understand how to solve the problem which is a very strong signal.
* Building something that makes a significant amount of money, makes getting hired optional and shows you are aware of market demand, identifying a problem and being able to monetize it.
* Publishing research papers proves your ability to go beyond academia and to build on top of other's research areas to advance the field or come up with something original to show in conference meet-ups (NeurIPS, SIGGRAPH, CVPR)
Unless it is a research career, the degree and where it came from matters far less.