For example, it's common for people new to english to use adjectives in a different order than what's common (opinion, size, age or shape, colour, origin, material, purpose)

en.wikipedia.org/wiki/Adjecti...

I worry that genuine applicants who don't have english as a first language will be caught in the crossfire of the arms race between LLM-written resumes and LLM-detectors (whether human or automated).

I don't know if humans can tell the difference between AI-generated and human mistakes.

What are some good "tells" that someone knows what they are talking about on observability 2.0? What are the kinds of things that people deep in this space are excited about that are strange to those on the outside/edges?

High performance computing and its applications to simulations deserve a bit more love. Computational Fluid Dynamics (CFD) has many applications in aerospace and other industries and has interesting performance demands on CPU, memory bandwidth, and more.

Did you feel that was influenced by trying to find work? I can sympathise with a frustrated grad who can't quite match what they learned in class to the shiny new tech/frameworks/etc. that is asked for in job ads.