[marxism]

My reading is this isn't for random engineers but experienced performance engineers with optimized toolchains who can tackle this efficiently. For someone with the right setup, this is likely straightforward work.

It's similar to job descriptions written for specific candidates they plan to hire. The question shouldn't be "why is this bounty so low?" but "what toolchain makes $20K reasonable for someone?"

Performance work in my experience has been largely organizational friction: running projects in various conditions, collecting evidence maintainers accept, maximizing that limited slice of attention people give my CLs, getting compiler improvements merged. These coordination tasks have become much easier to automate with LLMs (e.g., analyzing maintainer comments to understand cryptic 1 line feedback, what are they actually looking for, what do they mean).

My guess is there's an engineer who's either optimized their feedback cycle to under an hour through specialized tooling (more arrows) or is much better at finding the right signal the first time (more wood). I'd like to understand what tools enable that efficiency.