So far, there is serious cognitive step needed that LLM just can’t do to get productive. They can output code but they don’t understand what’s going on. They don’t grasp architecture. Large projects don’t fit on their token window.
There’s a remarkably effective solution for this, that helps both humans and models alike - write documentation.
It’s actually kind of funny how the LLM wave has sparked a renaissance of high-quality documentation. Who would have thought?
good benefits and perks.
Didn’t they literally just introduce free coffee at the office post-pandemic?
Not to say that I would willingly choose to work at Amazon, but I do know the reason. It’s documented here: https://www.levels.fyi/companies/amazon/salaries/software-engineer
For anyone who opened this link in the GitHub mobile app and got confused, make sure to read from the very beginning of the comment thread - the mobile app only shows the very last comments, which cuts out the actual interesting part.
Complete hands-off no-review no-technical experience vibe coding is obviously snake oil, yeah.
This is a pretty large problem when it comes to learning about LLM-based tooling: lots of noise, very little signal.