the more i looked into this, the more i realized this isn't really hypothetical anymore
companies like bloomberg and goldman are already experimenting with AI-assisted interviews where you're dropped into a codebase and expected to actually figure things out.
and tbh for actual engineers, that part isn't new. that's basically the job. you get a repo, you get a ticket, you find the relevant code, make the change, test it, etc.
what i'm more curious about is people who've mostly learned through AI/vibe coding and are now trying to prepare for interviews like this.
because prompting something into existence is very different from being dropped into a repo you've never seen before and having to know where to look, what to ask, whether the AI is wrong, and how to verify the change.
that's mostly what i've been building Groundwork around — unfamiliar repo, ticket, IDE, terminal, tests and an AI assistant.
i'm mainly trying to figure out whether this would actually be useful for interview prep though.
if you were preparing for this kind of interview, would you use something like that?
and what part would you actually want to practice?
Why though? AI is already part of how a lot of engineers work, and people are already using it to game traditional coding interviews. so trying to enforce “pretend AI doesn’t exist” feels a bit like giving a kid a calculator every day, then deciding the exam should test whether they can hide from the calculator.
i’d rather accept that the tool exists and test the part that still matters: can they reason, verify, catch bad output, understand the codebase, and make a safe change?
the AI shouldn’t be the thing being tested. the engineer’s judgment should be.
I like actually writing code. If the job you offer is being a glorified spellchecker for a clanker I'm just not interested.