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?


It’s disrespectful. I’m not, and will never be, a cog in a machine. If they want an assembly line then just run amok with LLMs. If they want an actual well thought out design, well.
Strongly this. If they don’t have time for me to ask questions, I don’t have time for them. An interview should be a two-way discussion where I can assess whether they are a suitable workplace for me.
Welcome welcome : https://lemmy.ml/c/antiai
Also https://lemmy.blahaj.zone/c/AntiAI
EDIT: fix 2nd link
Does anyone know how to add alt text to images? Or do we have to just include a separate comment?
When you make a post, there is a separate field to enter it.
Son of a biscuit… To the Docs!!!
500 internal error for me on blahaj.zone, curious.
yeah, i get that concern.
i don’t think the point should be “can this person produce code fastest with an llm.” that would be pretty bleak.
for me the interesting part is almost the opposite: can they still make good engineering decisions with AI in the loop? understand tradeoffs, reject bad suggestions, preserve the design, know when the generated fix is technically valid but wrong for the codebase.
if the assessment only rewards output, then yeah, it just turns people into cogs.
Yeah, you want to hire them. Take the time to learn about them. This reduces the dimensionality of any given candidate to 1.
isn’t that only true if you treat the result as the entire interview?
i’m thinking of it more as a way to create evidence for the conversation. not “you passed 8/10 checks so you’re good,” but show me how you approached something you hadn’t seen before and let’s talk through the decisions you made.
I’m going to request we part ways on this one.