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?
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.
That’s the easy part of the job. The hard part is getting the business to make a god damned decision without three months of fucking around and executives asking if we can “do ‘it’ with AI”, long before anyone has established what “it” is.
and the non-technical execs are usually the worst for it 😭 to them AI is basically a magic button, so somehow you’re expected to ship 100x faster on something nobody has even properly defined yet.
but that’s more the chaos you learn to survive once you actually have the job.
i’m more focused on the bit before that, what people are actually going to be tested on to get through the interview in the first place, especially with the market being this rough.
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.
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.
I’d start by actually learning how to code.
yeah, obviously 😭
i’m not saying AI replaces knowing how to code. i’m more interested in what comes after that baseline can you actually work through an unfamiliar repo, use AI without blindly trusting it, and make a safe change?
can you actually work through an unfamiliar repo, use AI without blindly trusting it,
That’s twice as much work as simply looking at the damn repo, because then you’ll have to understand the repo and whatever the fuck the AI shat out
Just make the changes without using AI???
you absolutely can, and honestly you probably should be able to.
my point is more that if the interview explicitly allows AI, then using it well becomes part of the skill being tested too. not “let AI do it for me,” but knowing when it helps, when it’s wrong, and when it’s faster to just do the thing yourself.
I’ll treat it as a trick question and decline to use AI anyway. If it turns out they actually want to me to use AI, I withdraw the application.
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.
Is this just an ad? Or is there a repository somewhere that I can’t find?
yeah, the platform exists.
this post is more me trying to validate the idea and hear what people would actually want from something like this before i over-engineer it.
i can share the link if you want to try it.
To a repository? Might be good to put that in the post itself, honestly.
this is the wrong use if llms. they cant make the call on who is a good fit for your team. i never used quiz interviews when hiring. i always asked: tell me about your last project or a project you are proud of and let there answer guide the questions. what tech are you excited about?
i think we’re talking about slightly different things, i’m not suggesting the llm should decide whether someone is a good engineer or a good fit. i wouldn’t trust that either.
the interesting part to me is putting someone in the environment they would actually work in, repo, ticket, tests, AI available and seeing how they reason through it.
do they understand what the AI gives them? question it? verify it? know where to look when it’s wrong?
the conversation afterwards can still be the most important part. the repo just gives you something concrete to have that conversation about.
ok i re-read. i see. i still never gave code based interviews. i found that people who could go i to theor projects with depth had a solid understanding.
yeah, i get that. but i think what i’m more interested in is problem navigation.
once someone joins a company, they’re not always going to be working on things they’ve already seen before or can talk about from past experience. they’ll get dropped into unfamiliar systems, weird bugs, new constraints, and have to figure out what matters.
so part of the value to me is seeing how someone behaves when they don’t already know the terrain, where they look first, what assumptions they make, how they narrow things down, and how quickly they build enough understanding to make a good decision.
i think that’s probably part of why leetcode-style interviews survived this long too. for all their flaws, they give you a problem the candidate hasn’t necessarily seen (sometimes) in that exact form and let you watch how they navigate it.
