Because of AI, what it means to “not have all of the inputs” has changed as anyone can cut and paste a Leetcode problem to a chatbot and solve it.
I think we are going to iterate a bit to figure out a better signal than the typical coding interview. For junior engineers, I think coding questions will move towards MBA style problems when someone is given more of an open ended question with a codebase and you see what the candidate does without context to reduce the problem.
It would make sense to build your career in a single domain, since your built up expertize will transfer to other companies within that domain.
Far fewer switches will happen for seniors across domains.
From a career risk perspective, this is also the right answer. Domains disappear, though they frequently morph. Cross domain knowledge allows the individual to apply lessons and patterns they've learned elsewhere.
"A Little Bit of Slope Makes Up For a Lot of Y-Intercept"
https://www.youtube.com/watch?v=mE98Is1quwY
> Pick a radical idea
> Build it over a weekend:
What AI has done is that we can do 10x more work a week, while only delivering 2x to production.
Right now, there are 4 people (and me) working on the same idea in 5 different ways - we're all training small language models, the goal is to get smaller or fewer active parameters.
By next week, we'll have lost on 3 different approaches. I know my approach is a dead-end already, but I'm not ready to give up till the pencils down.
The people I work with are great, because they will see the better solution by the end of it, whether they proposed it or someone else did.
A couple of them have been in the industry for less than 5 years and I feel like their slope is better than mine, which means I'm going to have a good time when they're fully up to speed :)
On a side note, I did founded my startup this year, and had that bug of doubt back of my head, but oh well…
ispq•2h ago
It’s probably too soon to claim “death of the coding interview”.
anukin•1h ago
lubujackson•1h ago
Find an easy to understand product, like a step above a todo list app. Share a spec and have them code it in their own IDE using LLM. Focus on speed. Then have them extended it, adding some features. Then ask them to show you where certain functionality exists in the code and to explain the architecture of how it is built. Ask them where it is weak and could be improved.
That's it, that's the interview. SWEs are getting quite good at the prompting, but fast navigation and understanding of the code is the key.
Anyone that can effectively translate a spec to code with minimal handholding shows product awareness. Anyone who can produce a working app can prompt AI reasonably. Anyone who can revise their design on the fly to support new features is someone with flexible thinking and some humility. Anyone who can navigate and explain what AI built is someone that understands how to build a mental map of a codebase. Anyone who can do all of this in an interview is someone who can handle pressure, work quickly and communicate.
You are welcome to keep trotting out linked list traversals and sliding window problems if you like, but leetcode is now (and maybe always has been) about culture fit more than an ability to build software.
biggestriverman•56m ago
For interviews where candidates are using AI I think you can supercharge this approach, but I do not think there is value in turning it into a code navigation puzzle as there is little value in that can be evaluated in the ~45 min you have for coding in a 1 hr interview slot. Ultimately in many software engineering jobs these days we need to understand how to build quality systems without looking into the underlying system except as necessary. I am not sure how to best evaluate this judgement in an AI assisted interview