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The stated reason was that they wanted to understand my ability to solve a problem and my thought process when faced with their problem. Having run technical in
by verandaguy 2y ago
The stated reason was that they wanted to understand my ability to solve a problem and my thought process when faced with their problem. Having run technical interviews in the past, I completely agree with the reasoning.
While I don't use it, I'll grant you that AI is good at solving small, repetitive, tedious problems; stuff that's maybe a bit too domain-specific to be widely available in a library, but that's consistently subtly different enough that you have to sink time into either making different implementations or trying to generalize.
AI is generally going to be poor at solving novel problems, and while that's something that you can never really use in an interview for a variety of reasons, I can send you a problem that's likely new to you and see how you tackle it.
I'll also admit that there's not a single good way to do that as it is. Technical interviewing is more of an art than a science, and it's difficult to get really good signal from an interview, generally speaking.
- williamcotton 2y agoIf you're experienced with how to use an LLM they can be very good at helping with novel problems and much more than boilerplate. I've been able to tackle problems that would have otherwise taken up too much time and effort between my jobs as both expert witness for software related Federal lawsuits and as a father of two young children. Here's just a sampling of what I've accomplished since I started using these tools: A convolutional neural network trained using PyTorch to predict the next chord (as tablature) on a guitar based on image data. Includes labeling software for the image data as well as an iOS app for hosting and running the model. A web framework written in C using clang blocks for the DSL, per request memory arena, and complete JSON-API compatible ORM, JWT auth, and enough sanitizers and leak detect to make your head spin. A custom CLI DSL modeled somewhat on AWK syntax written with Python Lex Yacc for turning CSV data into matplotlib graphics. A custom web framework written in F# that compiles to JS with Fable. LLMs helped with looking up documentation, higher level architecture, fixing errors, and yes, plenty of boilerplate! All of this being said, I brought with me almost 30 years of experience writing software and a pretty good idea high level of how to go about building these things. The devil is in the details and that's where the LLM was most useful.
- verandaguy 2y agoSure, but none of what you mentioned actually solves novel problems. It's a helpful tool, sure, but that was never up for debate. Beyond that, if it helps you spend more time with your family while still being good at your job, that's always a win.
- williamcotton 2y agoI'll agree that I was the one ultimately responsible for solving the novel problems!
- 9dev 2y agoMost people don’t actually work on novel problems though. They build CRUD web apps. Copilot shines there.
- SoftTalker 2y agoAnd leetcode interview problems are not novel either. They are formulaic, you just have to know the formulas.
- tchalla 2y agoThe ability to solve novel problems is tested like a marathon, not like a 100m race.