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9 points n2d4 | 2 comments | | HN request time: 0.413s | source

As an applicant, I've personally had a mixed experience with take-homes. We're designing the technical interviews right now, and I thought I'd ask for some stories on exciting take-home tasks. We're looking for something that resembles the actual job, so we'll allow any tool (including AI and debuggers).

Also curious to hear about any bad ones you've done.

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csomar ◴[] No.42190447[source]
Take-homes are highly flawed. If you provide a small/short challenge that could be solved with AI, it'll not help you measure the candidate. On the other hand, if you ask for a month worth of work, no one is going to take that up. Automattic does pay for it, and that's the only way I can see this attracting eligible candidates.

At your stage (startup with 2 people), you are much better focusing with designing your product than designing an interview process. Hire someone you know or freelancers.

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muzani ◴[] No.42192081[source]
The trick is to set the bar higher so that you can only solve it with AI. Don't ask them to do hackerrank level questions. Ask them to solve problems where part of the solution is a hackkerrank level component.

Architecture level tests are a sweet spot for nos. AI is not good at this, but senior candidates are often very good at them. You can give them template architecture to start with or work on, something that AI is known to trip over. The only way to know what AI is tripping on is to use it.

If the candidate is better at using AI to write code than the team, bring them in!

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1. n2d4 ◴[] No.42193136[source]
This was also my thinking — if you ask ChatGPT to design a DB schema design it often looks good at first glance but is actually pretty bad.

If a candidate uses AI as a help to solve their task, yet the output is still good, great! It's their job to solve the problem, with whatever tools they have.

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2. OccamsMirror ◴[] No.42211317[source]
> if you ask ChatGPT to design a DB schema design it often looks good at first glance but is actually pretty bad.

What are some of the things you've noticed ChatGPT get wrong vis-a-vis schema design?