Unfortunately real life problems involve a lot of context and introducing that to interviews is hard.
It either requires a long conversation where someone might lose track, or involve writing a large ish code base and getting them to work on that (which is a lot of work, and once again they don’t have context).
In my experience if a problem simple enough to be completed in an hour, it’s simple enough for AI.
- We're a close knit team of 5 in Sydney (plus several international)
- We're profitable and growing
Job details:
- Full stack (python django backend, react and typescript frontend)
- 3rd engineer - this means you will have a lot of freedom and autonomy and the ability to work on a much broader set of tasks than most other companies
My partners family plays a version of Canasta where you start dealing by picking up all the cards you think you’ll need to deal and if you picked it perfectly you get another 100 points.
It’s a great addition to the game and makes it a positive to be the dealer.
I'm very interested in the UX decisions they make here. Is it just going to be ChatGPT with a Bing logo or will it be able to intelligently decide when a search engine is better? Will it give results in natural language?
If they sometimes do normal search instead at least that answers how they'll make money
When I was younger I worked at a local supermarket and later at a sports store - turns out customers at the sports store were almost exclusively nice.
Not a huge sample size as I only worked at the one store but from talking to others seems like the number of degenerates is waaaay lower when people play sports
I’ve been working very closely with one over the past few months and the biggest improvement is clearly defining terms and making sure we always stick to them
We realised we were using the word design for like 4 different things and often two or more interpretations were valid
In my experience if a problem simple enough to be completed in an hour, it’s simple enough for AI.