I also find that because the web version is worse in order to push you to download the app, it is a good way to not get sucked into endlessly scrolling. Get in, do what you need, and get out because of bad experience.
At work I mostly use claude code and chatgpt web for general queries, but cursor is probably the most popular in our company. I don’t think we are "cooked" but it definitely changes how development will be done.
I think the process of coming up with solutions will still be there but implementation is much faster now.
My observations:
1. What works for me is the usual, work iteratively on a plan then implement and review. The more constraints I put into the plan the better.
2. The biggest problem for me is LLM assuming something wrong and then having to steer it back or redoing the plan.
3. Exploring and onboarding to new codebases is much faster.
4. I don’t see the 10x speedup but I do see that now I can discard and prototype ideas quickly. For example I don’t spend 20-30 minutes writing something just to revert it if I don’t like how it looks or works.
5. Mental exhaustion when working on multiple different projects/agent sessions is real, so I tend to only have one. Having to constantly switch mental model of a problem is much more draining than the “old” way of working on a single problem. Basically the more I give in into vibing the harder it is to review and understand.
I guess it is strange to me, as you usually only hear about bad stories. So I was expecting it to be much worse.
I agree, as long as companies evaluate candidates by a combination of different tests, this should be the best for everybody.
Two companies for which I went through the whole interview process had 5-7 different interviews, and only one of them was leetcode-style problem. So even if somebody fails at leetcode problem they should excel at something else.
I find Leetcode discussions strange. I recently changed jobs so I was preparing by doing some Leetcode problems. The actual problems I was asked during the interview process were very simple compared to what I expected. Interviewers even explicitly stated that they wanted to see how I think, and the solution didn't even have to compile. So in my experience the whole idea that «Leetcode is harmful» is overblown a little bit.
To me the value of coding interviews are knowing enough algorithms/data structures to apply and adapt them to problems, being able to quickly sketch out your idea, and explain trade-ffs.
I think it depends on your usecase. Check if you will actually benefit from pro/max. I'm willing to bet regular M1 is fine for the majority of people.
I got M1 air 16gb around 3 month ago and it works great, although it's not my only laptop. I was choosing between air M1 16 gb and 14" M1 pro 32 gb, and the price difference for additional ram, extra ports and screen size didn't make sense to me.
For my usage so far yes, dev VM has around 60 GB, others around 30-40 wich is plenty to install everything. For Nextcloud I mount NFS volumes from TrueNAS which has 2 TB HDD.
I build myself a home server last year, without any particular plan just to try it. Specs: Ryzen 7 3800X, 32 GB ECC RAM, 2 TB HDD and 500 GB SSD. I use it to run PLEX, Torrent, TrueNAS, WireGuard, NextCloud, and my side projects.
The server runs Proxmox, some of these services are separate VMs, others are running as Nomad jobs. I also have a dedicated development VM which I can access remotely through the VPN wich is pretty nice.
I used to work on similar project around 4 years ago, It was a Java Swing application that received all the data about the layout from the backend. The system was around 14 years or so, they implemented themselves most of the things like IoC container, custom XML markup for constructing UI, custom Swing elements.
It worked surprisingly well. The thing that impressed me the most was the amount of documentation which even included tutorials on how to make new UI elements, Screens, etc.
I got myself Thinkpad X1 Extreme last year with 16 GB RAM, 256 GB NVME SSD, 8th gen i7 running Linux, so far I'm very satisfied. It can be upgraded fairly easily, I already installed additional 1 TB SSD, and will probably upgrade RAM down the road.
On Linux apart from switching between dedicated Nvidia GPU and integrated, everything worked out of the box for me.