Pretty much every engineer needs to use Vim/vi when logged into any server, so from that point of view, this shouldn’t even be a question. I don’t think knowing how to use a modal editor in 2026 is a flex anymore, it’s just standard. But if you’re planning to commit to modal editing as a lifestyle, you should be using Helix, not Neovim.
It’s one of those tools that’s well designed and you don’t need a thousand line configuration file to be productive. The modal editing style is also an improvement over vim/neovim because you do selection -> action rather than action -> selection. Lastly, it’s written in Rust, which is not a plus purely because of that but because it’s a lot easier to contribute code changes to or tweak a modern Rust codebase.
Hard disagree. It is not an improvement - it is a deterioration.
Repeat (dot command .) is far more powerful and general thanks to operator->action.
Much better composability with counts, registers, marks and operators with operator->action
Operator Pending mode has some unique advantages for swipe edits that are painful in a select first paradigm. Ex: `d/foo<CR>`. No fast equivalent in Helix.
Also, if you really want, you can select in VIM and do your job too. Use visual mode with `v`.
Well, on the surface it may seem like there’s nothing being created of value, but I can assure you every company from seed stage to unicorns are heavily using claude code, cursor, and the like to produce software. At this point, most software you touch has been modified and enhanced with the use of LLMs. The difference in pace of shipping with and without AI assistance is staggering.
Why quantitative? I have friends at most major tech companies and I work at a startup now. You shouldn’t write by hand what can be prompted. Doesn’t mean the hard parts shouldn’t be done with the same care as when everything was handwritten, but a lot of minutiae are irrelevant now.
Because anything not quantitative is either “trust me bro” or AI marketing. Some of us are engineers, so we want to see actual numbers and not vibes.
And there are studies on this subject, like the MITRE study that shows that development speed decreases with LLMs while developers think it increases speed.
It's not clear what evidence you expect to see? Every major tech company is using AI for a significant % of their code. Ask anyone that works there and you will have all the evidence you need.
> Every major tech company is using AI for a significant % of their code
It shows, increased outages, increased vulnerabilities, windows failing to boot, windows task bar is still react native and barely works. And I have spoken to engineers at FANG companies, they are forced to use LLMs, managers are literally tracking metrics. So where is all this amazing new software and software quality or increased productivity from them?
You are measuring differently..they measure in how much stuff they ship. They don't measure if it's going to break , if it is not very maintainable, or how much it will cost to keep using the LLM I. The future. Remember its an extraction grift: buy now, pay later. Preferably after you have made the model an intrinsic part of the process. Oh snap, now we definitely need to bailout LLMs cause noone knows how this stuff works. Please help. Useful idiots all around. Classic case of not using their brains the way they evolved for.
I empathize with this cause circumstances often force us to move to a less than ideal location, but with everyone doing RTO again since 2 or 3 years ago, you slashed a huge percentage of the job opportunities out there.
I would say you can take opposite route as well. Become even more of a T-shaped engineer than you were before. For me that meant transitioning to vertical roles (i.e., performance engineering) rather than backend engineering. Sure, an AI can understand every level of the stack but reasoning up and down at every level of abstraction still has a human element to it (at least for now).
>http-request-validator is infinitely superior to “zephyr”
Is it though? How are you going to differentiate between 10 different variations of http-request-validator repos on GitHub? I think both have their downsides, but making the name super generic sounding is arguably worse. What I don't like about names like zephyr is that they're purely marketing-driven; people end up picking a zephyr over a http-request-validator purely because the name is sounds "cool" to them, even though http-request-validator might actually be the better library. And don't even get me started on people naming their projects random Japanese words.. it's like the equivalent of nicknames that Thai people use, which are just random English words like Ice Cream or Thank You.
Maybe the happy medium is, like you said, names that contain a hint as to what they do, like Actix (actor model). But TBH you kind of still have to look it up to know what it does, there's no way you're just going to infer that. Maybe later on it helps you remember what it was for though.
> don't even get me started on people naming their projects random Japanese words
But words help us learn. How many times do you notice a connection between some word from your childhood and an adult concept or place? And they're not random, people choose things because of many hidden reasons, but random is rarely the case.
Many of us love the story behind a word - as shown by many of the comments here reflecting on the cultural history behind our tool names.
IMO you should just transfer internally to a Deep Learning related team. That’s the path I’m taking, and while I wait for my new start date, I’m reading the important research papers etc. It shouldn’t take you as long as you think.
>Any software developer can access GitHub and StackOverflow - can they do it in a single shot as quickly as GPT?
I think the answer to this question is yes? If the developer can find a working example that they can copy paste (which is what GP is saying GPT-4 is essentially doing).
It’s actually just as likely for GPT-4 to have pasted a broken code example than a working one; it doesn’t understand if the code is correct.
>It seems like Asian cultures are much less likely to treat housing as an investment
Isn’t China one of the most prominent examples of using real estate as investment? There’s even whole ghost towns of apartment buildings that are constructed for this purpose.
yea all my Chinese (in China) relatives assume you should only invest in housing. And then when we tell them we have zero investment properties, they get really, really concerned for our future welfare and think that we're not doing very well.
No, domestic savers have capital controls and do not have the means to move money easily outside the country. The stock market also is not reliable in China as an avenue of investment. Government pensions are also small. So that mostly leaves real estate.
Evergrande Group is emblematic of the real estate industry’s trouble there. Property is 15-30% of Chinese GDP and much of it goes towards investment property.
I tend to be biased towards what Jeremy Siek himself markets as "Proven in the classroom" when it comes to book authors in CS. Many book authors lack this experience and simply write for themselves, which is ok, but can result in bad didactics. Good teachers and authors from academia are invaluable.
That's a great point about experience teaching the topic. (I've written a few articles where I certainly wished for that experience.)
I just wish textbooks didn't have their own bad tendencies: they have pablum as an attractor, because on average students just want to get through the class, not doing too much worse than average among the other students. Even without this problem, there's a more basic one: like with enterprise software, the decision to buy the book is not typically up to the user. "Will people actually want to read this on their own time?" is a strong driver of quality, even though it has pitfalls too.
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