I'm glad to see this. I'm happy to plan to pay for Zed - its not there yet but its well on its way - But I don't want essentially _any_ of the AI and telemetry features.
The fact of the matter is, I am not even using AI features much in my editor anymore. I've tried Copilot and friends over and over and it's just not _there_. It needs to be in a different location in the software development pipeline (Probably code reviews and RAG'ing up for documentation).
- I can kick out some money for a settings sync service.
- I can kick out some money to essentially "subscribe" for maintenance.
I don't personally think that an editor is going to return the kinds of ROI VCs look for. So.... yeah. I might be back to Emacs in a year with IntelliJ for powerful IDE needs....
I'm happy to finally see this take. I've been feeling pretty left out with everyone singing the praises of AI-assisted editors while I struggle to understand the hype. I've tried a few and it's never felt like an improvement to my workflow. At least for my team, the actual writing of code has never been the problem or bottleneck. Getting code reviewed by someone else in a timely manner has been a problem though, so we're considering AI code reviews to at least take some burden out of the process.
AI code reviews are the worst place to introduce AI, in my experience. They can find a few things quickly, but they can also send people down unnecessary paths or be easily persuaded by comments or even the slightest pushback from someone. They're fast to cave in and agree with any input.
It can also encourage laziness: If the AI reviewer didn't spot anything, it's easier to justify skimming the commit. Everyone says they won't do it, but it happens.
For anything AI related, having manual human review as the final step is key.
IMO, the AI bits are the least interesting parts of Zed. I hardly use them. For me, Zed is a blazing fast, lightweight editor with a large community supporting plugins and themes and all that. It's not exactly Sublime Text, but to me it's the nearest spiritual successor while being fully GPL'ed Free Software.
I don't mind the AI stuff. It's been nice when I used it, but I have a different workflow for those things right now. But all the stuff besides AI? It's freaking great.
I found the OP comment amusing because Emacs with a Jetbrains IDE when I need it is exactly my setup. The only thing I've found AI to be consistently good for is spitting out boring boilerplate so I can do the fun parts myself.
I always hear this "writing code isn't the bottleneck" used when talking about AI, as if there are chosen few engineers who only work on completely new and abstract domains that require a PhD and 20 years of experience that an LLM can not fathom.
Yes, you're right, AI cannot be a senior engineer with you. It can take a lot of the grunt work away though, which is still part of the job for many devs at all skill levels. Or it's useful for technologies you're not as well versed in. Or simply an inertia breaker if you're not feeling very motivated for getting to work.
Find what it's good for in your workflows and try it for that.
Highlighting code and having cursor show the recommended changes and make them for me with one click is just a time saver over me copying and pasting back and forth to an external chat window. I don’t find the autocomplete particularly useful, but the inbuilt chat is a useful feature honestly.
I'm the opposite. I held out this view for a long, long time. About two months ago, I gave Zed's agentic sidebar a try.
I'm blown away.
I'm a very senior engineer. I have extremely high standards. I know a lot of technologies top to bottom. And I have immediately found it insanely helpful.
There are a few hugely valuable use-cases for me. The first is writing tests. Agentic AI right now is shockingly good at figuring out what your code should be doing and writing tests that test the behavior, all the verbose and annoying edge cases, and even find bugs in your implementation. It's goddamn near magic. That's not to say they're perfect, sometimes they do get confused and assume your implementation is correct when the test doesn't pass. Sometimes they do misunderstand. But the overall improvement for me has been enormous. They also generally write good tests. Refactoring never breaks the tests they've written unless an actually-visible behavior change has happened.
Second is trying to figure out the answer to really thorny problems. I'm extremely good at doing this, but agentic AI has made me faster. It can prototype approaches that I want to try faster than I can and we can see if the approach works extremely quickly. I might not use the code it wrote, but the ability to rapidly give four or five alternatives a go versus the one or two I would personally have time for is massively helpful. I've even had them find approaches I never would have considered that ended up being my clear favorite. They're not always better than me at choosing which one to go with (I often ask for their summarized recommendations), but the sheer speed in which they get them done is a godsend.
Finding the source of tricky bugs is one more case that they excel in. I can do this work too, but again, they're faster. They'll write multiple tests with debugging output that leads to the answer in barely more time than it takes to just run the tests. A bug that might take me an hour to track down can take them five minutes. Even for a really hard one, I can set them on the task while I go make coffee or take the dog for a walk. They'll figure it out while I'm gone.
Lastly, when I have some spare time, I love asking them what areas of a code base could use some love and what are the biggest reward-to-effort ratio wins. They are great at finding those places and helping me constantly make things just a little bit better, one place at a time.
Overall, it's like having an extremely eager and prolific junior assistant with an encyclopedic brain. You have to give them guidance, you have to take some of their work with a grain of salt, but used correctly they're insanely productive. And as a bonus, unlike a real human, you don't ever have to feel guilty about throwing away their work if it doesn't make the grade.
AI is solid for kicking off learning a language or framework you've never touched before.
But in my day to day I'm just writing pure Go, highly concurrent and performance-sensitive distributed systems, and AI is just so wrong on everything that actually matters that I have stopped using it.
zed was just a fast and simple replacement for Atom (R.I.P) or vscode. Then they put AI on top when that showed up. I don't care for it, and appreciate a project like this to return the program to its core.
Just to echo the sentiment, I've had struggles trying to figure out how to use LLMs in my daily work.
I've landed on using it as part of my code review process before asking someone to review my PR. I get a lot of the nice things that LLMs can give me (a second set of eyes, a somewhat consistent reviewer) but without the downsides (no waiting on the agent to finish writing code that may not work, costs me personally nothing in time and effort as my Org pays for the LLM, when it hallucinates I can easily ignore it).
If it's formulaic enough, I will use the editor templates/snippets generator. Or write a code generator (if it involves a bunch of files). If it's not, I probably have another class I can copy and strip out (especially in UI and CRUD).
> integrate module A into module B
If it's cannot be done easily, that's the sign of a less than optimal API.
> entire codebase A into codebase B
Is that a real need?
> get someones github project up and running on your machine, do you manually fiddle with cmakes and npms
If the person can't be bothered to give proper documentation, why should I run the project? But actually, I will look into AUR (archlinux) and Homebrew formula if someone has already do the first jobs of figuring dependency version. If there's a dockerfile, I will use that instead.
> convert an idea or plan.md or a paper into working code?
Iteratively. First have an hello world or something working, then mowing down the task list.
> Fix flakes, fix test<->code discrepancies or increase coverage etc
Either the test is wrong or the code is wrong. Figure out which and rework it. The figuring part always take longer as you will need to ask around.
> If you do all this manually, why?
Because when something happens in prod, you really don't want that feeling of being the last one that have interacted with that part, but with no idea of what has changed.
To me, using AI to convert an idea or paper into working code is outsourcing the only enjoyable part of programming to a machine. Do we not appreciate problem solving anymore? Wild times.
I'm pretty fast coding and know what I'm doing. My ideas are too complex for claude to just crap out. If I'm really tired I'll use claude to write tests. Mostly they aren't really good though.
AI doesn't really help me code vs me doing it myself.
this is something i've found LLMs almost useless at. consider https://arxiv.org/abs/2506.11908 --- the paper explains its proposed methodology pretty well, so i figured this would be a good LLM use case. i tried to get a prototype to run with gemini 2.5 pro, but got nowhere even after a couple of hours, so i wrote it by hand; and i write a fair bit of code with LLMs, but it's primarily questions about best practices or simple errors, and i copy/paste from the web interface, which i guess is no longer in vogue. that being said, would cursor excel here at a one-shot (or even a few hours of back-and-forth), elegant prototype?
For stuff like adding generating and integrating new modules: the helpfulness of AI varies wildly.
If you’re using nest.js, which is great but also comically bloated with boilerplate, AI is fantastic. When my code is like 1 line of business logic per 6 lines of boilerplate, yes please AI do it all for me.
Projects with less cruft benefit less. I’m working on a form generator mini library, and I struggle to think of any piece I would actually let AI write for me.
Similar situation with tests. If your tests are mostly “mock x y and z, and make sure that this spied function is called with this mocked payload result”, AI is great. It’ll write all that garbage out in no time.
If your tests are doing larger chunks of biz logic like running against a database, or if you’re doing some kinda generative property based testing, LLMs are probably more trouble than they’re worth
To do those things, I do the same thing I've been doing for the thirty years that I've been programming professionally: I spend the (typically modest) time it takes to learn to understand the code that I am integrating into my project well enough to know how to use it, and I use my brain to convert my ideas into code. Sometimes this requires me to learn new things (a new tool, a new library, etc.). There is usually typing involved, and sometimes a whiteboard or notebook.
Usually it's not all that much effort to glance over some other project's documentation to figure out how to integrate it, and as to creating working code from an idea or plan... isn't that a big part of what "programming" is all about? I'm confused by the idea that suddenly we need machines to do that for us: at a practical level, that is literally what we do. And at a conceptual level, the process of trying to reify an idea into an actual working program is usually very valuable for iterating on one's plans, and identifying problems with one's mental model of whatever you're trying to write a program about (c.f. Naur's notions about theory building).
As to why one should do this manually (as opposed to letting the magic surprise box take a stab at it for you), a few answers come to mind:
1. I'm professionally and personally accountable for the code I write and what it does, and so I want to make sure I actually understand what it's doing. I would hate to have to tell a colleague or customer "no, I don't know why it did $HORRIBLE_THING, and it's because I didn't actually write the program that I gave you, the AI did!"
2. At a practical level, #1 means that I need to be able to be confident that I know what's going on in my code and that I can fix it when it breaks. Fiddling with cmakes and npms is part of how I become confident that I understand what I'm building well enough to deal with the inevitable problems that will occur down the road.
3. Along similar lines, I need to be able to say that what I'm producing isn't violating somebody's IP, and to know where everything came from.
4. I'd rather spend my time making things work right the first time, than endlessly mess around trying to find the right incantation to explain to the magic box what I want it to do in sufficient detail. That seems like more work than just writing it myself.
Now, I will certainly agree that there is a role for LLMs in coding: fancier auto-complete and refactoring tools are great, and I have also found Zed's inline LLM assistant mode helpful for very limited things (basically as a souped-up find and replace feature, though I should note that I've also seen it introduce spectacular and complicated-to-fix errors). But those are all about making me more efficient at interacting with code I've already written, not doing the main body of the work for me.
What do you mean by this? If you just mean moving things around then code refactoring tools to move functions/classes/modules have existed in IDEs for millennia before LLMs came around.
> get someones github project up and running on your machine
docker
> convert an idea or plan.md or a paper into working code
I sit in front of a keyboard and start typing.
> Fix flakes, fix test<->code discrepancies or increase coverage etc
I sit in front of a keyboard, read, think, and then start typing.
> If you do all this manually, why?
Because I care about the quality of my code. If these activities don't interest you, why are you in this field?
> I can kick out some money to essentially "subscribe" for maintenance.
People on HN and other geeky forums keep saying this, but the fact of the matter is that you're a minority and not enough people would do it to actually sustain a product/company like Zed.
It's a code editor so I think the geeky forums are relevant here.
Also, this post is higher on HN than the post about raising capital from Sequoia where many of the comments are about how negatively they view the raising of capital from VC.
The fact of the matter is that people want this and the inability of companies to monetize on that desire says nothing about whether the desire is large enough to "actually sustain" a product/company like Zed.
"Happy to see this". The folks over at Zed did all of the hard work of making the thing, try to make some money, and then someone just forks it to get rid of all of the things they need to put in to make it worth their time developing. I understand if you don't want to pay for Zed - but to celebrate someone making it harder for Zed to make money when you weren't paying them to begin with -"Happy to PLAN to pay for Zed"- is beyond.
The only path forward I see for a classic VC investment is the AI drive.
But I don't think the AI bit is valuable. A powerful plugin system would be sufficient to achieve LLM integration.
So I don't think this is a worthwhile investment unless the product gets a LOT worse and becomes actively awful for users who aren't paying beaucoup bucks for AI tooling- the ROI will have to center the AI drive.
It's not a move that will generate a good outcome for the average user.
I always have mixed feelings about forks. Especially the hard ones. Zed recently rolled out a feature that lets you disable all AI features. I also know telemetry can be opted out. So I don’t see the need for this fork. Especially given the list of features stated. Feels like something that can be upstreamed. Hope that happens
I remember the Redis fork and how it fragmented that ecosystem to a large extent.
I'd see less need for this fork if Zed's creators weren't already doing nefarious things like refusing to allow the Zed account / sign-in features to be disabled.
I don't see a reason to be afraid of "fragmented ecosystems", rather, let's embrace a long tail of tools and the freedom from lock-in and groupthink they bring.
Well there's features within Zed that are part of the account / sign-in process, so it might be a bit more effort to just "simply comment out login" for an editor that is as fast and smooth as Zed, I dont care that its there as long as they dont force it on me, which they don't.
Even opt-in telemetry makes me feel uncomfortable. I am always aware that the software is capable of reporting the size of my underwear and what I had for breakfast this morning at any moment, held back only by a single checkbox. As for the other features, opt-out stuff just feels like a nuisance, having to say "No, I don't want this" over and over again. In some cases it's a matter of balance, but generally I want to lean towards minimalism.
It's nice to have additional assurance that the software won't upload behind your back on first startup. Though I also run opensnitch, belt and suspenders style.
Bit premature to post this, especially without some manifesto explaining the particular reason for this fork. The "no rugpulls" implies something happened with Zed, but you can't really expect every HN reader to be in the loop with the open source controversy of the week.
Contributor Agreements are specifically there for license rug-pulls, so they can change the license in the future as they own all the copyrights. So the fact that they have a CA means they are prepping for a rug-pull and thus this bullet point.
I can’t speak for Zed’s specific case, but several years ago I was part of a project which used a permissive license. I wanted to make it even more permissive, by changing it to one of those essentially-public-domain licenses. The person with the ultimate decision power had no objections and was fine with it, but said we couldn’t do that because we never had Contributor License Agreements. So it cuts both ways.
I’m not sure where this belief came from, or why the people who believe it feel so strongly about it, but this is not generally true.
With the exception of GPL derivatives, most popular licenses such as MIT already include provisions allowing you to relicense or create derivative works as desired. So even if you follow the supposed norm that without an explicit license agreement all open source contributions should be understood to be licensed by contributors under the same terms as the license of the project, this would still allow the project owners to “rug pull” (create a fork under another license) using those contributions.
But given that Zed appears to make their source available under the Apache 2.0 license, the GPL exception wouldn’t apply.
CA means: this is not just a hobby project, it's a business, and we want to retain the power to make business decisions as we see fit.
I don't like the term "rug-pull". It's misleading.
If you have an open source version of Zed today, you can keep it forever, even if future versions switch to closed source or some source-available only model.
CLAs represent an important legal protection, and I would never accept a PR from a stranger, for something being developed in public, without one. They're the simplest way to prove that the contributor consented to licensing the code under the terms of the project license, and a CYA in case the contributed code is e.g. plagiarized from another party.
(I see that I have received two downvotes for this in mere minutes, but no replies. I genuinely don't understand the basis for objecting to what I have to say here, and could not possibly understand it without a counterargument. What I'm saying seems straightforward and obvious to me; I wouldn't say it otherwise.)
Zed is quite well known to be heavily cloud- and AI-focused, it seems clear that's what's motivating this fork. It's not some new controversy, it's just the clearly signposted direction of the project that many don't like.
But a fork with focus on privacy and local-first only needs lack of those to justify itself. It will have to cut some features that zed is really proud of, so it's hard to even say this is a rugpull.
> It will have to cut some features that zed is really proud of
What, they're proud of the telemetery?
The fork claims to make everything opt-in and to not default to any specific vendor, and only to remove things that cannot be self-hosted. What proprietary features have to be cut that Zed people are really proud of?
Today we're announcing our $32M Series B led by Sequoia Capital with participation from our existing investors, bringing our total funding to over $42M. - zed.dev
> I’m gradually removing all the features I deem undesirable: telemetry, auto-updates, proprietary cloud-only AI integrations, reliance on node.js, auto-downloading of language servers, upsells, the sign-in button, etc. I’m also aiming to make some of the cloud-only features self-hostable where it makes sense, e.g. running Zeta edit predictions off of your own llama.cpp or vLLM instance. It’s currently good enough to be my main editor, though I tend to be a bit behind on updates since there is a lot of code churn and my way of modifying the codebase isn’t exactly ideal for avoiding merge conflicts. To that end I’m experimenting with using tree-sitter to automatically apply AST-level edits, which might end up becoming a tool that can build customizable “unshittified” versions of Zed.
For Zed specifically? It cuts directly against their stated goal of being fast and resource-light. Moreover, it is not acceptable for software I use to automatically download and run third-party software without asking me.
For node.js in general? The language isn't even considered good in the browser, for which it was invented. It is absolutely insane to then try to turn it into a standalone programming language. There are so many better options available, use one of them! Reusing a crappy tool just because it's what you know is a mark of very poor craftsmanship.
It shouldn't be as tightly integrated into the editor as it is. Zed uses it for a lot of things, including to install various language servers and other things via NPM, which is just nasty.
You might not be old enough to remember how much everyone hated JavaScript initially - just as an in-browser language. Then suddenly it's a standalone programming language too? WTH??
I assume that's where a lot of the hate comes from. Note that's not my opinion, just wondering if that might be why.
I guess some node.js based tools that are included in Zed (or its language extensions) such as ‘prettier’ don’t behave well in some environments (e.g., they constantly try to write files to /home/$USER even if that’s not your home directory). Things like that create some backlash.
Slow and ram heavy. Zed feels refreshingly snappy compared to vscode even before adding plugins. And why does desktop application need to use interpreted programming languages?
What I really want from Zed is multi window support. Currently, I can’t pop out the agent panel or any other panels to use them on another monitor.
Local-first is nice, but I do use the AI tools, so I’m unlikely to use this fork in the near term. I do like the idea behind this, especially no telemetry and no contributor agreements. I wish them the best of luck.
I did happily use Zed for about year before using any of its AI features, so who knows, maybe I’ll get fed up with AI and switch to this eventually.
Yes same here. I tried it out because of all the discussion about it then saw I couldn’t pop the panel out (or change some really basic settings cursor has had for over a year) then closed and uninstalled it.
Readit News
The fact of the matter is, I am not even using AI features much in my editor anymore. I've tried Copilot and friends over and over and it's just not _there_. It needs to be in a different location in the software development pipeline (Probably code reviews and RAG'ing up for documentation).
- I can kick out some money for a settings sync service. - I can kick out some money to essentially "subscribe" for maintenance.
I don't personally think that an editor is going to return the kinds of ROI VCs look for. So.... yeah. I might be back to Emacs in a year with IntelliJ for powerful IDE needs....
It can also encourage laziness: If the AI reviewer didn't spot anything, it's easier to justify skimming the commit. Everyone says they won't do it, but it happens.
For anything AI related, having manual human review as the final step is key.
I don't mind the AI stuff. It's been nice when I used it, but I have a different workflow for those things right now. But all the stuff besides AI? It's freaking great.
Yes, you're right, AI cannot be a senior engineer with you. It can take a lot of the grunt work away though, which is still part of the job for many devs at all skill levels. Or it's useful for technologies you're not as well versed in. Or simply an inertia breaker if you're not feeling very motivated for getting to work.
Find what it's good for in your workflows and try it for that.
I'm blown away.
I'm a very senior engineer. I have extremely high standards. I know a lot of technologies top to bottom. And I have immediately found it insanely helpful.
There are a few hugely valuable use-cases for me. The first is writing tests. Agentic AI right now is shockingly good at figuring out what your code should be doing and writing tests that test the behavior, all the verbose and annoying edge cases, and even find bugs in your implementation. It's goddamn near magic. That's not to say they're perfect, sometimes they do get confused and assume your implementation is correct when the test doesn't pass. Sometimes they do misunderstand. But the overall improvement for me has been enormous. They also generally write good tests. Refactoring never breaks the tests they've written unless an actually-visible behavior change has happened.
Second is trying to figure out the answer to really thorny problems. I'm extremely good at doing this, but agentic AI has made me faster. It can prototype approaches that I want to try faster than I can and we can see if the approach works extremely quickly. I might not use the code it wrote, but the ability to rapidly give four or five alternatives a go versus the one or two I would personally have time for is massively helpful. I've even had them find approaches I never would have considered that ended up being my clear favorite. They're not always better than me at choosing which one to go with (I often ask for their summarized recommendations), but the sheer speed in which they get them done is a godsend.
Finding the source of tricky bugs is one more case that they excel in. I can do this work too, but again, they're faster. They'll write multiple tests with debugging output that leads to the answer in barely more time than it takes to just run the tests. A bug that might take me an hour to track down can take them five minutes. Even for a really hard one, I can set them on the task while I go make coffee or take the dog for a walk. They'll figure it out while I'm gone.
Lastly, when I have some spare time, I love asking them what areas of a code base could use some love and what are the biggest reward-to-effort ratio wins. They are great at finding those places and helping me constantly make things just a little bit better, one place at a time.
Overall, it's like having an extremely eager and prolific junior assistant with an encyclopedic brain. You have to give them guidance, you have to take some of their work with a grain of salt, but used correctly they're insanely productive. And as a bonus, unlike a real human, you don't ever have to feel guilty about throwing away their work if it doesn't make the grade.
But in my day to day I'm just writing pure Go, highly concurrent and performance-sensitive distributed systems, and AI is just so wrong on everything that actually matters that I have stopped using it.
[0] https://zed.dev/blog/disable-ai-features
I would prefer an off-by-default telemetry, but if there's a simple opt-out, that's fine?
I've landed on using it as part of my code review process before asking someone to review my PR. I get a lot of the nice things that LLMs can give me (a second set of eyes, a somewhat consistent reviewer) but without the downsides (no waiting on the agent to finish writing code that may not work, costs me personally nothing in time and effort as my Org pays for the LLM, when it hallucinates I can easily ignore it).
- generate new modules/classes in your projects - integrate module A into module B or entire codebase A into codebase B?
- get someones github project up and running on your machine, do you manually fiddle with cmakes and npms?
- convert an idea or plan.md or a paper into working code?
- Fix flakes, fix test<->code discrepancies or increase coverage etc
If you do all this manually, why?
If it's formulaic enough, I will use the editor templates/snippets generator. Or write a code generator (if it involves a bunch of files). If it's not, I probably have another class I can copy and strip out (especially in UI and CRUD).
> integrate module A into module B
If it's cannot be done easily, that's the sign of a less than optimal API.
> entire codebase A into codebase B
Is that a real need?
> get someones github project up and running on your machine, do you manually fiddle with cmakes and npms
If the person can't be bothered to give proper documentation, why should I run the project? But actually, I will look into AUR (archlinux) and Homebrew formula if someone has already do the first jobs of figuring dependency version. If there's a dockerfile, I will use that instead.
> convert an idea or plan.md or a paper into working code?
Iteratively. First have an hello world or something working, then mowing down the task list.
> Fix flakes, fix test<->code discrepancies or increase coverage etc
Either the test is wrong or the code is wrong. Figure out which and rework it. The figuring part always take longer as you will need to ask around.
> If you do all this manually, why?
Because when something happens in prod, you really don't want that feeling of being the last one that have interacted with that part, but with no idea of what has changed.
AI doesn't really help me code vs me doing it myself.
AI is better doing other things...
this is something i've found LLMs almost useless at. consider https://arxiv.org/abs/2506.11908 --- the paper explains its proposed methodology pretty well, so i figured this would be a good LLM use case. i tried to get a prototype to run with gemini 2.5 pro, but got nowhere even after a couple of hours, so i wrote it by hand; and i write a fair bit of code with LLMs, but it's primarily questions about best practices or simple errors, and i copy/paste from the web interface, which i guess is no longer in vogue. that being said, would cursor excel here at a one-shot (or even a few hours of back-and-forth), elegant prototype?
If you’re using nest.js, which is great but also comically bloated with boilerplate, AI is fantastic. When my code is like 1 line of business logic per 6 lines of boilerplate, yes please AI do it all for me.
Projects with less cruft benefit less. I’m working on a form generator mini library, and I struggle to think of any piece I would actually let AI write for me.
Similar situation with tests. If your tests are mostly “mock x y and z, and make sure that this spied function is called with this mocked payload result”, AI is great. It’ll write all that garbage out in no time.
If your tests are doing larger chunks of biz logic like running against a database, or if you’re doing some kinda generative property based testing, LLMs are probably more trouble than they’re worth
Usually it's not all that much effort to glance over some other project's documentation to figure out how to integrate it, and as to creating working code from an idea or plan... isn't that a big part of what "programming" is all about? I'm confused by the idea that suddenly we need machines to do that for us: at a practical level, that is literally what we do. And at a conceptual level, the process of trying to reify an idea into an actual working program is usually very valuable for iterating on one's plans, and identifying problems with one's mental model of whatever you're trying to write a program about (c.f. Naur's notions about theory building).
As to why one should do this manually (as opposed to letting the magic surprise box take a stab at it for you), a few answers come to mind:
1. I'm professionally and personally accountable for the code I write and what it does, and so I want to make sure I actually understand what it's doing. I would hate to have to tell a colleague or customer "no, I don't know why it did $HORRIBLE_THING, and it's because I didn't actually write the program that I gave you, the AI did!"
2. At a practical level, #1 means that I need to be able to be confident that I know what's going on in my code and that I can fix it when it breaks. Fiddling with cmakes and npms is part of how I become confident that I understand what I'm building well enough to deal with the inevitable problems that will occur down the road.
3. Along similar lines, I need to be able to say that what I'm producing isn't violating somebody's IP, and to know where everything came from.
4. I'd rather spend my time making things work right the first time, than endlessly mess around trying to find the right incantation to explain to the magic box what I want it to do in sufficient detail. That seems like more work than just writing it myself.
Now, I will certainly agree that there is a role for LLMs in coding: fancier auto-complete and refactoring tools are great, and I have also found Zed's inline LLM assistant mode helpful for very limited things (basically as a souped-up find and replace feature, though I should note that I've also seen it introduce spectacular and complicated-to-fix errors). But those are all about making me more efficient at interacting with code I've already written, not doing the main body of the work for me.
So that's my $0.02!
I type:
or: > integrate module A into module BWhat do you mean by this? If you just mean moving things around then code refactoring tools to move functions/classes/modules have existed in IDEs for millennia before LLMs came around.
> get someones github project up and running on your machine
docker
> convert an idea or plan.md or a paper into working code
I sit in front of a keyboard and start typing.
> Fix flakes, fix test<->code discrepancies or increase coverage etc
I sit in front of a keyboard, read, think, and then start typing.
> If you do all this manually, why?
Because I care about the quality of my code. If these activities don't interest you, why are you in this field?
People on HN and other geeky forums keep saying this, but the fact of the matter is that you're a minority and not enough people would do it to actually sustain a product/company like Zed.
Also, this post is higher on HN than the post about raising capital from Sequoia where many of the comments are about how negatively they view the raising of capital from VC.
The fact of the matter is that people want this and the inability of companies to monetize on that desire says nothing about whether the desire is large enough to "actually sustain" a product/company like Zed.
I would pay for zed.
The only path forward I see for a classic VC investment is the AI drive.
But I don't think the AI bit is valuable. A powerful plugin system would be sufficient to achieve LLM integration.
So I don't think this is a worthwhile investment unless the product gets a LOT worse and becomes actively awful for users who aren't paying beaucoup bucks for AI tooling- the ROI will have to center the AI drive.
It's not a move that will generate a good outcome for the average user.
But he does say he does want to pay!
I remember the Redis fork and how it fragmented that ecosystem to a large extent.
I don't see a reason to be afraid of "fragmented ecosystems", rather, let's embrace a long tail of tools and the freedom from lock-in and groupthink they bring.
I think your thinking is common sense.
opt-out is not enough, specially in a program where opt-out happens via text-only config files.
I can never know if I've correctly opted out of all the things I don't want.
All of that hard work, intended to build a business, and nobody is happy.
Now there's a hard fork.
This is shitty.
With the exception of GPL derivatives, most popular licenses such as MIT already include provisions allowing you to relicense or create derivative works as desired. So even if you follow the supposed norm that without an explicit license agreement all open source contributions should be understood to be licensed by contributors under the same terms as the license of the project, this would still allow the project owners to “rug pull” (create a fork under another license) using those contributions.
But given that Zed appears to make their source available under the Apache 2.0 license, the GPL exception wouldn’t apply.
I don't like the term "rug-pull". It's misleading.
If you have an open source version of Zed today, you can keep it forever, even if future versions switch to closed source or some source-available only model.
(I see that I have received two downvotes for this in mere minutes, but no replies. I genuinely don't understand the basis for objecting to what I have to say here, and could not possibly understand it without a counterargument. What I'm saying seems straightforward and obvious to me; I wouldn't say it otherwise.)
Dead Comment
But a fork with focus on privacy and local-first only needs lack of those to justify itself. It will have to cut some features that zed is really proud of, so it's hard to even say this is a rugpull.
What, they're proud of the telemetery?
The fork claims to make everything opt-in and to not default to any specific vendor, and only to remove things that cannot be self-hosted. What proprietary features have to be cut that Zed people are really proud of?
https://github.com/zedless-editor/zedless?tab=readme-ov-file...
As far as I know, the Zed people have open sourced their collab server components (as AGPLv3), at least well enough to self-host. For example, https://github.com/zed-industries/zed/blob/main/docs/src/dev... -- AFAIK it's just https://github.com/livekit/livekit
The AI stuff will happily talk to self-hosted models, or OpenAI API lookalikes.
If there’s a group of people painfully aware of telemetry and AI being pushed everywhere is devs…
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Zed for Windows: What's Taking So Long? - https://news.ycombinator.com/item?id=44964366
Sequoia backs Zed - https://news.ycombinator.com/item?id=44961172
> Since someone mentioned forking, I suppose I’ll use this opportunity to advertise my fork of Zed: https://github.com/zedless-editor/zed
> I’m gradually removing all the features I deem undesirable: telemetry, auto-updates, proprietary cloud-only AI integrations, reliance on node.js, auto-downloading of language servers, upsells, the sign-in button, etc. I’m also aiming to make some of the cloud-only features self-hostable where it makes sense, e.g. running Zeta edit predictions off of your own llama.cpp or vLLM instance. It’s currently good enough to be my main editor, though I tend to be a bit behind on updates since there is a lot of code churn and my way of modifying the codebase isn’t exactly ideal for avoiding merge conflicts. To that end I’m experimenting with using tree-sitter to automatically apply AST-level edits, which might end up becoming a tool that can build customizable “unshittified” versions of Zed.
When did people start hating node and what do they have against it?
For node.js in general? The language isn't even considered good in the browser, for which it was invented. It is absolutely insane to then try to turn it into a standalone programming language. There are so many better options available, use one of them! Reusing a crappy tool just because it's what you know is a mark of very poor craftsmanship.
You're kidding, right?
I assume that's where a lot of the hate comes from. Note that's not my opinion, just wondering if that might be why.
WinterTC has only recently been chartered in order to make strides towards specifying a unified standard library for the JS ecosystem.
Local-first is nice, but I do use the AI tools, so I’m unlikely to use this fork in the near term. I do like the idea behind this, especially no telemetry and no contributor agreements. I wish them the best of luck.
I did happily use Zed for about year before using any of its AI features, so who knows, maybe I’ll get fed up with AI and switch to this eventually.
That's all I have to say right now, but I feel it needs to be said. Thank you for doing this.