All the death knell comments - Is no one looking at the revenue line? Revenue still trending the same. Costs presumably haven't skyrocketed. They've invested in something big. Thats probably a good thing, and often needed to evolve.
Yeah look at the details below. Revenue is up 6% (which is not amazing but still growth). But staff expenses are up 34.2%. And the real big hint is "Cash Flow From Investing" plunging from -83 million $USD to -469. That's massive. They're staffing up and investing in... something.
I still have this naive notion that we don't need LLMs for code generation and editing. Does a system need the knowledge of the full works of Shakespeare to be able to output Javascript?
Maybe people smarter than me know better but couldn't there be a middle ground where an IDE/Editor has an embedded engine (doesn't need to be a full-on LLM) that doesn't require external tool calls and token spend?
If an organization is paying $2400/year per developer for tokens and a highly intelligent editor/IDE comes around that charges $1000/yr and gets more output at a fixed cost, its a no-brainer of a decision.
> Does a system need the knowledge of the full works of Shakespeare to be able to output Javascript?
Turns out that actually - no. Researchers have managed to prune half the Experts in a MoE model that had a low probability of getting activated during coding tasks, resulting in a more focused model:
Main benefit is that it greatly reduces the amount of RAM required to run these models. Of course you could just cache those unused experts on disk instead, but the main point here is that you know which ones matter.
But aside from that recent models, like Qwen3.8-27b are reportedly more durable under heavy quantisation, e.g. 3bits or even ternary. With additional techniques like TurboQuant, you can feasibly run these models on consumer hardware - even if at 1/4th the speed you'd get from rented infrastructure.
VS Code has extensions such as Kilo Code or llama-vscode which let you work with local models much like you would with cloud based solutions.
You know what, considering there was a recent "small" open weights LLM released recently that meets 90% of my coding needs I'm inclined to agree.
Qwen3.8-Flash-Next - relatively small, it runs on 6 6 year old GPUs on my home PC happily running 5 simultaneous 262k sessions with additional 10 cached in RAM (bought back when you didn't have to remortgage your house for Ram) and it has been the first local model that is not a toy.
But there is a class of problems where I still reach for Anthropic's fable...
However, I have a hunch bordering with certainty Anthropic is achieving such great results by doing a lot of harness tricks.
For example opus 4.8, is not much better on coding than before mentioned Qwen model, but gets amazing results on factual knowledge stuff (the knowing all works of Shakespeare thing). How hard would it be to add a general knowledge RAG to requests that contain relevant questions and beat all benchmarks like that? Not very hard.
So I think there is big innovation to be had in harnesses, routers, inference and so on.
As to money spent on AI per developer my current client (a fortune 200 software company) spends $500 per month. That is $6k a year. A lot more than your examples. And many people run out of their quota pretty quickly.
I was inclined to listen to your take… then you started talking about having 6 graphics cards in your computer and acting like that’s a normal thing that people do…
The other pitfall here is that we are tempted to compare this crazy setup to frontier models when the real comparison is running this same model in OpenRouter.
This 6 GPU setup will probably outspend OpenRouter on electricity alone.
Keep in mind that GPU iteration cycles are slowing down significantly for some time now, so "a GPU from 2020" can actually mean NVIDIA RTX 3090 with 24 GB VRAM, one of the best cards you can buy in 2026 for local LLM use; in fact buying one used is probably the best choice right now, because newer generation RTXes are crazy expensive.
I have two. I paid <$1000 for each, before this craziness started. They work, sure, but 48GB of VRAM is just not enough to use a local LLM like a cloud model.
we use that same model at our company, it powers not only our devs but also many business needs. We rent 1 gpu (B300), it costs around 10x less than the api costs
Do you rent from AWS or some other provider? I wonder if there are issues with on-demand rent for those high-end GPU instances, is capacity always there or sometimes it is unavailable?
Not the person to whom you responded, but several times I have been dealing with debugging. Issue, tried. Opus/Sol/whatever and come up dry, then thrown it at Fable and gotten the solution in one shot.
> "Does a system need the knowledge of the full works of Shakespeare to be able to output Javascript?"
If the implementation brief says "attempting a reconnect in this handler would be a wild goose chase", the model needs to know enough Shakespeare, at least indirectly, to understand that expression...
Forgive my naive understanding of LLMs - but how do you get semantic understanding of a codebase, such that it knows what changes to make/why/where, without a wider understanding of language more broadly?
I'm using the word understanding loosely there, but I couldn't think of another word.
LLMs at my work have access to Slack chat history, the Wiki, the complete git history, (AI generated) notes from every in person meeting team meeting, JIRA, all code reviews, and all production logs, as well as your personal email (when you run it yourself)
They can typically explain the history of something faster than any human
Depends on what exactly you want to change. Lsp can do a lot but only in very simple changes.
Intellij when I used to use it had a lot great features like refactoring, extracting part of code as a function, renaming and creating empty classes/boilerplate but that's it
In current job I can order LLM to take data sink from other endpoint and write new with given URL. It will fetch from endpoint, check what it gives, compare with other and write new sink. Then it needs polishing because it always create something as awful as possible with cloning data all around but the most boring and soul sucking part is done
This is why I am working on https://github.com/spockz/semantic-editor. To bring more powerful editing functionality to agents. In a way that attaches to their chain of thought and deals with their probabilistic framing in json so it all works out cheaper and faster.
It's a totally fair question. I'm personally wondering if there's a half way point. Some kind of structured language that isn't plain English that a "dumb" LLM is able to parse. It could be human written, or it could be written by a "smart" LLM at a greater cost.
Looking at what Jev has shown, and what is being done in the space. I think you are right that there’s probably a lot of room for performance improvement on specific tasks and workflows that will be happening in the next few years
I also imagine it could be a big shakeup if all of a sudden models could run on CPU. Imagine running an Astra-level coding agent, locally on your laptop. All of a sudden GPUs wouldn’t look as valuable, if you don’t need them as much
We are still some time away from that, but it seems like progress is being made
We’re conditioned to interact with language models as chatbots and in that sense strong language understanding (implicit - some sort of world knowledge), is probably necessary for that?
But I’m sure we can have a small model that’s really strong at programming concepts, JavaScript syntax, and that’s about it. You’d interact with it differently, at specific seams in your code base - review a PR, merge two functions together, investigate these logs.
Or maybe I’m just not adequately absorbing the bitter lesson. Idk
No kidding. As a small employer I expect to be spending $200 a month so each employee can have an OAI or Claude 20x sub, or else spend it on the Chinese prepaid tokens of their choice.
I think the amount of knowledge to correctly work on code is more than you'd think, because at the end of the day writing code without an understanding of the environment it exists in/for is likely to not fit the problem correctly. Maybe it doesn't need knowledge of _Shakespeare_ per se, but if you were working on a virtual tabletop having knowledge of tabletop games can help with identifying the right implementation to use, knowing what kind of constraints to consider, etc.
I don't need AI in the same way that I don't need autocomplete. I can definitely program without autocompletion, but I'm a lot slower than others who use it
I think this already happens through Mixture of Experts which is now build in to ost models.
But finding out what an LLM needs to understand from a business side to write your code good, is an otpimzation which no one cares currently.
I'm pretty sure we either stay on big full frontier models for a long time, just use them for everything or we will start to see more and more people doing finetuning/project specific training like java + german + english + business contxt xy;
My gut says the economics, e.g hardware/data center/resource constraints, are going make the economics of small specialized models more attractive. Without any evidence whatsoever, I also think that the big frontier companies will have to de-emphasize chatbots as huge models in favor of chatbots as huge products with a much much more granular mixture of experts approach, but with much smaller models. I’ve been saying for a while now that AI products have to hit the gas on prioritizing product design to reliably solve real people’s problems in predictable-enough ways, because the current approach is only really appealing to enthusiasts, developers, or optimistic managers, and with the kind of money they’re throwing around, that’s not going to work.
My gut is that you could distill 98% of what's currently being done inside LLMs into a classical knowledge base/inference engine and only use the language models for natural language processing and an oracle for brainstorming and cut most of the computational cost and hallucinations out.
I have a feeling that when all the AI-hype dust settles, what you describe will be the killer app of AI. That, ChatBots and unstructured data processing. Huge productivity improvements but not the sci-fi hype of today.
It is very difficult to predict ahead of time what knowledge a model would need to understand a prompt to generate a program. It could refer to all kinds of real world knowledge referring to the kinds of entities you want the program to model.
Well, the post I’m replying to says that English was learned first, and I’m saying that I learned Perl before I learned English.
I don't think LLM needs to know Shakespeare to understand: "attempting a reconnect in this handler would be a wild goose chase." I would even bet that most people learned of this expression before reading Romeo and Julie.
That might be a bad example ... replace english with nearly anything not related to prompting/coding. For example, I bet the models have "knowledge" of biology, chemistry, etc. not exactly useful for programming a SaaS web app that say does project mgmt. I think there's opportunity for very specific tooling rather than "general" knowledge.
I don't train LLMs myself, but my impression is that general knowledge has lead to more intelligent behavior on specific tasks. The voluminous training set is imporant.
But even besides that... Yesterday I prompted a feature by referencing a specific Monty Python skit. Does the coding tool need to know Monty Python? Maybe I could describe the feature in other terms, but it sure was convenient to have this shared knowledge. I don't see why Shakespeare would be any different.
Everything around "desired machine physics" is superfluous wank; historically a biz case stored as code when some UI could feed biz case params go a function generator
Come on we know what we use computers for; media consumption and 2D data entry/review. Locally we just need a core engine for geometric transforms of visual state. What all these languages give us ability to create such a generic VM filled with customized semantics that mean nothing to solving the problem but plenty to a clever coder.
Kind of like Unicode we need distilled geometry primitives like "teapot for text" and desktop metaphors and to let people put the superfluous wank at the presentation layer
Which text used to be so making UI out of layers of text, OOP, and such made sense for decades
But we're just engaged in bloating system state through def jargon_to_encapsulate { desired machine physics } when we already know it's going to be simulated 3D or 2D visual transforms. We don't need to capture all those states in code verbatim.
Things like Jev are the future of models. Fine tuned on transforms given a context. "So you want to replicate GTA5? Here's a data set of geometric shapes and gradients constraints from all observed xyz" pipe that into your local renderer
We're entering the phase of software engineering (and engineering generally) where we realized we been dramatically over playing the song and can strip out entire asides and digressions, circumlocutions of provenance, to tighten up pacing and improve enjoyment of the outcomes. Hopefully. Or we kill ourselves. Through social squabbles (political, economic, religious, whatever) due to laziness to learn etiquette, and environmental destruction.
1. Storing Shakespeare's work costs almost no $ in regards to disk space.
2. If the prompt doesn't include "Shakespeare" or relevant terms then no regression is performed for that topic and therefore there is no effective token cost.
Someone may correct me, but I think it's not a big $ win to exclude relevant topics from the models' overall capabilities. Instead you'd tune weights so that #2 better identifies what is or isn't among the relevant terms on which to run regressions.
I think you're probably missing the forest for the trees here... broadly speaking, these multibillion "parameter" (whatever that actually means) models store a lot more than shakespeare, and have storage costs in the 100s of GB/TB (which translates to $$$$$$ in SSD/RAM costs), nevermind the (kilos/mega/giga)watts involved, all the pollution, etc...
Meanwhile, a template (maybe a couple KB) costs less than a couple cents to store and run. Large Languages Models are not really interesting, (smaller) LLMs that only contain "what you need" are.
To me it feels like the difference between crows and humans. Yes crows are smart, but what we really want are all inclusive models capable of human "thinking" . I guess we probably need a mix of both so we can give the crows the easy jobs freeing up resources.
Right but if the cost difference is negligible, as I've pointed out in another comment, in what case would you prefer to tell the crow twice to do something that a better weighted large model could do in one prompt?
I don't see it. In every case my time is more valuable than the cost of the prompt (so far) so the higher dollar cost, one shot, "getter done" model is the better net value option.
This is especially true when taking into account that the crow doesn't just fail on a single prompt, it does something much worse. It creates new problems that need to be undone afterwards. It confidently duplicates, triplicates, etc. a damaging work output that then needs more and more work to clean up before starting over.
Claude Fable 5.1 currently estimates its own total data set at 45TB.
That's a trivial number for sharing between a small user base of, in my case, 150 employees.
What am I missing? You're talking about maybe $60k retail cost in high read speed SANs that are likely already in place for a business of this size anyway? (Probably purchased a few years ago for under $30k. At least mine are.) In a US data center I'm paying a flat rate for rack space, so power consumption isn't a consideration anyway, but honestly it really isn't that much power even if I was being billed for it.
It's really nothing. An overlooked line item on a budget sheet.
So the real cost if I were to self host is video cards. But as mentioned previously, that's not reduced by smaller data sets, it's reduced by better weighted models, right? Let me know if I'm mistaken, please.
I'm very interested to be persuaded otherwise as a decision maker. Thanks for your insight and ideas.
Considering all of the above, I'm currently of the mind that a lower cost model that makes more mistakes is much more expensive in net, actually. So I prefer the most accurate, better weighted model, not the slimmer data set.
> Maybe people smarter than me know better but couldn't there be a middle ground where an IDE/Editor has an embedded engine (doesn't need to be a full-on LLM) that doesn't require external tool calls and token spend?
IDEA already have small LLM for one line code completion IIRC.
But the gain people want from LLM is generally "here, add this entire feature" or "here, go thru every dependency's changelog and update code to work with latest version". Those are not small LLM tasks
I have hope we will get there eventually, once all the hype/wealth extraction/boys club giving all their buddies money cycles end, and the specialized tools with real value start to emerge.
These specialized tools already deliver tremendous value. What happens on the backend financially is of no concern to me, as I have no influence over it.
I think they're in the perfect position to take a stab at actually monetizing a "just-works-and-good-enough" local code-assistant that works well enough to save people on burning tokens with the big providers and/or keeping their data offline for regulatory reasons (ie also selling to customers that CANNOT use Claude or OpenAI).
1: Local models are catching up quickly
2: Visual Studio Intellicode (not to be confused with Intellisense) was/is surprisingly good at suggestions (when it first appeared before people went over to CLI's I felt that it was almost magically good for it's time, turned off co-pilot and whatever backend for a reason of compliance for a local workspace and the suggestions are quite good still even if not on the same level as the frontier suggestions).
If it pans out, with their brand people many would probably be happy to fork over for a Jetbrains licence.
To do nothing is to die. I've been a JetBrains subscriber for over a decade. Nobody is going to use their tools in five years. I certainly don't need my subscription anymore.
> on some "also ran" LLM sinkhole.
They can't do Junie. It's a dead end. They can't do the same thing everyone else is doing either, or they're exactly as you put it: an "also ran" in a very crowded field.
The only way for JetBrains to survive is to figure out their Garmin play. They either find some niche within the existing product or - maybe (and very improbably) - they can innovate something wild nobody else has figured out yet that provides a path to new fertile pasture. But that's more the startup path than the thriving incumbent facing innovator's dilemma path.
But no matter what, if they stay the course, they're dead. Just like half the people expecting to still be writing code by hand.
I think they are trying new things even with "nobody writes code anymore" in mind. Their IDEs are now MCP servers for agents to reason about the code. Imagine your agent will stop wasting tokens using grep to find symbol usages if he can just ask IDE where it is used. They are not the best option for vibecoders right now but who knows what will happen in 1 year.
Integration with other developer tools, code reviews etc. are better than ever. Ideavim is probably the best vim plugin and it gets new features every month. They are also investing a lot in the AI.
I would bet they will survive just fine unless we would write software in slack only using emoji :-)
Imagine your agent will stop wasting tokens using grep to find symbol usages if he can just ask IDE where it is used. They are not the best option for vibecoders right now but who knows what will happen in 1 year.
Can't agents just use a language server? There are already a bunch of projects that provide this, e.g.: https://www.agent-lsp.com/
Doesn't seem like a huge differentiator anymore?
I don't really know much about their current users, but from a business perspective, post-tokenmaxxing and them having an IDE, it seems like the most efficient environment for having a human in the loop is something they could tackle?
Well nobody needs to use IDE. There were always people who used vim with tmux as their IDE. The value of IDE is the I as in integrated - I see some value in having easy to manage single dev environment with batteries included. (I'm not an IDE guy though, and I personally closer to vim/vscode + plugins)
There were always people who used vim with tmux as their IDE.
But until language servers, IDEs with built-in code analysis had a huge advantage. This stopped once LSP was designed and some language servers got mature. LSP was developed originally by VS Code and it is easy to see why - it allowed VS Code to compete with IDEs without writing their own code analysis by letting language developers write a standard server. This made VS Code (and others like Zed) so powerful, that they had already replaced IDEs for many users (maybe outside Java). LLMs are just another nail in the coffin.
No, it didn't stop. In my experience, LSPs are still incredibly poor and comparatively primitive vs the actual analysis that JetBrains have implemented. It's night-and-day different in terms of the supported refactorings, actual understanding of the types and the codebase etc.
Also, LSP is just poorly designed and inefficient. JSON-RPC was an awful choice, the specification text is not well-written and the whole thing feels like a Microsoft pet project for VS Code than an open specification that everyone agrees works well.
This is not the whole picture. IDE is not just for writing code. What I really like on jetbrains is how strong the platform is. I will show you example which would be great if they implement it.
If you use ideavim you can enable feature which shows you action ID you have currently triggered (Ideavim: Track action IDs). If you click on anything it will show you name of that action and you can setup vim shortcut for that. This way, you can use almost anything by just typing a few letters. But that is just a start.
Now imagine you can use this to create "macro" which will create something like skill for LLM. So in a few seconds to minutes you can create "skills"/runbooks for major refactorings, project updates, git bisections, project deployments, log analysis or whatever you can think of. You will just click on 20 features and it will record what you did with some additional context (files, connected services, build systems etc.). This is the strength of integrated tools.
Of course this is just my imagination but I am not the smartest person in the world and I am pretty sure/hope that someone in jetbrains or in other IDE company is thinking this way.
You envision a world in which humans don't look at code.
I think that world is farther off than you think, especially in critical line of business software. You can YOLO it with your internal dashboard or your hipster coffee review site, but in my 2M-line highly regulated banking system, humans sign off on the code - even if LLMs do most of the typing.
And their MCP servers and tools are great! But I wish they’d remember that some of us also actually code in the IDE, because human usage quality of their IDEs has been getting worse in that time…
You are right, they fix even most annoying bugs really slowly. I also remember something like 2 years ago when they made pycharm unusable with poetry for several months and the release was like 18th of December (who decided to release tool for work as Christmas gift :-D ). The good thing is that you can always revert to older version and wait for proper fix.
Not using tooling (or not creating one) for repeating tasks and trying to one shot everything with latest frontier model is a difference between the bill for AI usage being 10 Eur or 10000 Eur
While I "vibe code" more and more these days, an IDE that still does code highlighting, I can use it to look up functions source and so on, it is very useful to be able to figure out what the LLM did.
And yes, there are people who use vim in a screen session, but I don't fit into that category. I like my GoLand IDE.
And while there are a ton of IDEs out there, I use what I'm used to.
I have been Jetbrains subscriber for over a decade and stopped using them last year. Visual Studio Code did LLM integration better. And now I am using VS Code less and less with AI-native control plane like Paseo. I can literally develop on my mobile phone.
> They either find some niche within the existing product
They should stay in where they started, dev experience and IDEs custom for each language. Entering the AI coding was a mistake in my opinion, I’m sure one can argue that AI coding would have better tooling without their IDEs, but AI coders (Cc and codex) don’t use IDEs anymore so it’s a lost battle before the start
I remember around 2019 or so they shipped their first AI feature and there was a huge backlash for it. Did that change their direction in anyway? Obviously 2026 is a way different landscape than back then.
I disagree on to do nothing is also to die, I'd love to continue paying if they prioritized bugfixing, speed, remote/container editing and having an open AI ecosystem, as well as supporting any new language features without degenerating into an "always online" editor like vs.code.
I could not care less about "new paradigm" editors, UI reworks and AI lock-in offerings, the only AI I want is let me bring my own local model, or interface with claude / codex / ...
I love their tools and am keeping my subscription for now, but would have to agree.
VSCode has been eating at their users for years now. Jetbrains tools still were much better in my opinion but they are competing with “free” and “good enough”. With AI getting better, the main advantages of Jetbrains are gone.
I don’t need a massive IDE anymore. I still need an editor, but there’s hundreds of better tools for quick edits than a massive IDE.
It’s a company at the end of the day, but I hope they find a niche or pull a Garmin play like you said, otherwise I don’t see them being relevant.
I look at it as like being able to start a fire in the woods without a lighter. It’s a skill, a helpful one even on the extremely rare occasions that it’s necessary. But realistically with even the bare minimum amount of prep, not a useful one.
How many people out there can do hand lithography to make an 8086 to bootstrap computing? One?
They picked weird direction. "Here, pay ENTIRE EXTRA SUB to use the LLM we made that is worse than one you're already using".
Yeah, no, vast majority just want to pick a AI vendor and integrate it into their IDEA or CLion or whatever other editor they were already using. Pushing into entirely different subscription was dead on arrival.
They figured that out and started integrating it into main tooling (https://plugins.jetbrains.com/plugin/33314-air), but they definitely wasted a bunch of resources on something nobody really wanted.
This was so annoying as a long time subscriber- we were begging them to get / let us integrate some of the more mainstream models - didn’t help that there early model was terrible
> Nobody is going to use their tools in five years.
What will replace it? The dumpster fire called Eclipse, certainly not. The even larger dumpster fire that is Electron based VS Code, also not. And "vibe coding", "agentic AI" etc. will also be a thing of the past once the VC money spigot selling tokens for far below actual cost dries up.
The JetBrains portfolio is here to stay.
(One might even see a total ban for American products in the EU or a significant push in sovereign technology on the horizon, and JB stands to profit from both options!)
I'm not a fan of VS Code myself, but everyone I know uses it (except for people I myself have influenced into using something else). It truly is a sort of default editor these days.
I guess it depends on your niche; I spend half my time coding Golang and Python, and the other half terraform, ansible, perl and I use other languages now and again for small projects and utilities.
In the devops/sysadmin world my stack would be common, and mostly people pick an editor and stick to it. I've been using Emacs for the past 20+ years at this point, and the last time I used Microsoft's IDE was back in the day when I was writing desktop apps using MFC (which probably dates me pretty well!) with visual studio.
I've seen colleagues use anything from atom, vim, emacs, notepad++, and other generic editors whos name I didn't recognize. There are one or two instances of VS Code I see now and again, but they're the outlier rather than the norm in my professional life.
I was a big IDE user since they existed (I used Visual C++ beta releases in 1992). However, since adopting AI tools I really haven't used an IDE. Once in a while for things I don't know how to do without one (e.g. view a markdown file locally). That's it though.
Most of their products have an AI harness embedded and it works well, at least for me. Has tools to let the models access proper debugging too(my experience is Clion) so that my build is available to them even when using remote/docker builds. The integration with codex works well too.
They host a lot of models too, and that is probably where they burned the cash.
Cost of services is up. I suspect that's where the token cost comes into play, but they didn't "invest" in tokens. They can't call that an investment anyway. The increase in cost of services relative to revenue impacts net income - we can see that in prior years - but that's not the whole story. Total assets on the balance sheet increased at the same time net income decreased. They spent money on something of value.
Could they label that as investing in such a report? Sounds misleading. Investing to me means paying for something you then own afterwards, paying for AI sounds like a normal expense.
No idea why they thought they can compete with frontier AI labs on that, it's entirely waste of money
They also tried to push AI feature set as a separate subscription which is just insane in current tooling market.
All users wanted is good integration of multi-AI providers in their base offering. I think they are slowly shifting to that but that's a lot of money wasted already
They integrated air recently into intellij, and I believe it's quite fruitful. You can use any agent you want, they can work locally, in separate worktrees, or remotely and you can switch between them, and merge their results back properly.
> ...the real big hint is "Cash Flow From Investing" plunging from -83 million $USD to -469. That's massive. They're staffing up and investing in... something.
...or they're bailing out of really bad investments before they become even worse ones...
> They're staffing up and investing in... something
You're suggesting "investing" is like R&D?
Investing is when you buy stocks or bitcoin and hope. Except for 1 year, their "investments" have always lost, last year about 50% of total assets:
-908 -4,374 3,970 -1,946 -10,273
"Investing" is traditionally how money is skimmed: something's sold to a friend at an inflated price that only becomes recognized as such years later amidst some other cover/crisis (if not after a statute of limitations). The other option is sweetheart deals - unneeded property leases, jobs for friends, etc. - but those are a bit more traceable, while investments can have multiple shell-company layers and complex derivatives.
Apparently, no one commenting knows how to read financial statements. They look at one item and assume the company is going out of business. Meanwhile, their total assets have increased. Cost of services have increased significantly over recent years - mostly commensurate with revenue growth, although the gap has been shrinking. Operating costs have been pretty flat. I don't have time to investigate where they spent the money, but the company is not at risk. They brought in more money than in prior years and spent it on something. That's it.
Jetbrains has been pushing Junie real hard, my guess is that they've been giving out too many cheap tokens to try to stay relevant as Claude and friends pull people away from the IDE.
In everyone's day jobs where they used an IDE 5 years ago, or even a year ago, are those jobs abandoning the IDE?
I still use Visual Studio in my day job, where Claude's output while VERY helpful, requires my ownership of everything, meaning I am inspecting every single line it changes. If a change is bigger than I think it should, I kill it before I commit.
I know I don't HAVE to use an IDE for that, but if the change is small enough, I am faster than asking Claude to understand the subtext behind my personal context of the product, and the IDE is supremely helpful for making a quick change across a handful of files.
> meaning I am inspecting every single line it changes.
I think this is changing fast. Pressure is increasing on devs for output, and most devs I know are no longer inspecting lines. I have devs in my business unit who claim to not have looked at code for months, except on certain rare occasions. I am not a developer and this week I've been given access to the repo to build my own apps and extensions. There's a "review" between commit and deploy, but there's no chance the Tech Lead can manually review everything, so that's getting done by AI too.
I know this horrifies a lot of devs, but these tools are shockingly good and we are not seeing an increase in bugs. In fact our automated detections (also AI assisted) are reducing the number of customer reported critical bugs.
I really think the days of inspecting every line are over.
This type of codebases will become a goldmine for cybersec in the near future. Except by then, only few people will be able to detect them or fix them. LLMs will leave the hardest problems and most difficult bugs plus and plethora of devs who either have skill atrophy or haven't learn these things in the first place.
Actually, cybersecurity seems to be the area that LLMs shine the most at; though it needs directing to actually look for the problem, LLMs have been able to find security faults in code that is well-vetted and written by experts.
It's an interesting philosophic question. LLMs tend to be overly verbose and defensive in coding. It's not a ton of extra complexity but it makes the code harder to follow for a human. But if a human is not writing the code how much does that matter?
I agree that they have gotten shockingly good. It's been a long time since I've seen them do something that is objectively wrong. Once we get closer to the "too cheap to meter" cost level things will change radically again.
Have you ever tried to use an LLM to add a feature to a really nice, pre 2023 codebase? It’s incredible how much easier it is to do, how much of a difference you instantly feel
> It's not a ton of extra complexity but it makes the code harder to follow for a human.
It is. I have seen Claude chasing after endless amount of edge cases that are just irrelevant in real usage especially for the kind of users we are supporting. At some point you need to stop reasoning about all those cases because it has zero benefit.
But it IS a ton of complexity and blows out context windows. Less code good. More code bad. Both for human and agent. Somehow, still only human can make code less.
Yes and….no. I have seen this play out at a large corp to spectacularly awful results. Talking 60k line react nextjs apps where every use effect has a linter silenced because the ai gave up on writing correct react code.
I have seen millions wasted because someone trusted an ai scripts calculation of a metric from the bottom of the org that led the top of the org to make a wrong decision only to laugh about ai. There is value but ffs read the god damn code. You can have the cake and eat it too. If the volume of code is so large you cannot read it, maybe it isnt worth shipping?
Or are you one of the ones pushing the real code reading on to others which seems to be common. Yes i can have agents vibe out 10 features and have my coworkers suffer fixing it in reviews.
What IS useful are the AI reviews. They catch bugs, not all are bugs but they do catch some. It is almost like they are better at finding logical issues across millions of tokens but not good at writing streamlined logic.
The number of times ai gives me a 800 line dif only to replace it with a 5 line dif after i read it and notice it grossly overcomplicated the ask and scoped in a bunch of nonsense from training data.
I'm beginning to abandon the IDE (vscode in my case). I've always been very comfortable with (or at least not scared of) the command line so the Claude app with a terminal pane open is handling much of my IDE use cases. What I really need to do is get better at using find, grep, and other search tools from the terminal and then create a good .vimrc for editing and i'm set. heh what's old is new again!
> I am inspecting every single line it changes.
Honestly, when I'm looking at ClaudeCode's output 75% of time i'm doing it to learn and understand and not just check for correctness. I'm confident enough to admit I don't know everything and I've learned a lot from reading Claude's code.
I had personal subscriptions to WebStorm and GoLand and cancelled them not long after getting Windsurf. Just don't need the IDE abilities like I used to... Still use 'go to definition' but that's pretty much it.
IMO what's being called an 'Agent Development Environment' solves this issue for you. I like Orca but there's a few dozen of them.
Basically they give you a way to view the code the llm has generated/changed easily, annotate that code for the llm, and manage multiple agents and at once.
And with LLMs you can just create your own pretty easily that matches your exact workflow and integrates with all your tools. I've gone through a few iterations, first using the Unix small tools that talk to each other philosophy, then a single TUI app running in a pane next to my agent cli and now a Go server that has a cli and web ui with xterm embedded terminals and has its own chat sidebar in the web ui that can use tools and interact with running sessions in terminals. I'll probably have something new in 6 months.
Yes that is a real problem at work. A lot of stuff is done in containers or virtual devices and jetbrains remote developping workflow takes too much time due to this transfer. VsCode is much faster there.
Yes. Github draft PRs for giving inline feedback to agents, then going back to chat window with agents in Cursor, Claude, Codex, etc. to say 'review my comments and address them'.
I tried it in DataGrip on a messy database. It hallucinated about which tables and columns to use. Had better results using Claude in the terminal and having it give me the SQL to run.
I use it daily, but I'm also the AI consumer that is looking for something like a hammer and a saw (it's clear what their job are and they're doing their job fine). I'm absolutelty not looking for the next-gen-stuff, so I avoid Codex/Claude/...
I think Junie is comparable to something like Claude Code or Codex, but moving a little slower feature wise. It's perfectly adequate for developers who want to use AI but don't want to keep up with the bleeding edge of tooling.
It felt quite competitive about a year ago. But haven't tried it since, no idea how it has held up with the other advancing. What I liked was the tight integration with the IDE. I don't particularly like the way I work with Claude now, still wanting to check the changes, navigate code, ask questions, write some code myself etc. Feel claude mostly is for the "bigger" changes. Sometimes I just want to select some text and refactor it, or ask a stupid simple question without the "chat".
Worked fine as a free tool, but as long as AI companies are selling their slopware tokens below cost with subscriptions, it's not really that interesting in my opinion.
The Jetbrains integration is nice, but if you rely on the tool you're probably not going to use the IDE much anyway.
Not personally but Junie was what made the fellow developer I respect most in the world actually start taking notice of LLMs as something useful instead of bad.
It is alright to get an LLM review on code I write myself, but getting extra tokens is expensive, and it was not clear if I could configure it to use one of the API keys I have from GLM, MiMo, etc.
I tried Air as well. It was alright, but I found it a bit more cumbersome to use then Pi. I tried configuring Pi to be accessed though ACP, but it felt like going through a hoop to have a worse experience. Then again, I am not someone that manages multiple agents in parallel, at most I have one agent implementing something in a different repository while I am doing my own things.
Air could maybe be useful for me if I could plug in the LLMs I actually use directly, it is too tied to ChatGPT, Claude, etc.
I enjoyed it a lot early on. In particular it didn’t have all the confusing and anxiety inducing options that other agents have to use more expensive or less expensive models, I liked the way it approached “plan mode” [1] and I didn’t feel like I had to stress it about token costs the way I do with the other models…. Jetbrains now gives me a choice of agents which I don’t like because having to think about it makes feel like one of those “ai bros” who is overthinking their relationship to ai and underthinking their code.
I would like to see one more ide-integrated, like I think running commands like ‘grep’ with the shell is really for the birds (creates a risk that some other command line might be run, the wrong files might be accessed, all that) and rather there should be a specialized toolbox.
[1] … I reject vibe coding. Token costs be damned but I always like to have a talk before it starts like “I think…, maybe you should…, does this make sense?, do you have any questions for me before you start?” and later “what are you doing in the code in the selection?”
Yeah, mind blowing after reading some comments which wen to conclusions without thininkg...
Look at the report (or point your clankers at it), not the saased helgi-pay-me-for-more, but free, full at CZ corporate registry. few tidbits from my fast (error prone) readin:
- main reason of net income loss is currency movement in 2025(CZK vs USD). eg. if they hold USD, they report loss without money moving. The other was bigger costs (but look below)
- they have 6% rev growth but ONLY in this CZK entity, whole group is whooping 25% up
- investing was lending (to subsidiaries) and outflow to bank deposits (sic!)
- cost increase impacting operating profit was from:
- “Other services”: +1,941, to 4,941.
- Consulting: +482, to 601.
- Marketing: +428, to 2,146
- Software development: -1,025, to 3,216
Looks fine for me and definitely not ai-doom-scenario.
Why are investments considered losses? It always seemed unintuitive to me as a layman. You made the profit and it's free to use however you want... investing it is a loss?
Or more likely, they're burning cash trying to chase the AI train to no avail while their core product stagnates, which is definitely not a good thing.
The war in Ukraine and subsequent move to Czechia did seem to hurt them pretty badly, but I wouldn't say they are stagnant. I've been a happy customer of PHPStorm for years and it continues to improve.
If your existing, well-established product is at risk due to new, competing products that do things in radically different ways, immediately dropping your product to chase the competition from way behind is usually not the right move. Unless you have a significant moat around your ecosystem, what reason do users have to adopt your inferior copy instead of the thing you copied?
I firmly believe JetBrains would have a better chance of survival if they stopped chasing the AI hype and got back to work on their IDEs, accepting the fact that they'll have less users than before. Right now, they're completely lost.
IDEs are for professionals. I understand that LLMs can one shot a weather app, and I get that it's exciting, but this is not the case with complex software.
I agree with you in principle but I am seeing my colleague who supposedly is an experienced engineer just sends out 40-file PRs without going through the code. When someone asked why the code does a certain thing he used LLM to come up with an answer. Apparently he has no idea what the code is doing and I doubt he reviews any of it or cares.
I don't understand what the value proposition of such an employee is. If all you're doing is acting as a meat proxy between your manager and your AI, why does your role even exist? Why shouldn't your superiors just prompt the AI directly?
I agree. Even in the era of LLMs, part of one’s job as a software developer is to understand the codebase and how it works and be able to fix bugs and add features without breaking other things in the process or compromising quality or security.
If you’re not doing that and just blindly committing whatever code the LLM generates without so much as glancing at it, you’re not adding any value and there’s a good chance that with a little initial guidance, the janitor could perform your prompt-jockeying about as well.
> I don't understand what the value proposition of such an employee is.
Creating the correct prompts to address specific concerns and goals requires technical knowledge and problem solving skills, same as before LLMs. Now, there's less typing of the code. Ofc 40 file changes indicates management is failing, leaving little confidence they could prompt their way to intended features. Code storms should be a converted to a stacked pr on a feature branch, so it is reviewable with great confidence. These words describing these issues require a level of sophistication which will necessarily no longer be a people manager role. I think this kind of (nearly) codeless position is ahead of the curve, not behind.
What is the value proposition of the managers? In the old times, it was mostly managing the human aspects of development. At least in my experience, managers wouldn't know what to prompt, even if they could.
Yes, welcome to the new world. This is how things are now. Every couple months the models and tools get better, while everyone keeps assuring themselves that any day now they’re going to run into the wall. Whether we like it or not, this is how it is. Let go and let Claude.
Probably AI spend and increased developer cost (salary + AI subscription cost). And the increase in memory prices means procuring IT assets has sky-rocketed too.
I would assume the margins they operated on, evaporated with the AI bubble.
Now it's Claude Code and ever so occasionally Codex.
I never do work in IDEs by hand anymore. I stopped writing code entirely in February and I will likely never write code again unless my internet dies.
I need a JetBrains-level AST navigator that focuses on high level code navigation and understanding, and moreover on code and architectural review. I need to quickly scan diffs and quickly see architecture at a glance.
Of course even that too many eventually fall away.
I rarely open RustRover these days. I could never have predicted that.
I "code" using Codex but I still use PHPStorm for checking diffs, database access, reviewing PRs, and the debugger. The value proposition has changed, not disappeared.
> I "code" using Codex but I still use PHPStorm for checking diffs, database access, reviewing PRs, and the debugger. The value proposition has changed, not disappeared.
You are able to do this while the output is small enough. But, it will not stay small for long. Business expectations are rising fast. To stay competitive, you have to push large amounts of code/fixes/features. There is no way to manually review it or QA it. If your org is not there yet, it will eventually get there. Or it will die out. It is only a matter of time.
I'm on the opinion that if it's "code review" and code is not properly checked out than it's just a meat linter phase that's almost completely useless with meaningless style disagreements.
I've been paying for the all products pack for 8 years now, but at my latest job all code is generated, and I think this will be the reality at most companies. I won't extend this year
If you've been on HN long enough you recognize that the OP is quite prolific in making absurd claims about AI: infamously predicted that children would be making professional, Hollywood level films by the end of 2025, and is now spending their time building the 5000th barely functional clone of Adobe tools[0]. It's probably a little unfair, but they are bold claims from someone who really does not have the ground to be making bold claims.
You don't get the nuance that there are people who enjoy the writing the code part more than they enjoy the handholding and hitting enter on a prompt part. And they write it fast or concise enough to not need to prompt engineer bicker with a machine.
And as soon as an edge case pops up that your model will have never been able to hear about because it hasn't been released publicly, security vuln, whatever, you'll get a "fix" confidently hallucinated at you and be none the wiser.
There's going to be a huge pendulum swing with all the llm zombies and sanewashing it like this isn't helping anyone.
All of this just oozes junior engineer if you're even employed in the field at all.
I do get that some people enjoy the manual process more than they enjoy building the product.
It doesn't give you the right to insult my expertise, and frankly your arguments sound like things that one would make up despite little actual experience using AI to develop software.
How can one insult something one knows nothing about. Tell us what sort of expert are you instead of patting yourself on the back. Anybody can come here and claim they're bigger experts than you. Will you believe them? Maybe you're a big ego with rubbish "engineering" skills.
A large percentage thinks that the current status quo is how things will look over the next decade. They don't think everything is fundamentally and irreversibly changing.
Nobody is coming out of this with the same career. The whole world is being rewired. Some people really don't like that.
I'm just glad we're out of the web platform / cellphone incrementalism era. I wish more of my career could have been spent with this rocket fuel. It's dangerous and hypergolic, but it's fun and flashy and capable of pulling us out of this gravity well.
> Is no one looking at the revenue line? Revenue still trending the same.
Yes. Companies have been looking at nothing but revenue for over 10 years now. You realize that a sustainable company has to look at net profit at some point?
Late 30s. Used to drink a fair amount of wine/beer. I Drink a lot less now.
- Getting older, it affects me for longer. I don’t want to write off feeling tip top the next day. Too high a price to pay.
- I try and train (exercise) hard most days - I can’t train anywhere near as well after alcohol.
- Kids - when you’re trying to fit work, hobbies, training, learning / self development and kids / family in, there’s not much room for slack. (Which could be considered a bad situation in itself…)
Has just become not worth it regularly. Fortnightly binges work better!
Opposite for me. Late 30s but I drink more or the same.
But I don't drink my go-to Zinfandel anymore as it has a big ass flag printed on the box. It's embarrassing feeling the cashier's judgemental gaze. They know I'm a drunk of course but I don't want them thinking I support the US
Tell the wine makers to stop putting that flag on there and maybe exports may pick up again
America’s obsession with their flag is now seen as nationalism on the outside. I always ask to imagine Germans putting their massive flag absolutely everywhere possible and how would that make everyone else feel.
Yep fully appreciate that , being slightly glib- it’s probably a fraction of what it would have been spread out though, and probably feels like more of a binge due to infrequency / age than it actually is!
Each year, I watch less and less football. In Portugal you have to subscribe 2 or 3 streaming platforms if want to follow the Portuguese League, the Champions League, and eventually other country leagues (like Premier League and La Liga).
Now, we see huge panels (double the height) for ads in stadiums which become very intrusive when watching on TV (20–30% of the screen ends up being used for ads). Added the hydratation->ADs breaks, and increased World Cup tickets insanely.
Football used to be for everyone, now they're are killing it for almost everyone.
> In Portugal you have to subscribe 2 or 3 streaming platforms
Same in the UK (Sky for EPL+EFL Cup, HBO for EPL+UCL, Amazon Prime for Christmas EPL + occasional cup games) + a TV licence (for the occasional cup game / tournaments.)
If you don't pay for anything, you can watch about 10? cup games a season on ITV. Or go to a pub, obviously (but then you'll be forced to buy drinks.)
You can usually listen to a bunch of games per week via BBC Radio (I think it requires a TV licence if you use streaming but you can still get 5Live on AM radio AFAIK) and TalkSport (also on AM radio.)
TV license is 'required' for all live TV (all channels) + iPlayer. Also if you're watching live sports through e.g. NowTV's website you still need one. It's much wider reaching than just the BBC channels.
Are you going to be leading the campaign to get your national FA to return all of the money it received from the highest-revenue-sharing-ever US World Cup?
Sweden cleared $2.5M in profit from their participation, about the same as the previous edition, all the increase was eaten up by the US taxing the teams and higher costs. That's not nearly enough money to sell out for.
Not at all true. There’s a whole industry around measuring this (e.g. https://www.edo.com). A massive amount of money is spent on advertising for large companies. McD spend ballpark $3bn across the parent and franchisees, they want to make sure they get value.
You can ignore something actively but you are a still picking up on the message of it’s ubiquitousness. I think we have all had the experience of considering buying a {redacted} or something sometime after seeing and ignoring an add for one.
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