The question formed wrong . They killed entire industries. I feel like they are at inflection point where they hired fde , but for now they try to solve fancy problems to do not visually scare their customers .
Yet picture is very sad , industries affected to the point that majority of the companies asking about their existence:
1) software dev tools all IDE , developer analytics tools eg jellyfish etc . Dead . On the same note : warp.dev that raised $80m a year ago as an ai terminal… can barely explain why do they exist now.
Visual workflow editors . Older ones and even n8n. There were literally 1000 companies that were doing small deployments. Why do you need it now ? A year ago half of the Internet was booming about these tools .
Any data visualization tools . Gone .
Data integration tools all kind of crm to crm to erp to something else . Solved problem
And you can go on and on . I would probably not exaggerate if I’d say that millions of businesses are heavily affected by, from tiny one to adobe .
Yeah I think people just don't quite understand what's happening yet.
There's no reason for OpenAI/Google/Anthropic/etc to start other software businesses because "LLMs" will be the only software that anybody will ever pay for.
Why would you have a different "app" to do something when you can just do it all in Claude or Gemini or ChatGPT? We'll be there soon enough.
- stuff that’s easily replicable that I can tailor to my use-case (e.g. I have an alternative to git add -p that I generated that I find much more ergonomic)
- stuff that’s a giant boondoggle to replicate because there are so many edge cases and considerations that it takes years of iterations to arrive at something stable
Am I really going to create an iTerm2 alternative? What the hell would I want out of an alternative?
Am I really going to create a git alternative? Who in the right mind would take the time to even learn it?
And also, no, Claude isn’t going to replace git. Deterministic compute still has a place in software, nondeterministic compute isn’t going to take over just because the UI is more pleasant for nontechnical folks.
A chat window that takes multiple seconds to respond and behaves non-determinstically is a pretty bad paradigm for most computer tasks. It just happens to work for software development in particular.
Twitter consensus now is more like LLMs will be entirely commoditized, apps & features will be cheap, and only systems of record will have lasting value.
A chat window that takes multiple seconds to respond, versus your buddy Guy who just went out on lunch.
Non-deterministic behavior from your chatbot, like how the visual design artist's client keeps sending back and forth emails asking for it to "pop" more
You ask the chat window to build a new tool or visualization or simulation or data editing tool for you...and it spins for a few seconds or 10s of seconds then presents it to you, ready to be re-used and designed to interact with both you directly and the AI itself.
Perhaps even by other people, and over time, continuously improving as we discover new use cases or that things are more complicated than they seemed on the first pass. Like... regular software, and not "do[ing] it all in Claude or Gemini or ChatGPT"
Still shocked that people use LLMs as automation for some things that should be done with software.
“Claude deploy this to dev”
vs
“Claude build me a tool that allows me to deploy to dev with a single click / command from CLI”
Orders of magnitude less expensive for the latter than the former. The former usually costs a few cents and the latter maybe a one time cost of 40 cents and then free forever afterwards.
So at the end of the day you still need an app… and maybe instead of spending tokens every time you want an app you just use a prebuilt one… :surprised-pikachu:
If you just need a narrow subset of the functionality for now, might be cheaper in tokens to just vibe it than the attentional cost of searching for just the right software...let alone paying for it.
Have you tried chatjimmy? It operates at the speed of thought. Imagine this with one of the recent frontier AI. AI that operates faster than you can express your thoughts seems like a foregone conclusion eventually but may not make sense right now as they try to reach the limit of what they can make in a model.
"speed of thought" is wildly underselling how fast chatjimmy is. The speeds claimed by system one decision models are slow in comparison to chatjimmy, which produces actual text.
you use the chat window to make the software which is deterministic and can be tested. Then the chat window uses that software to do the analytics or whatever else you need. Op is correct.
99.999999% of people have no interest in making software, they just want to do whatever they need to with minimal hassle. You may as well say restaurants are going out of business because microwaves exist.
Even the people making software barely want to make software honestly, but you gotta make that daily bread somehow and sometimes it's kinda cool I guess? But like people overestimate the desire of the average person to be their own software maintainer, most people consume, not produce, regardless of ease and trying to turn everyone into a producer is... kind of the opposite of where society has been going for a very long time.
Because selling access to models will not be a good business. But they can form a cartel and keep frontier models to themselves. This will also prevent distillations.
Access to models will trend towards zero, nobody has a moat, open weight models already exist, and inference is getting cheaper all the time.
Ultimately the value will be in the data.
We're in a window here where the data is silo'd and we can use agents to vibe code / glue it all together and create traditional apps that people will still use, but I think that window is narrow.
Eventually today's LLM providers will incorporate direct access to more data sources, and the data won't be silo'd for them - it'll all be available. And instead of third parties vibe-coding apps, the LLM companys' web UIs will become the apps that link everything together directly.
It's not even clear that access to data is that important. It's important for LLMs, but somehow we manage to turn babies into intelligent adults without them reading more than a few hundred books - for some, no books at all. Whatever is the breakthrough after LLMs likely won't need lots of data.
Anthropic, Google, OpenAI, Meta, xAI(whatever is it called these days) are sitting on mountains of compute.
Yes, local and open-weight models will continue improving, and they'll be good enough for an increasing number of tasks. But there's a difference between making yesterday's capabilities cheap and pushing the frontier forward.
The most capable models will likely continue to demand enormous compute resources, both for training and inference.
And the pricing is already there - we're charged for token usage, not model access. Draft an email, summarize a paper - basically free. But the "big stuff" will require Frontier-models with Frontier-level of compute.
OpenAI spent something like tens of millions on "solving" a Millenium Prize math model. And there will always be another problem worth throwing massive amounts of compute at, whether it's mathematics, scientific discovery, engineering, etc.
>Because selling access to models will not be a good business
Let me go on a tangent to make a point. For some countries if you want a US Visa Consulate appt today they only open 3 months out and are booked constantly. They block you for 10mins on the 5th refresh.
It’s well known on crrtain communities that the only way to get one is with an ai agent that can patiently work around this and jump on the bookings with perfect timing or refresh within the bounds of the detection to nab a cancellation opening.
So we’re starting to head into a world where every single person needs an ai subscription just to deal with bureaucracy.
It’s a fucking fantastic business and i don’t understand how you could suggest it’s not good business.
> every single person needs an ai subscription just to deal with bureaucracy.
If everyone uses an AI agent as you suggest, the appointment schedule will be bottlenecked just the same as if everyone only used a web browser. Using AI won’t achieve the goal of everyone getting an appointment. So AI won’t actually be useful here if everyone uses it.
> Why would you have a different "app" to do something when you can just do it all in Claude or Gemini or ChatGPT? We'll be there soon enough.
At least from the engineering perspective, the app has a massive advantage: determinism. If I write something in Python or Java or whatever, it has set inputs and outputs and those can be proven to accomplish a computational task because they are working in a logical system.
If I ask an LLM to do that same task, it has inputs and outputs, but the logic isn't anywhere nearly as defined. There will be a chance, no matter how small, that will not act in a way that makes any sort of logical sense given the constraints of the task it was meant to accomplish.
When you combine that with the fact that deterministic applications are far cheaper to run, at least for the foreseeable future, the app wins.
You're right but the trick LLM-backed tools have is that they can just write traditional code on the fly.
There are usability and performance problems right now which is why we have this interregnum. But as these systems evolve, the tools can offload "expensive" operations to traditional compute by writing the glue code on demand, and persist the code for future use (so regenerating it won't be required again later) when the user confirms it's doing what it's supposed to do. You can A/B test it in real time and ask the user to pick the "better" result.
Same is true for e.g. GUI elements, widgets, etc. Write it the first time, have your user verify it, persist it, retrieve it.
And maybe you have a couple of people in your org who work through the process of generating a bespoke app that processes data with a GUI optimized for whatever they're doing, but it's all mediated directly through your vendor. The users run through the process all in the web UI of whatever LLM vendor the org's data is silo'd with, the output is a mix of traditional computation and LLM contexts that anybody can maintain via asking the tool to change itself.
this is a point that i think is missed on many people (myself included earlier in the year). Sure, the LLM is non-deterministic but it can write code that is not and test cases to verify it. Then, once verified correct, it can use what it wrote to perform the task in a deterministic way. Even though the LLM is still non-deterministic all it has to get right is the arguments to the software which is much easier than the full logic of the task. That's very powerful.
I've seen this first hand when asking AI to do non-trivial analysis over a couple of spreadsheets and then also a database. It writes python to do this, tests it with sample data, and then calls the python it creates to do the processing on the actual data.
Even if the process of creating software was 100% cost-free and bug-free (which we know isn't true, even the most efficient LLMs actively burn tokens and cost you money) - pre-built software still has the advantage of being opinionated and having features I never thought to ask about.
I might have the general desire to play a video game with my friend where we shoot WW2 like guns together. I'm willing to bet that a video game company with artists, game designers, historians, etc. is better able to articulate that into existence than I can. Especially given I might not be willing to spend the time to do that...
Yes, I still hear software development coworkers who want to replace all our tested, deterministic software with non-deterministic, high latency, much more expensive LLM based systems.
Have the LLMs generate even more deterministic software to solve well defined needs and keep the LLMs for solving higher level problems using the deterministic software's outputs as inputs.
But you just ask the LLM to produce a new well-tested artifact to perform those tasks for you, then let it call them and orchestrate them as needed.
IT folk have long been creating quality of life scrips for themselves to automate tasks, the LLMs make this even easier.
So we get more determinism for cheaper, if done correctly.
Yeah I think efficiency is still a counterargument to the model doing everything.
If I need to process a million items it still wouldn't make sense to feed them directly to the model and burn a crazy amount of tokens
Of course the model can produce code to process them on the fly but if its a repeated task why would I want that to be re-created every time, especially if I've already tested/validated it
That overhyped thing that never did anything well and everybody that used them regretted it later? Yeah, hyped things tend to die once the money used to hype them ends.
> Any data visualization tools
Microsoft killed them with anticompetitive practices. It helps that every single one of them tried very hard to kill themselves by being as hostile as possible.
> Data integration tools all kind of crm to crm to erp to something else
Yep, everybody writes those in Python nowadays. Apache is a great market killer, the best kind of market killer.
I heard some chatter about Warp some six months ago and decided to give it a try. Blew my mind that a terminal with an LLM wrapper side-panel raised $80M
I'm sure there's some impressive stuff in there that the warp team built but also the second my own _terminal_ tried to get me to subscribe to a monthly plan I uninstalled that shit so fast.
Data visualization is such a dead end product. Wow lots of pretty charts, can you actually interpret the data and make an informed decision? Any idiot can throw shit into Excel and make charts and pivot tables. An AI that can not only interpret the data but also offer advice on how one should react is way more valuable.
Of course you shouldn't just rely on AI that's consumed every MBA book to give you all of your business advice. Sometimes the textbook response is not always the best response.
Jupyter notebooks were the canonical solution to data visualization problems if you needed more than Excel, but required training in understanding Python or similar high level programming language.
Lol, "software dev tools all IDE , developer analytics tools eg jellyfish etc . Dead"
This is the most insane perspective, it's like you have now idea what is happening across the industry. In you fantasy world here, are you saying devs are just yeeting slop into production, no debugging, no profiling, no code review, just prompt to prod? Because that's not happening.
Seems like a really bad article. They have a loss, but their revenue is still trending up, which suggests they are spending more money building products (perhaps with better AI tooling). That's a pretty normal thing for a healthy business to do in this landscape.
The article doesn't mention this at all. It just blindly includes that graph and than muses about the death of Jetbrains for a few paragraphs.
Maybe I should rephrase, it's not happening at any org that will be in business beyond the next couple years. Customers don't care about your software factory, they care about a product that works reliably.
I actually disagree here, what matters most is procurement & distribution. You can sell absolute dog water software (see: Teams[1]) and capture a market with the right procurement and distributions pipelines.
The sad reality IMO is that the quality of software matters much less than we (the engineers) would hope it does.
Yeah I can use it to see and hear my coworkers and their screens and exchange text messages through a crappy editor and schedule meetings. That's really all a business needs to keep using it.
> Customers don't care about your software factory, they care about a product that works reliably.
You don't think AI is capable of putting out CRUD apps into the ether that work reliably? Even my local GLM5.3-Flash is capable of doing that. These products make up a non negligible amount of the industry. Additionally reducing headcount is about to hit in the next year or so. Where are juniors gonna find jobs? Etc etc...
I personally rarely touch an IDE anymore. I talk to lots of people with the same experience. This is anecdotal, sure, but if you ask any software developer that isn't staunchly anti-ai or just living with their head in the sand, you'll probably get told something similar.
I find this very hard to believe, even though I use plenty of frontier AI in my dev process. I have to live in vscode to get things done because I still frequently need to look at the generated code and point out issues to get the AI past some problem it's stuck at.
Improve your workflow.
I have 4 instances of intellij, 2 web storm, 2 Rustrover and two phpstorm open for WEEKS. Along with some vs code instance.
I think I unminimized only one just today to check something: I was being super lazy and I just wanted to check git status without typing anything.
I had to rebuild multiple images with new structure to mitigate php2shell; had to patch more than 15 servers etc just in last few days. Fork old other people's images and update them, add some features while at it. Bug fix old php sites not running on new php. And so on and so on...all done with 5/6 agents running in parallel.
I have the IDEs open but minimized. Don't need them really...
i like reading the generated code as a code review, and then i can leave inline comments back to the ai, rather than trying to point the ai to the right lines via chat.
im already practiced at reviewing code through code review tools, so id rather do it that way than in vscode
No one's going to come out and admit that they're just stamping LGTM on every pull request because they can't bear to review another net 2,000 lines of AI-generated code. The problem is that right now the tools we have for code review were designed for a world where code was cheap.
That site is AI slop with a bunch of questionable nonsense. For example, they suggest that Devin, Cognition's product, shut down. I'm not even sure where they got that information.
Wow I had no idea Mechanical Turk closed. I assumed it would be quite valuable for doing a lot of data labelling type of work that percolates into AI models.
Yet picture is very sad , industries affected to the point that majority of the companies asking about their existence:
1) software dev tools all IDE , developer analytics tools eg jellyfish etc . Dead . On the same note : warp.dev that raised $80m a year ago as an ai terminal… can barely explain why do they exist now.
Visual workflow editors . Older ones and even n8n. There were literally 1000 companies that were doing small deployments. Why do you need it now ? A year ago half of the Internet was booming about these tools .
Any data visualization tools . Gone .
Data integration tools all kind of crm to crm to erp to something else . Solved problem
And you can go on and on . I would probably not exaggerate if I’d say that millions of businesses are heavily affected by, from tiny one to adobe .