Is this a symptom of the same phenomenon behind the deluge of disposable JavaScript frameworks of just ten years ago? Is it peer pressure, fear of missing out? At its root, I suspect so; of course I would imagine it's rare for the C-suite to have ever mandated the usage of a specific language or framework, and LLMs represent an unprecedented lever of power to have an even bigger shot at first mover's advantage, from a business perspective. (Yes, I am aware of how "good enough" local models have become for many.)
I don't really have anything useful nor actionable to say here regarding this dialling back of capability to deal with capacity issues. Are there any indications of shops or individual contributors with contingency plans on the table for dialling back LLM usage in kind to mitigate these unknowns? I know the calculus is such that potential (and frequently realised) gains heavily outweigh the risks of going all in, but, in the grander scheme of time and circumstance, long term commitments are starting to be more apparently risky. I am purposefully trying to avoid "begging the question" here; if instead of LLMs, this were some other tool or service, reactions to these events would have been far more pragmatic, with less of a reticence to invest time on in-house solutions when dealing with flaky vendors.
It seems like every LLM thread for the past couple years is full of posts saying that the latest hot AI tool/approach has made them unbelievably more productive, followed by others saying they found that same thing underwhelming.
I don't think many of you have legitimately tried Claude Code, or maybe you're holding it wrong.
I'm getting 10x the work done. I'm operating at all layers of the stack with a speed and rapidity I've never had before.
And before anyone accuses me of being some "vibe coder", I've built five nines active-active money rails that move billions of dollars a day at 50kqps+, amongst lots of other hard hitting platform engineering work. Serious senior engineering for over a decade.
This isn't just a "cool technology". We've exited the punch card phase. And that is hard or impossible to come back from.
If you're not seeing these same successes, I legitimately think you're using it wrong.
I honestly don't like subscription services, hyperscaler concentration of power, or the fact I can't run Opus locally. But it doesn't matter - the tool exists in the shape it does, and I have to consume it in the way that it's presented. I hope for a different offering that is more democratic and open, but right now the market hasn't provided that.
It's as if you got access to fiber or broadband and were asked to go back to ISDN/dial up.
I just don’t see how I could export 10x the work and have it properly validated by peers at this point in time. I may be able to generate code 10-20x faster, but there are nuances that only a human can reason about in my particular sector.
I spend a lot of time reviewing any code that comes out of Claude Code. Even using Opus 4.6 with max effort there is almost always something that needs to be changed, often dramatically.
I can see how people go down the path of thinking "Wow, this code compiles and passes my tests! Ship it!" and start handing trust over to Opus, but I've already seen what this turns into 6 months down the road: Projects get mired down in so much complexity and LLM spaghetti that the codebase becomes fragile. Everyone is sidetracked restructuring messy code from the past, then fighting bugs that appear in the change.
I can believe some of the more recent studies showing LLMs can accelerate work by circa 20% (1.2X) because that's on the same order of magnitude that I and others are seeing with careful use.
When someone comes out and claims 10X more output, I simply cannot believe they're doing careful engineering work instead of just shipping the output after a cursory glance.
In all seriousness though, writing code, or even sitting down and properly architecting things, have never been bottlenecks for me. It has either been artificial deadlines preventing me from writing proper unit tests, or the requirement for code review from people on my team who don't even work on the same codebase as I do on a daily basis. I have often stated and stand by the assertion that I develop at the speed of my own understanding, and I think that is a good virtue to carry forth that I think will stand the test of time and bring about the best organisational outcomes. It's just a matter of finding the right place that values this approach.
Edit for context: My team is an ops team that needed a couple developers; I was picked to implement some internal tooling. The deadlines I was given for the initial development are tied directly to my performance evaluation. My boss has only ever been a manager for almost two years. He has only ever had development headcount for less than a year. He has never been on a development team himself. The man does not take breaks and micromanages at every opportunity he gets. He is paranoid for his job, thinking he is going to be imminently replaced by our (cheaper) EU counterparts. His management style and verbal admonitions reflect this; he frequently projects these insecurities onto others, using unnecessarily accusatory speech. I am not the only developer on my team who has had such interactions with him. I have screenshots of conversations with him that I felt necessary to present to a therapist. This degree of time pressure is entirely unprecedented in my 20 year career. Yes, this is a dysfunctional environment.
After I solved entrepreneurship I decided to retire and I now spend my days reading HN, posting on topics about AI.
I mostly believe you. I have seen hints of what you are talking about.
But often times I feel like I’m on the right track but I’m actually just spinning when wheels and the AI is just happily going along with it.
Or I’m getting too deep on something and I’m caught up in the loop, becoming ungrounded from the reality of the code and the specific problem.
If I notice that and am not too tired, I can reel it back in and re-ground things. Take a step back and make sure we are on reasonable path.
But I’m realizing it can be surprisingly difficult to catch that loop early sometimes. At least for me.
I’ve also done some pretty awesome shit with it that either would have never happened or taken far longer without AI — easily 5x-10x in many cases. It’s all quite fascinating.
Much to learn. This idea is forming for me that developing good “AI discipline” is incredibly important.
P.s. sometimes I also get this weird feeling of “AI exhaustion”. Where the thought of sending another prompt feels quite painful. The last week I’ve felt that a lot.
P.p.s. And then of course this doesn’t even touch on maintaining code quality over time. The “after” part when the LLM implements something. There are lots of good patterns and approaches for handling this, but it’s a distinct phase of the process with lots of complexities and nuances. And it’s oh-so-temping to skip or postpone. More so if the AI output is larger — exactly when you need it most.
I struggle to believe that a ton of seemingly intelligent software engineers are too dumb to figure out how to use Claude code to get reliable results, it seems much more likely to me that it can do well at isolated tasks or new projects but fails when pointed at large complex code bases because it just... is a token predictor lol.
But yeah spinning up a green fields project in an extensively solved area (ledgers) is going to be something an AI shines at.
It isn't like we don't use this stuff also, I ask Cursor to do things 20x a day and it does something I don't like 50% of the time. Even things like pasting an error message it struggles with. How do I reconcile my actual daily experience with hype messages I see online?
> If you're not seeing these same successes, I legitimately think you're using it wrong.
I'm not sure how you could say that, considering I'm not using it at all. I don't want to, and I don't plan to. If that becomes an issue, I'm exiting this industry because I simply don't fucking care any longer. I am fine living the rest of my life and dying happy and sore being an automotive technician.
The challenge now is how to plan architectures and codebases to get really big and really scale, without AI slop creating hidden tech debt.
Foundations of the code must be very solid, and the architecture from the start has to be right. But even redoing the architecture becomes so much faster now...
Need some help selling these notepad apps, do you have a prompt for that?
I'm just curious, why do you "have to"? Don't get me wrong, I'm making the same choice myself too, realizing a bunch of global drawbacks because of my local/personal preference, but I won't claim I have to, it's a choice I'm making because I'm lazy.
What is “using it right”? You wrote claims, but explain nothing about your process. Anything not reproducible is either luck or lie.
Yet
You sound like a pro wrestler. I'd like to know what "hard-hitting" engineering work is. Hydraulic hammers?
Here's a reason not in your list.
Short version: A kind of peer pressure, but from above. In some circles I'm told a developer must have AI skills on their resume now, and those probably need to be with well known subscription services, or they substantially reduce their employment prospects.
Multiple people I know who are employers have recently, without prompting, told me they no longer hire developers who don't use AI in their workflow.
One of them told me all the employers they know think "seniors" fall into two camps, those who are embracing AI and therefore nimble and adaptive, and those who are avoiding it and therefore too backward-looking, stuck-in-their-ways to be a good hire for the future. So if they don't see signs of AI usage on a senior dev's resume now, that's an automatic discard. For devs I know laid off from an R&D company where AI was not permitted for development (for IP/confidentiality reasons), that's unfair as they were certainly not backward-looking people, but the market is not fair.
Another "business leader" employer I met recently told me his devs are divided into those who are embracing AI and those who aren't, said he finds software feature development "so slow!", and said if it wasn't for employment law he'd fire all his devs who aren't choosing to use AI. I assume he was joking, but it was interesting to hear it said out loud without prompting.
I've been to several business leadership type meetups in recent months, and it seems to be simply assumed that everyone is using AI for almost everything worth talking about. I don't think they really are, so it's interesting to watch that narrative playing out.
Isn't this almost certainly against ToS, at least if you're using "plans" (as opposed to paying per-token)?
Why does it sound like you're on drugs? I know that sounds extremely rude, but I can't think of any other reasonable comparison for that language.
It's hard to take these kinds of endorsements seriously when they're written so hyperbolically, in terms of the same cliches, and focused on entirely on how it makes you feel rather than what it does.
This has basically been what all of Silicon Valley sounds like to me for a few years now.
They are known for abusing many psycho-stimulants out there. The stupid “manifesto” Marc Andreessen put out a while back sounded like adderall-produced drivel more than a coherent political manifesto.
Code is notation, just like music sheets, or food recipes. If your interaction with anyone else is with the end result only (the software), the. The code does not matter. But for collaboration, it does. When it’s badly written, that just increase everyone burden.
It’s like forcing everyone to learn a symphony with the record instead of the sheets. And often a badly recorded version.
Do you think that is impossible? There are plenty of people who enjoy composing music on things like trackers, with no intent of ever playing said music on an instrument.
I love coding, but I also like making things, and the two are in conflict: When I write code for the sake of writing code, I am meticulous and look for perfection. When I make things, I want to move as fast as possible, because it is the end-product that matters.
There is also a hidden presumption in what you've written that 1) the code will be badly written. Sometimes it is, but that is the case for people to, but often it is better than what I would produce (say, when needing to produce something in a language I'm not familiar enough with), 2) and that the collaboration will be with people manually working on the code. That is increasingly often not true.
What I don’t understand, are the people who let it go over night or with whole “agent teams” working on software. I have no idea how they trust any of it.
As an example, a long term goal at the employer I work for is exactly this: run LLMs locally. There's a big infrastructure backlog through, so it's waiting on those things, and hopefully we'll see good local models by then that can do what Claude Sonnet or GPT-5.3-Codex can do today.
There is a cost though, the context switches of topics aren't free. But if I need to visualise a something, I let an LLM create a page. If I have two tables of data that needs to be joined/mapped, I let an LLM do the first shot, often that is enough.
I cannot even hope to reach that speed. It isn't a magic tool, but it really accelerates some task.
That speed allows for in-house solutions to become viable again, software that really adapts specific business processes instead of some wonky ERP package that never really fit what you were trying to do.
I have our dbs schema checked into a Gitea repository, which our AIs can just access to quickly ingest schema definitions. If data safety is an issue, use a local model. It is extremely beneficial if you quickly can establish context and let your AI deal with real problems. And it is quite good at that.
I still use more traditional approach for finding bugs and other issues in my code, but the agentic workflow doesn't give me any net value.
Maybe in 5 years we'll have an open weights model that is in the "good enough" category that I can run on a RTX 9000 for 15k dollars or whatever.
It's why we pay stupid amounts for takeout when it's a button away, it's why we accept the issues that come with online dating rather than breaking the ice outside, it's why there's been decades scams that claim to get you abs without effort...
LLMs are the ultimate friction removal. They can remove gaps or mechanical work that regular programming can, but more importantly they can think for you.
I'm convinced this human pattern is as dangerous as addiction. But it's so much harder to fight against, because who's going to be in favor of doing things with more effort rather than less? The whole point of capitalism is supposed to be that it rewards efficiency.
Aw hell. You found my vice and my own cognitive dissonance here. If I want to truly stand by my convictions, I should probably cook more and log off. Waiting for signs that the tides are turning and that people are beginning to value a slower, more methodical approach again isn't doing anything in the current moment to stave off the genuine feelings of dread that have honestly led to some suicidal ideation.
(this is serious and not sarcasm, by the way)
By which I mean, it's likely you're not the only one feeling that dread. We're due for a counter movement, and it's a matter of time to see it flower.
We're paying for servers that sit idle at night, you don't find enough sysadmins for the current problems, the open source models aren't as strong as closed source, providing context (as in googling) means you hook everything up to the internet anyway, where do you find the power and the cooling systems and the space, what do you do with the GPUs after 3 years?
Suddenly that $500/month/user seems like a steal.
Lately though the RAM crisis is continuing and making things like this more unfeasible. But you can still use a lot of smaller models for coding and testing tasks.
Planning tasks I'd use a cloud hosted one, for now, because gemma4 isn't there yet and because the GPU prices are still quite insane.
The cool and fun part is that with ollama and vllm you can just build your own agentic environment IDE, give it the tools you like, and make the workflow however you like. And it isn't even that hard to do, it just needs a lot of tweaking and prompt fiddling.
And on top of that: Use kiwix to selfhost Wikipedia, stackoverflow and devdocs. Give the LLM a tool to use the search and read the pages, and your productivity is skyrocketing pretty quickly. No need anymore to have internet, and a cheap Intel NUC is good enough for self-hosting a lot of containers already.
Source: I am building my own offline agentic environment for Golang [1] which is pretty experimental but sometimes it's also working.
The LLM bit though, personally, is just not for me.
It would be cool to run SOTA models on my own hardware but I can't. Hence, the subscription.
That said, I’m not sure I follow your statement of less resistance to the development of internal tools when the opposite seems to be the case; companies (or more specifically developers) are perhaps too quick to think they can just vibe-code a replacement for any vendor in a weekend these days.
0 as of this writing, it's noticeable. Lots of "should I continue?" And "you should run this command if you want to see that information." Roadblocks that I hadn't seen in a year+
That means they are going to be far more constrained infrastructurally than some of the competition. I think this is some of the constraints that we are seeing.
They don't have compute because they didn't play the game and get the good rates a couple of years ago, and are now forced to work with third-rate providers. That's not a strategy.
I would take everything he says with a huge grain of salt.
[0] “We’re buying a lot. We’re buying a hell of a lot. We’re buying an amount that’s comparable to what the biggest players in the game are buying.”
“Profitability is this kind of weird thing in this field. I don’t think in this field profitability is actually a measure of spending down versus investing in the business.”
[1] “You don’t just serve the current models and never train another model, because then you don’t have any demand because you’ll fall behind.”
So he's not spending so they can be profitable, AND spending as much as the biggest players are spending, AND not really looking at profit as a measure of anything? K.
they're looking to IPO in 2028 vs 2030 for OpenAI, who have raised more than double the funds
so they're willing to play fast and loose with the terms and conditions of existing customers trying to make it happen
those pockets must be drying up really fast
But as it stands, the more likely reason is capacity crunch caused by a chips shortage and demand heavily outpacing supply. You vibe coding reason is based on as much vibes as their code probably is.
I recently vibe-translated a simple project from Javascript to C, where Javascript was producing 30fps, and the first C version produced 1 frame every 20 seconds. After some time trying to get the AI to optimize it, I arrived at 1fps from the C project. Not a win, but the AI did produce working C code.
I have no doubt that if I had done this myself (which I will do soon), with the appropriate level of care, it would have been 30fps or more.
Codex shines really well at what I call "hard problems." You set thinking high, and you just let it throw raw power at the problem. Whereas, Claude Code is better at your average day-to-day "write me code" tasks.
So the difference is kind of nuanced. You kind of need to use both a while to get a real sense of it.
They’re still doing subscriptions: https://developers.openai.com/codex/pricing
There was a headline saying they were, and the actual article showed they were doing nothingbof the sort.
If you read HN headlines, and don't even bother to click into the comments and see everyone calling out the headline as bogus, you might think something like your statement is true.
Edit: Looks like it still works with subs, they just measure usage per token instead of per message.
Before a Subscription was the cheapest way to gain Codex usage, but now they've essentially having API and Subscription pricing match (e.g. $200 sub = $200 in API Codex usage).
The only value of a subscription now is that you get the web version of ChatGPT "free." In terms of raw Codex usage, you could just as easily buy API usage.
edit: This is currently rolled out for Enterprise, but is coming to Pro/Plus soon. The people below saying "I haven't had this issue" haven't yet*.
I don't think it's made out like that, I'm on the ChatGPT Pro plan for personal usage, and for a client I'm using the OpenAI API, both almost only using GPT 5.4 xhigh, done pretty much 50/50 work on client/personal projects, and clients API usage is up to 400 USD right now after a week of work, and ChatGPT Pro limit has 61% left, resets tomorrow.
Still seems to me you'd get a heck more out of the subscription than API credits.
Day 1: 2
Day 2: 3
Day 3: 1
Not sure how I can hit such limits so quickly with such low scores on its own chart.
Pentagon: No
OpenAI: We are okay if the line is merely a suggestion and we encourage you not to cross it!
Pentagon: Yes we pick that option
That has led to a significant number of people switching over from openai, or at least stating they were going to do so.
I have cancelled my subscription last week, I'll see them when they fix this nonesense
For some context, they added 2x Palantir or .75x Shopify or .68x Adobe annual revenue in March alone.
Fwiw there are worse delays from second tier providers like moonshot's kimik2.5 that are also popular for agentic use.
Vibe coding doesn't automatically mean lower quality. My codebase quality and overall app experience has improved since I started using agents to code. You can leverage AI to test as well as write new code.
It’s great to buy dollars for a penny, but the guy selling em is going to want to charge a dollar eventually…
Do you feel there is enough visibility and stability around the "Prompt -> API token usage" connection to make a reliable estimate as to what using the API may end up costing?
Personally, it feels like paying for Netflix based on "data usage" without having anyway for me to know ahead of time how much data any given episode or movie will end up using, because Netflix is constantly changing the quality/compression/etc on the fly.
I agree that ex ante it’s tough, and they could benefit from some mode of estimation.
Perhaps we can give tasks sizes, like T shirts? Or a group of claudes can spend the first 1M tokens assigning point values to the prospective tasks?
Take the response on another post about Claude Code.
https://news.ycombinator.com/item?id=47664442
This reads like even if you had a rough idea today about what usage might look like, a change deployed tomorrow could have a major impact on usage. And you wouldn't know it until after you were already using it.
Of course, I have no idea how MS is justifying the Copilot pricing. I can't imagine any world in which it is sustainable, so I'm trying to get as much as I can out of it now before they jack up prices.
Now we’re going to find out what these tools are really worth.
So I noticed the model is purposefully coming with dumb ideas or running around in circles and only when you tell it that they are trying to defraud you, they suddenly come back with a right solution.
It works out even if some customers are able to eat a lot, because people on average have a certain limit. The limits of computers are much higher.
If an hour of an excellent developer's time is worth $X, isn't that the upper bound of what the AI companies can charge? If hiring a person is better value than paying for an AI, then do that.
They can charge whatever they want, I think many people like to make business decisions based on relative predictability or at least be more aware that there's a risk. If they want it to be "some weeks you have lots of usage, some weeks less, and it depends on X factors, or even random factors" then people could make a more informed choice. I think now it's basically incredibly vague and that works while it's relatively predictable, and starts to fail when it's not, for those that wanted the implied predictability.
I'm not sure how businesses budget for llm APIs, as they seem wildly unpredictable to me and super expensive, but maybe I'm missing something about it.
1. Me not wanting that for context management reasons
2. It burning tokens on an expensive model.
Literally a conversation that I just had:
* ME: "Have sonnet background agent do X"
* Opus: "Agent failed, I'll do it myself"
* Me: "No, have a background agent do it"
* Opus: Proceeds to do it in the foreground
* Flips keyboard
This has completely broken my workflows. I'm stuck waiting for Opus to monitor a basic task and destroy my context.
Luckily, ISPs tend to be quite reliable and don't have outrageous price hikes, but maybe that's because of regulation or focused competition, I'm not sure.
We'll see AI chat replace Google, we'll see companies adopting AI in high-value areas, and we'll see local models like Gemma 4 get used heavily.
AI winter will see a disappearance of the clickbait headlines about everyone losing their jobs. Literally nobody is making those statements taking into account that pricing to this point is way less than the profit maximizing level.
I’ve been toying around at home with it and I’ve been fine with its output mostly (in a Java project ofc), but I’ve run into a few consistent problems
- The thing always trips up validating its work. It consistently tries to use powershell in a WSL environment I don’t have it installed in. It also seems to struggle with relative/absolute paths when running commands.
- Pricing makes no sense to me, but Jetbrains offering seems to have its own layer of abstraction in “credits” that just seem so opaque.
Then again, I mostly use this stuff for implementing tedious utilities/features. I’m not doing entity agent written and still do a lot of hand tweaks to code, because it’s still faster to just do it myself sometimes. Mostly all from all from the IDE still.
Unless they meant "all code that needs to be written has already been written" so their mission is to prevent any new code from being written via a kind of a bait and switch?
I think Anthropics model has conflict of interest. They seem to have nerfed the models so that it takes more iterations to get the result (and spend more money) than it used to where e.g. Opus would get something right first time.
At my workplace we have been sticking with older versions, and now stick to the stable release channel.
Is Microsoft (one of the largest companies in the world) really a victim of brand death?
Not worth the money now, will be canceling unless fixed soon.
It's actually via quantum entanglement.
prompts. tool calling quirks. evals. auth. retries. all the weird failure modes your team already paid to learn.
There was constant drama with CC. Degradation, low reliability, harness conspiring against you, and etc – these things are not new. Its burgeoning popularity has only made it worse. Anthropic is always doing something to shoot themselves in the foot.
The harness does cool things, don't get me wrong. But it comes with a ton of papercuts that don't belong in a professional product.
The rest of the organisation, which is not software development or IT related, mainly uses GPT models. I just wish I hadn't taught risk management about claude code so they weren't wasting MY tokens.
Obviously in hindsight it would be unfair to Anthropic to judge them on an unstable day so I'l leave those complaints aside but I hit the session limit way too fast. I planned out 3 tasks and it couldn't finish the first plan completely, for that implementation task it has seen a grand total of 1 build log and hasn't even run any tests which already caused it to enter in the red territory of the context circle.
It was even asking me during planning which endpoints the new feature should use to hook into the existing system, codex would never ask this and just simply look these up during planning and whenever it encounters ambiguity it would either ask straight away or put it as an open question. I have to wonder if they're limiting this behavior due trying to keep the context as small as possible and preventing even earlier session limits.
Maybe codex's limits are not sustainable in the long run and I'm very spoiled by the limits but at this point CC(sonnet) and Codex(5.4) are simply not in the same league when comparing both 20 dollar subscriptions.
I will also clearly state that the value both these tools provide at these price points are absolutely worth it, it's just that codex's value/money ratio is much better.
CC is a better implementation and seems to be fairly economic with token usage. That is the really the only defining point and, I suspect, Anthropic are going to have a lot of trouble staying relevant with all the product issues.
They were far ahead for a brief period in November/December which is driving the hype cycle that now appears to be collapsing the company.
You have to test at least every month, things are moving quickly. Stepfun is releasing soon and seems to have an Opus-level model with more efficient architecture.
One example is I have a multi-stage distillation/knowledge extraction script for taking a Discord channel and answering questions. I have a hardcoded 5k message test set where I set up 20 questions myself based on analyzing it.
In my harness Minimax wasn't even getting half of them right, whereas Sonnet was 100%. Granted this isn't code, but my usage on pi felt about the same.
What are you using to drive the Chinese models in order to evaluate this? OpenCode?
Some of Claude Code's features, like remote sessions, are far more important than the underlying model for my productivity.
I keep coming back to it because I can run it as a manager for the smaller tasks.
Free and local.
Maybe you should consider....local models instead?
I doubt even the core engineers know how to begin debugging that spaghetti code.
