prymitive

Here’s an idea: Musk launches a ton of orbital gpus but in reality it’s just an empty shell and real gpus sit in unused grok data centres. How would we even know?

It used to be that you need a good reason to make huge refactorings, because it’s often so much work. Now agent can rewrite half of your code if your prompt is vague enough and you don’t actual try to review it all. And so the “soul” of a program can change dramatically every single day. It’s both great and very much not so.

How do you manage to make Opus follow any rules? Maybe it’s a windsurf thing but I have a ton of custom rules and Opus just ignores most of them. GPT on the other hand follows them like it’s a cult - if I have a rule I can’t ever force it to ignore it. Opus just doesn’t care. If I ask why it’s not following rules it will apologise and suggest creating a rule for it …

I often find myself annoyed when Opus fixes a typo in a comment and decides to run tests, lints and whenever else it can find to run. Often it will start by stashing current changes just to preemptively check if all tests were passing before. And I can blame myself a bit because my rules do say: verify all changes with tests. But as there is that I in AI that is hyped which you’d think means it knows not to put tomatoes into fruit salad …

I need to write code because otherwise LLMs will write too much code, it’s only when you fully understand the problem you can generalise it enough to not end up with 10k lines and 5 abstraction layers for “hello world”. LLMs are token predictors, so all solutions are you tokens, the more problems to solve == the more tokens (code) to output.

Oh the number of time LLM will, for example, be giving me the list of bugs it found in code, when I ask it for a review, just to decide there’s no big half way through explaining it.

I think the problem here is that LLMs aren’t really “intelligence models” but more like “knowledge models”. LLMs don’t “think”, they just use a clever trick to make it seem like they do. I might not understand a lot about current state of AI, but that’s what they seem to be. Give it information and ask to organise it and make links, and they’ll do it, but that’s it, they don’t continually try to get out of the knowledge box they’re at, they don’t even know there’s a box.

Even getting Amazon tablet that’s specifically designed for children comes with useless apps you just cannot get rid off, because they need to shove all their services into your mouth hoping you will accidentally swallow at least some of them. There used to be time when every company had a mission statement and some (sometimes silly) ambitions, today it’s all just money, nothing else, not even a pretending anymore.

Silicon Valley is working round the clock to make bad behaviour as cheap and easy as possible, while taking all the profits. PR floods are probably the most innocent of this. Imagine if you want to send someone abusive text, previously you’d have to spend time and energy writing insults, now the machine can text or even phone someone on your behalf and harass them all day all night. Being a pest to the society was never as easy as right now.

So, essentially, my experience is that it's automated away the easy bits

Yes, which is great for “easy” but mundane and time consuming tasks like refactoring structs when you have a ton of tests that look at snapshots of nested structs etc. Squeezing that last few bits of “make comments consistent with the style and tone of existing comments”, or “stop adding docs that make it sound like an academic paper” or just keep the overall feel of the code same across all files take a lot of effort and energy.

For me the biggest issue with AI coding model is not that it writes code, or how it writes code, or whether it will replace me or not. I mean, these are real problems, but just not the ones that makes the difference to me daily. Instead what sets my feeling about the AI is simple: the experience of working with AI models, because it's the worse experience of my life so far.

Every single LLM will make up stuff, go down rabbit holes I didn't even ask it to visit and infuriate me all day long by doing ALMOST what I asked it to do, but just not quite. Take "yes" to one question as an approval to some other question. Come up with a plan but one you review the plan and accept it it hits some minor issue and then throws away the plan and do whatever it wants. Or when I reject some line of code or don't approve a command it wants to run 9/10 times it just tries to re-add or re-run it as if my rejection was meaningless. And no amount of rules and markdown files ever seems to change its behaviour for long, if at all. It's like working with a sociopath who just doesn't remember anything that happened 5 minutes ago. It's the classic case of "my computer doesn't do what I want, only what I tell it".

And all of that would be fine if it didn't pretend to be a human, if all the UX didn't create the illusion that you interact with some intelligent being, because as long as I remember that this is a cli tool it's all good, I manage my expectations, but the experience sooner or later makes you annoyed and frustrated - and if this was a person they would either stop or you wouldn't never work with them again.

What’s the point of paying people a ton of money and giving them lots of power if they simply follow a script given to them by others?

I am constantly confused at work that people see AI as binary: it’s either a person writing the code and taking ownership of it, or it’s AI and the poor person has no control. It’s rather bespoke or entirely vibe coded. Why? When I use AI it’s still me writing the code, I just get better autocomplete and a tool that can verify my changes using fuzzy sentence as the linting rules. Why did so many people just immediately assumed that it all must be vibe coded now? Maybe it’s because everyone hates reviewing code they didn’t write?

Maybe your agent could have a little blog where it keeps a diary of cool pages it read for you? And then you subscribe to that?

Partially because they think that once employees put enough context and rules into markdown files they can be fired and replaced by an online subscription.

IMHO it’s just good old fomo. They fear that the landscape will shift overnight and they’ll be left with a ton of useless meat bags instead of a pay as you go models that you can upgrade instantly every quarter.

The only thing that interested in is: did they fix screen brightness getting super dim even when the slider is at max? That’s incredibly annoying and frustrating, and it’s been like that since first 26 release. And it’s a clear bug because brightness resets to expected level if I go to photos and open an HDR image. I can wait for autocomplete that doesn’t suggest garbage 50% of the time, but this one is just too annoying.

https://discussions.apple.com/thread/256141236

AIshittification

One can ask, what is a practical difference between “Check everything that it produces” and “Do all the work yourself”?

It’s not typing that’s the bottleneck, at least not often, so this is essentially assuming that you can do all the needed work without actually doing it, which is obviously wishful thinking.

All companies are now AI companies. Just like a while ago all companies were suddenly Ads companies. The entire tech sector is one big FOMO - once you reach certain scale you do exactly the same thing as everyone else.

I have no idea how much I’ve spent, it’s invisible to me, the company doesn’t share it with me. I have no idea what “1 credit” means in terms of $$$, is that 1$? 0.1? 0.01? Is it even a fixed price? I have no idea how much will given take cost. Well, I can ask for a plan and extrapolate from that, but all perfectly reasonable looking plans eventually end up in a rabbit hole. Providers keep introducing new models and each is more expensive while offering modest improvements, it’s a silent inflation.

So I personally can easily believe that. Especially that a lot of people will just try to see if model can make that huge improvement / refactoring they’ve been hoping to do a reality, or tons of experiments to validate ideas.

I have an ancient Withings scale and a Fitbit, it used to be that Withings sends data straight to Fitbit but these days seems gone, so now I have Withings app writing to Apple Health and then Google Health reads from it. Great time to be alive

Call me old but there was a time when “open source project” meant “I had a problem, this is my solution, if someone has the same problem then you are free to use my solution”. These days is more: - building personal brand - showcasing your skills - trying to outsmart somebody else, often because they didn’t merge your pr - sometimes just having fun

And if you work for big org it’s also often “this looks vaguely similar to one of our epics so let’s start using it and demand 24/7 support”

One of the scalars in our feature matrix allowed for an attack vector to move beyond our security barrier causing an incident overflow

Any prediction market bets on what will they rewrite it into next week? Era of just-in-vibe software is here.

What I’m curious about is how well LLMs do when they create something from scratch, because so far my experience was with letting it fix issues or add features to existing codebase where I already shaped the general architecture and put in a lot of guardrails. But what if the architecture is unclear and there is nothing letting agent know if change breaks something or not? My only experience with tiny codebase where it did a lot of scaffolding was poor - it did what I asked for, not what I needed. If i did more of the thinking myself I would realise it’s a code that works but doesn’t solve the problem I’m after.

It’s not like this is a factory floor where you process something coming in and AI suddenly makes the process more efficient and people are idle. Every team in tech world has infinite backlog, you don’t fire 20% the minute someone manages to close a few tickets.

Obviously AI is just a excuse

No alphabro wants to learn from anyone else, they already know everything

You want to see what we’re doing, understand our decisions, and see progress through shipping. Second, a shared sense of pride.

So basically: - recent changes are all crap - so why did you make them?