Comment by spaceman_2020

> I predict that we'll see some languages really pull ahead of others in the next few years based on their advantages for AI-powered development.

Oh absolutely. I've been using Python for past 15 or so years for everything.

I've never written a single line of Rust in my life, and all my new projects are Rust now, even the quick-script-throwaway things, because it's so much better at instantly screaming at claude when it goes off track. It may take it longer to finish what I asked it to do, but requires so much less involvement from me.

I will likely never start another new project in python ever.

EDIT: Forgot to add that paired with a good linter, this is even more impressive. I told Claude to come up with the most masochistic clippy configuration possible, where even a tiny mistake is instantly punished and exceptions have to be truly exceptional (I have another agent that verifies this each run).

I just wish there was cargo-clippy for enforcing architectural patterns.

and with types, it makes it easier for rounds of agents to pick up mistakes at compile time, statically. linting and sanity checking untyped languages only goes so far. I've not seen LLM's one shot perl style regexes. and javascript can still have ugly runtime WTFs

Hah! I actually initiated the project because I'm a long time XBMC/Kodi user. I started using it when it was called XBMC, on an actual Xbox 1. I am sick and tired of its crashing, poor playback performance, and increasingly bloated feature set. It's embarrassing when I have friends or family over for movie night, and I have to explain "Sorry folks, Kodi froze midway through the movie again" while I frantically try to re-launch/reboot my way back to watching the movie. VLC's playback engine is much better but the VLC app's TV UX is ass. This application actually uses the libVLC playback engine under the hood.

By tomorrow the app will be replaced with a new version from the other competitor, by that time the memory leak will not reveal itself

Part of the "one day" development time was exhaustively testing it. Since the tool's scope is so small, getting good test coverage was pretty easy. Of course, I'm not guaranteeing through formal verification methods that the code is bug free. I did find bugs, but they were all areas that were poorly specified by me in the requirements.

> At work I only have access to calude using the GitHub copilot integration so this could be the cause of my problems.

You really need to at least try Claude Code directly instead of using CoPilot. My work gives us access to CoPilot, Claude Code, and Codex. CoPilot isn’t close to the other more agentic products.

Ah, but you’re at the beginning stage young grasshopper. Soon you will be missing that horizontal ultra wide monitor as you spin up 8 different Claude agents in parallel seasons.

The AI bubble is kind of like the dot-com bubble in that it's a revolutionary technology that will certainly be a huge part of the future, but it's still overhyped (i.e. people are investing without regard for logic).

What exactly does it say, in your opinion? I can imagine 4-5 different takes on that post.

I strongly concur with your second statement. Anything other than agent mode in GH copilot feels useless to me. If I want to engage Opus through GH copilot for planning work, I still use agent mode and just indicate the desired output is whatever.md. I obviously only do this in environments lacking a better tool (Claude Code).

Check out Antigravity+Google AI Pro $20 plan+Opus 4.5. apparently the Opus limits are insanely generous (of course that could change on a dime).

I'd used both CC and Copilot Agent Mode in VSCode, but not the combination of CC + Opus 4.5, and I agree, I was happy enough with Copilot.

The gap didn't seem big, but in November (which admittedly was when Opus 4.5 was in preview on Copilot) Opus 4.5 with Copilot was awful.

This is how Beads works, especially with Claude Code. What I do is I tell Claude to always create a Bead when I tell it to add something, or about something that needs to be added, then I start brainstorming, and even ask it to do market research what are top apps doing for x, y or z. Then ask it to update the bead (I call them tasks) and then finally when its got enough detail, I tell it, do all of these in parallel.

There are several rubs with that operating protocol extending beyond the "you're holding it wrong" claim.

1) There exists a threshold, only identifiable in retrospect, past which it would have been faster to locate or write the code yourself than to navigate the LLM's correction loop or otherwise ensure one-shot success.

2) The intuition and motivations of LLMs derive from a latent space that the LLM cannot actually access. I cannot get a reliable answer on why the LLM chose the approaches it did; it can only retroactively confabulate. Unlike human developers who can recall off-hand, or at least review associated tickets and meeting notes to jog their memory. The LLM prompter always documenting sufficiently to bridge this LLM provenance gap hits rub #1.

3) Gradually building prompt dependency where one's ability to take over from the LLM declines and one can no longer answer questions or develop at the same velocity themselves.

4) My development costs increasingly being determined by the AI labs and hardware vendors they partner with. Particularly when the former will need to increase prices dramatically over the coming years to break even with even 2025 economics.

> With the latest models if you're clear enough with your requirements you'll usually find it does the right thing on the first try

That's great that this is your experience, but it's not a lot of people's. There are projects where it's just not going to know what to do.

I'm working in a web framework that is a Frankenstein-ing of Laravel and October CMS. It's so easy for the agent to get confused because, even when I tell it this is a different framework, it sees things that look like Laravel or October CMS and suggests solutions that are only for those frameworks. So there's constant made up methods and getting stuck in loops.

The documentation is terrible, you just have to read the code. Which, despite what people say, Cursor is terrible at, because embeddings are not a real way to read a codebase.

In a circuitous way, you can rather successfully have one agent write a specification and another one execute the code changes. Claude code has a planning mode that lets you work with the model to create a robust specification that can then be executed, asking the sort of leading questions for which it already seems to know it could make an incorrect assumption. I say 'agent' but I'm really just talking about separate model contexts, nothing fancy.

Even better, have it write code to describe the right thing then run its code against that, taking yourself out of that loop.

And if you've told it too many times to fix it, tell it someone has a gun to your head, for some reason it almost always gets it right this very next time.

The more explicit/detailed your plan, the more context it uses up, the less accurate and generally functional it is. Don't get me wrong, it's amazing, but on a complex problem with large enough context it will consistently shit the bed.

> The funny part about rapidly changing industries is that, despite the fomo, there's honestly not any reward to keeping up unless you want to be a consultant.

LMAO what???

If the trend line holds you’ll be very, very surprised.

Of course I'm astounded. But being spectacular and being useful are entirely different things.

Because I want correct answers.

> The context window isn't "crippled".

... Proceeds to explain how it's crippled and all the workarounds you have to do to make it less crippled.

> a pretty big context window if you are feeding it the right context.

Yup. There's some magical "right context" that will fix all the problems. What is that right context? No idea, I guess I need to read a yet-another 20 000-word post describing magical incantations that you should or shouldn't do in the context.

The "Opus 4.5 is something else/nex tier/just works" claims in my mind means that I wouldn't need to babysit its every decision, or that it would actually read relevant lines from relevant files etc. Nope. Exact same behaviors as whatever the previous model was.

Oh, and that "200k tokens context window"? It's a lie. The quality quickly degrades as soon as Claude reaches somewhere around 50% of the context window. At 80+% it's nearly indistinguishable from a model from two years ago. (BTW, same for Codex/GPT with it's "1 million token window")

1. It's a workaround for context limitations

2. It's the same workarounds we've been doing forever

3. It's indistinguishable from "clear context and re-feed the entire world of relevant info from scratch" we've had forever, just slightly more automated

That's why I don't understand all the "it's new tier" etc. It's all the same issues with all the same workarounds.

Opus 4.5 was released 24th November.

Looks like you hallucinated the Opus release date

Are you sure you're not an LLM?

FWIW, Gas Town is strange because Steve is strange (in a good way).

It's just the same agent swarm orchestration that most agent frameworks are using, but with quirky marketing. All of that is just based on the SDLC [PM/Architect -> engineer planning group -> engineer -> review -> qa/evaluation] loop most people here should be familiar with. So actually pretty banal, which is probably part of the reason Steve decided to be zany.

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They made the "abstracted away the CRUD app", it's called Salesforce. Hows that going?

I think perhaps for some folks we're looking at their first professional paradigm shift. If you're a bit older, you've seen (smaller versions of) the same thing happening before as e.g. the Internet gained traction, Web2.0, ecommerce, crypto, etc. and have seen your past skillset become useless as now it can be accomplished for only $10/mo/user.... either you pivot and move on somehow, or you become a curmudgeon. Truly, the latter is optional, and at any point when you find yourself doing that you wish to stop and just embrace the new thing, you're still more than welcome to do so. AI is only going to get EASIER to get involved with, not harder.

Agreed, it always seemed a little crazy that you could make wild amounts of money to just write software. I think the music is finally stopping and we'll all have to go back to actually knowing how to do something useful.

> The vast majority of coders in employment barely write anything more complex than basic CRUD apps. These jobs were always going to be automated or abstracted away sooner or later.

My experience has been negative progress in this field. On iOS, UIKit in Interface Builder is an order of magnitude faster to write and to debug, with less weird edge cases, than SwiftUI was last summer. I say last summer because I've been less and less interested in iOS the more I learn about liquid glass, even ignoring the whole "aaaaaaa" factor of "has AI made front end irrelevant anyway?" and "can someone please suggest something the AI really can't do so I can get a job in that?"

On what planet is concentrating an increasingly high amount of the output of this whole industry on a small handful of megacorps “democratising” anything?

Software development was already one of the most democratised professions on earth. With any old dirt cheap used computer, an internet connection, and enough drive and curiosity you could self-train yourself into a role that could quickly become a high paying job. While they certainly helped, you never needed any formal education or expensive qualifications to excel in this field. How is this better?

I used claude code to set up a bunch of basic tools my wife was using in her daily work. Things like custom pomodoro timers, task managers, todo notes.

She used to log into 3 different websites. Now she just opens localhost:3000 and has all of them on the same page. No emails shared with anyone. All data stored locally.

I could have done this earlier but the time commitment with Claude Code now was writing a spec in 5-minutes and pressing approve a few times vs half a day.

I count this as an absolute win. No privacy breaches, no data sharing.

> The artists are calling the AI companies oppressors because they are breaking the artist's stranglehold on the market.

Tt's because these companies profit from all the existing art without compensating the artists. Even worse, they are now putting the very people out of a job who (unwittingly) helped to create these tools in the first place. Not to mention how hurtful it must be for artists seeing their personal style imitated by a machine without their consent.

I totally see how it can empower regular people, but it also empowers the megacorps and bad actors. The jury is still out on whether AI is providing a net positive to society. Until then, let's not ignore the injustice and harm that went into creating these tools and the potential and real dangers that come with it.

When you imagine my position, "I hate these companies for democratizing code/art", then debate that it is called a strawman logical fallacy.

Ascribing the goals of "democratize code/art" onto these companies and their products is called delusion.

I am sure the 3 letter agency directors on these company boards are thrilled you think they left their lifelong careers solely to finally realize their dream to allow you to code and "manifest your artistic ideas".

But people are not creating anything. They are just asking a computer to remix what other people created.

It's incredibly ironic how blatant theft has left otherwise capitalistic people so enthusiastic.

We are not talking about inference.

The prompts and responses are used as training data. Even if your provider allows you to opt out they are still tracking your usage telemetry and using that to gauge performance. If you don’t own the storage and compute then you are training the tools which will be used to oppress you.

Incredibly naive comment.

I understand how these LLMs work.

I find it hard to believe there are people who know these companies stole the entire creative output of humanity and egregiously continually scrape the internet are, for some reason, ignoring the data you voluntarily give them.

> I know that breaks the "training the tools of the oppressor" narrative

"Narrative"? This is just reality. In their own words:

> The awards to Anthropic, Google, OpenAI, and xAI – each with a $200M ceiling – will enable the Department to leverage the technology and talent of U.S. frontier AI companies to develop agentic AI workflows across a variety of mission areas. Establishing these partnerships will broaden DoD use of and experience in frontier AI capabilities and increase the ability of these companies to understand and address critical national security needs with the most advanced AI capabilities U.S. industry has to offer. The adoption of AI is transforming the Department’s ability to support our warfighters and maintain strategic advantage over our adversaries [0]

Is 'warfighting adversaries' some convoluted code for allowing Aurornis to 'see a 1337x in productivity'?

Or perhaps you are a wealthy westerner of a racial and sexual majority and as such have felt little by way of oppression by this tech?

In such a case I would encourage you to develop empathy, or at least sympathy.

> Using an LLM for inference .. does not train the LLM.

In their own words:

> One of the most useful and promising features of AI models is that they can improve over time. We continuously improve our models through research breakthroughs as well as exposure to real-world problems and data. When you share your content with us, it helps our models become more accurate and better at solving your specific problems and it also helps improve their general capabilities and safety. We do not use your content to market our services or create advertising profiles of you—we use it to make our models more helpful. ChatGPT, for instance, improves by further training on the conversations people have with it, unless you opt out.

[0] https://www.ai.mil/latest/news-press/pr-view/article/4242822...

[1] https://help.openai.com/en/articles/5722486-how-your-data-is...

Who is the parent oppressing? Making a comment and companies looking to automate labor are a little bit different. One might disagree that automation is oppressive or whatever goals the major tech CEOs have in developing AIs (surveillance, influencing politics, increasing wealth gap), but certainly commenting that they are oppressive is not the same thing.

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