Enlightened dumbness 🧘

It regurgitates old code, it cannot come up with new stuff.

The trick is, most of what you write is basically old code in new wrapping. In most projects, I’d say the new and novel part is maybe 10% of the code. The rest is things like setting up db models, connecting them to base logic, set up views, api endpoints, decoding the message on the ui part, displaying it to user, handling input back, threading things so UI doesn’t hang, error handling, input data verification, basic unit tests, set up settings, support reading them from a file or env vars, making UI look not horrible, add translatable text, and so on and on and on. All that has been written in some variation a million times before. All can be written (and verified) by a half-asleep competent coder.

The actual new interesting part is gonna be a small small percentage of the total code.

I guess I’m one of the idiots then, but what do I know. I’ve only been coding since the 90s

That’s kinda wrong though. I’ve seen llm’s write pretty good code, in some cases even doing something clever I hadn’t thought of.

You should treat it as any junior though, and read the code changes and give feedback if needed.

I’ve used Claude code to fix some bugs and add some new features to some of my old, small programs and websites. Not things I can’t do myself, but things I can’t be arsed to sit down and actually do.

It’s actually gone really well, with clean and solid code. easily readable, correct, with error handling and even comments explaining things. It even took a gui stream processing program I had and wrote a server / webapp with the same functionality, and was able to extend it with a few new features I’ve been thinking to add.

These are not complex things, but a few of them were 20+ files big, and it manage to not only navigate the code, but understand it well enough to add features with the changes touching multiple files (model, logic, view layer for example, or refactor a too big class and update all references to use the new classes).

So it’s absolutely useful and capable of writing good code.

I’ve found it useful to write test units once you’we written one or two, write specific functions and small scripts. For example some time ago I needed a script that found a machine’s public ip, then post that to an mqtt topic along with timestamp, with config abstracted out in a file.

Now there’s nothing difficult with this, but just looking up what libraries to use and their syntax takes some time, along with actually writing the code. Also, since it’s so straight forward, it’s pretty boring. ChatGPT wrote it in under two minutes, working perfectly on first try.

It’s also been helpful with bash scripts, powershell scripts and ansible playbooks. Things I don’t really remember the syntax on between use, and which are a bit arcane / exotic. It’s just a nice helper to have for the boring and simple things that still need to be done.

Just can’t waste time on trying to make it do anything complicated because that never goes well.

Yeah, that’s a waste of time. However, it can knock out simple code you can easily write yourself, but is boring to write and take time out of working on the real problems.

When you cosplay as judge dredd, it’s exactly how it works

We don’t even know who killed the guy yet

It doesn’t matter at this point, the current narrative has already picked up too much steam

This case also highlights how the use of artificial intelligence (AI) can potentially contribute to the development of preventable adverse health outcomes. Based on the timeline of this case, it appears that the patient either consulted ChatGPT 3.5 or 4.0 when considering how he might remove chloride from this diet. Unfortunately, we do not have access to his ChatGPT conversation log and we will never be able to know with certainty what exactly the output he received was, since individual responses are unique and build from previous inputs.

However, when we asked ChatGPT 3.5 what chloride can be replaced with, we also produced a response that included bromide. Though the reply stated that context matters, it did not provide a specific health warning, nor did it inquire about why we wanted to know, as we presume a medical professional would do.

https://www.acpjournals.org/doi/10.7326/aimcc.2024.1260

Management: “But the coin miners are the only ones maintaining the server, if it wasn’t for that it would have died long time ago”

https://www.computerworld.com/article/3990472/china-takes-edge-computing-to-orbit-with-first-space-based-processing-network.html

So someone thinks it’s not entirely stupid

Yes, which has improved some tasks measurably. ~20% improvement on programming tasks, as a practical example. It has also improved tool use and agentic tasks, allowing the llm to plan ahead and adjust it’s initial approach based on later parts.

Having the llm talk through the tasks allows it to improve or fix bad decisions taken early based on new realizations on later stages. Sort of like when a human thinks through how to do something.

We’ll still have models like deepseek, and (hopefully) discount used server hardware

I’ve seen some saying that “lifetime” refers to product lifetime, which is not expected to be more than X years. So yeah, slimes gonna slime

“South American shot after opening fire on police searching for illegal immigrant gang members”

FTFY

Well, it wasn’t a comment on the quality of the model, just that the context limitation has already been largely overcome by one company, and others will probably follow (and improve on it further) over time. Especially as “AI Coding” gets more marketable.

That said, was this the new gemini 2.5 pro you tried, or the old one? I haven’t tried the new model myself, but I’ve heard good things about it.

Yeah, I’ve been seeing the same. Purely economically it doesn’t make sense with junior developers any more. AI is faster, cheaper and usually writes better code too.

The problem is that you need junior developers working and getting experience, otherwise you won’t get senior developers. I really wonder how development as a profession will be in 10 years

Working on a big codebase, I don’t even get the idea to ask an AI, you just can’t feed enough context to the AI that it’s really able to generate meaningful code…

That’s not a hard limit, for example google’s models can handle 2-million-token context window.

https://ai.google.dev/gemini-api/docs/long-context

AI isn’t ready to replace programmers, engineers or IT admins yet.

On the other hand… it’s been about 2.5 years since chatgpt came out, and it’s gone from you being lucky it could write a few python lines without errors to being able to one shot a mobile phone level complexity game, even with self hosted models.

Who knows where it’ll be in a few years