Isn't it concerning that the hype and billions in investment is mostly steering towards finding that the only paying customer base are ergonomics tasks for other developers? Not exactly looking like the world changer right now
I've even finally found the time to tackle some hobby projects that have been sitting on my back burner for literally years. Claude just tears through problems at breakneck speed. And you know what? It's actually fun again! I forgot how enjoyable coding could be when you're not getting bogged down in the tedious stuff.
Sure, maybe the big revolutionary applications haven't materialized yet, but when a tool can take something that would have taken me days and knock it out in an afternoon? That doesn't feel like just "making things more comfortable" - that feels pretty transformative to me, at least for how I work.
I most recently asked for a privilege-separated JMAP client daemon (dns, fetcher, writer) using pledge() and unveil() that would write to my Maildir, my khal dir and contacts whenever it had connectivity and otherwise behave like a sane network client.
I got 800 lines of garbage C. Structs were repeated all over the place, the config file was #defined four times, each with a different name and path.
Every step should only affect a handful of classes or functions, that you can still keep in your head and easily verify. Basically, same thing as if you were doing it by hand, but at a higher abstraction level, so faster and less mentally tiring.
Shameless plug: I am working on a new cross-platform IDE designed for just this kind of workflow. It has basic C/C++ support already: https://sysprogs.com/CodeVROOM/?features=why
This isn't the context of this particular thread through. Its this
"Claude just tears through problems at breakneck speed."
But if there are things worth hesitating and weighing, LLM will fly past them at cruising speed.
There are plenty of problems of both kinds.
I'm an experienced dev (this year is my 10 year anniversary of 'officially' being in the industry). I've been using Claude Code over these last two weeks. It's like a magical code generator tool e.g. protoc; if you can describe the rote and boring "do this tedious x->y translation", then it can probably bang that out with tests in a couple minutes, making it easy for you to focus on the logic. It's not that Claude Code is doing the "programming", it's more like Claude is doing the typing (and it types REALLY fast). Literally imagine if you could type as fast as you could think, like just saying "oh I'll need functions covering x/y/z behaviors and cases, similar to the other functions already present but tailored like <way>." All you had to do was type that sentence and it wrote basically what you would have written, but instantly.
This is exactly how vibe coding has been feeling to me lately, I do read all the code while it writes it, and I command the AI to write/edit/fix the code, so its like faster programming but we're still on the director seat
also focusing on logic, and the problems at hand, and not syntax, API, or function signatures, allows one to build at much faster speed and focusing on architecture and actual UX and not just code
Strange thing to respond to people having great success with it. You clearly want it to fail, but why?
Not to mention the ethical / copyright / misbehaving scrapers.
These days, with explision of options and alternatives and visible augmentation of their skills (tasks orchestration, mcps, etc) I have temporary reverse of that feeling as I struggle to settle on one approach/tool/editor, and always in half-baked experiementation stage with these tools, that also evolve quicker that I can try them out.
yes I've been addicted to vibe coding too but i don't share the sentiment here.
This only holds true as long as you don't run into a bug that llm throws up its hands. Now you have no option but to read and understand code.
Also, I get caught up in multiple errors that will never go away and, since I'm stepping out of my wheelhouse with libraries or packages I'm completely unfamiliar with, I'm completely helpless but to diagnose what went wrong myself and improve upon my code prompting skills.
Don't get me wrong. AI makes possible many things for me. However, I think professional coders probably accomplish much more.
Actually I forgot there's a second one he read all the way through, for which he defined the initial concept and early plot, but then the rest of the plot and the writing were all done by GPT-4.5.
The code is kind of basic, and each chapter is written without the full text of prior chapters, but the output isn't bad.
https://gist.github.com/rahimnathwani/41e5bc475163cd5ea43822...
I find the quality rapidly degrades as soon as I run out of context to fit the whole text of the novel. Even summarizing the chapters doesn’t work well.
This would be fine for a cheap model, but GPT 4.5 was not cheap!
I would have liked to have fewer, longer chapters, but my (few) experiments at getting it to output more tokens didn't have much impact.
I'm firmly convinced that being able to troubleshoot code, even code generated by LLMs, and to write guidelines and tests to make sure it's functioning, is a skill of a shrinking pool
For smaller stuff, great. Everyone's the same. The second your application starts gaining responsibility and complexity, you're going to need to be able to demonstrate reproducibility and reliability of your application to stakeholders.
Like, your job increasingly will be creating interface checkpoints in the code, and then having the model generate each step of the pipeline. That's great, but you have understand and validate what it wrote, AND have a rich set of very comprehensive tests to be able to iterate quickly.
And as mentioned, on top of that, large swaths of the field of new people have their brains completely rotted by these tools. (certainly not all new/young people, but i've seen some real rough shit)
If anything, I see a weird gap opening up
- people who dont adopt these tools start falling out of the industry - they're too slow
- people who adopt these tools too early stop getting hired - they're too risky
- people who have experience in industry/troubleshooting/etc, who adopt these tools, become modern day cobol programmers - they're charging $700 an hour
the real question to me is this: does the amount of people taken out of the pool by being slow or risky due to these tools, outpace the reduction in jobs caused by these tools?
Well, today only scientists can make stone tools.
It’s like if I was hiring a mathematician. I’d expect them to use a calculator or CAS package but I’d also expect them to be able to do everything by hand. I wouldn’t ever waste their time by making them do that, of course.
I was trying to say that dropping old technologies isn't always bad.
> It’s like if I was hiring a mathematician.
Do you expect candidate to memorize all theorems up to date. Usually people forgetting things they don't actively use. But they are able to refresh their knowledge if needed. I've learned quite a lot, but no, I don't remember even key theorems from partial differential equations (used them in my diploma). I can refresh and relearn quickly, I'm sure.
Using LLM without understanding disqualifies the candidate, even monkey can do it. But if he deeply understands the subject and uses LLM for like handbook for minor details.. that's different.
Completely missing the point. I expect them to have enough knowledge to briefly study the theorems and understand how to apply them. I’m not trying to quiz people, I’m trying to get things done - and done well.
And for the stuff I’m doing, it’s required that any engineer understand what they’re building and why.
> Using LLM without understanding disqualifies the candidate, even monkey can do it. But if he deeply understands the subject and uses LLM for like handbook for minor details.. that's different
The problem is that they don’t understand the subject and overly rely on LLMs. Completely falling apart during in person interviews. Surface knowledge of everything and no depth.
Using LLMs isn’t inherently bad but I’ve seen severe side effects from students and junior engineers who over rely on it.
A great developer + an AI = productive.
A shitty developer + an AI = still shit.
AI does not make all developers the same. And it doesn't make all marketers the same.
First, the breathless nerds. Then, the greater swath of nerds (where we are). And this is when people start to get excited in various degrees while others say stuff like "no one will ever want to fuss with dialup and a second phone line" or "no one will ever put real info or use credit cards online".
Then a couple years later, grandma is calling you over to fix her Netzero and away we go...
My partner is not a coder but uses copilot a lot.
Compare this to blockchain, which never did anything useful for anyone after 20 years.
- ransomware payments
- money transfers for online and telephone scams
- buying illegal drugs online
- funding North Korea’s government
But I was talking within the same context as the thread, which is business.
(I apologize for being a smart aleck.)
- avoiding monetary tyranny in not-so-well developed authoritarian countries
maybe not so important for you, but for some people it is simply a matter of acquiring food and medicine, because a working member of their family has just one way to support his relatives by sending them money from abroad, and it is bitcoin