still, this "ai code tools will deprecate real programming" bullshit will one day be laughed at just like how most of us laugh at shitcoin maniacs
it just takes a lot of people way too long to learn
I spend much of the day reading and thinking and only a small portion actually writing code, because when I'm typing, I usually have a hypothetical solution that is 99% correct and I'm just bringing it to life. Or I'm refactoring. You can interrupt me at any time and I could give you the complete recipe of what I'm doing.
Which is why I don't use LLMs, because it's actually twice the work for me. Typing out the specs, then verifying and editing the given result, while I could type the code in the first place. And they suck at prototyping. Sometimes I may want to leave something in the bare state where only one incantation works, because I'm not sure of the design yet, and have a TODO comment, but they go to generate a more complicated code. Which is a pain to refactor later.
For example, yesterday I needed a parser for a mini-language. I wrote a grammar — actually not even the formal grammar, just some examples — and what I wanted the AST to look like. I said “write the tokenizer”, and it did. I told it to tweak a few things and write tests. It did. I told it to “write a recursive descent parser”, and it did. Add tests and do some tweaks, done.
The whole thing works and it took less than an hour.
So yeah, I had to know I needed a parser, but at that point I could pretty much hand off the details. (Which I still checked over, so I’m not even in full vibe mode, guess.)
It isn’t exactly breaking new ground or doing anything you couldn’t find with a quick google search.
If you have a parser generator tool that can go from zero to parser based on a few examples rather than a grammar, I’d love to hear about it.
That's the part where the LLM would be useful. Turn the examples into a grammar, verify the grammar, and use a parser generator for the rest.
You know the code does what it should and you get there in minutes.
there's the snake in the grass - you're asking the LLM to write tests after the code is generated, so naturally, it will write passing tests - including tests which enforce buggy behavior
if not now, then you're lucky; watch out for next time.
Generally, you wouldn't type out the spec either, either you provide an existing spec to the model (in form of white board notes, meeting notes, etc.) or you iterate conversationally until you arrive at an initial implementation plan.
It's a different way of working for sure, and it has distinct draw backs and requires different mental modes depending if you're doing green field, demo/prototype, existing large app feature development etc. but it's been a massive productivity enhancement, especially when tackling multiple projects in quick succession.
When you're making a game, it's really expensive to try out different ideas, like a few different implementations of a mechanic. It could be hours of work to make a change. You tend to have to do a lot of thinking to tweak a mechanic in a fundamental way just to see what it feels like, knowing that you're probably going to throw it away.
LLMs are really good at this. Make a git branch, ask Claude Code to tweak the physics so that it does X, see what it feels like. Rollback the change or continue tweaking.
Same with branching the UI to see what a different idea would feel like. Simple changes to explain could result in hours of refactoring UI code (chore work) just to see if you like the result. Or just ask the LLM to do it, see what it feels like, roll it back.
How do you verify that Claude did what you wanted?
Maybe more importantly, how do you verify that Claude didn't make a change that you didn't want?
Trying to verify the code changes just by testing the running project seems incredibly careless
There's a responsible enlightened self enriching way to use AI tools, and there's "vibe coding".
I don't believe anyone will actually use AI this way long-term
Even if we start out this way, eventually people will trust it enough that they get complacent and mistakes will start to slip through
Besides which, this doesn't actually sound faster than just writing the code yourself
You simply can't learn nearly as fast with vi or Emacs or VSCode, and they can't explain unknown code and APIs and algorithms and bug fixes to you, suggest best practices, review code, write documentation for existing code, check and align code with updated documentation, or automatically update existing documentation and comments to reflect the actual code.
Right now I'm using Cursor to refactor and overhaul a huge complex multi-repo codebase of Python, TypeScript, Bash, SQL, JSON, YAML, Markdown, and ML models, from multiple repos with Google Cloud Build to a monorepo with GitHub actions, and it's no cake walk, a huge amount of work, I'm learning and applying a whole lot of new stuff, meticulously documenting every part of the system, making it rock solid, DRY, with extensive logging and error handling, and there's no way I would have been able to do 5% of this work in the same amount of time without using AI. You don't HAVE to be lazy, instead you can work as hard as you've ever worked without AI and get a hell of a lot more done while learning new things, if you so choose to. It's all up to you.
If you insist on going into it refusing to use it as a learning tool, and don't want to work hard, then you be you, and I'm going to have a huge advantage over you or any "vibe coder".
You asked "How do you verify that Claude did what you wanted?" and I told you. Just because you're too lazy and incurious to drink the water I led you to doesn't mean I or anyone else can't.
It's a shame that we'll invest so much money and compute into this, and continue to ignore all the ergonomics research that could help.
Everything is shifting so fast right now that it hardly matters anyways. Whatever I spend time learning will be outdated in a few years (when things are predicted to get good). It does matter if you're trying to sell AI products, though. Then you gotta convince people they're missing out, their livelihood is at stake if they don't use your new thing now now now.