I've got 10+ years of coding experience, I am an AI advocate, but not vibe coding. AI is a great tool to help with the boring bits, using it to initialize files, help figure out various approaches, as a first pass code reviewer, helping with configuring, those things all work well.
But full-on replacing coders? It's not there yet. Will require an order of magnitude more improvement.
If you spend a couple of years with an LLM really watching and understanding what it’s doing and learning from mistakes, then you can get up the ladder very quickly.
A "basic" understanding in critical domains is extremely dangerous and an LLM will often give you a false sense of security that things are going fine while overlooking potential massive security issues.
All I could think was, "good luck" and I certainly hope their app never processes anything important...
I don't feel like most providers keep a model for more than 2 years. GPT-4o got deprecated in 1.5 years. Are we expecting coding models to stay stable for longer time horizons?
Then again the problem is that the public has learned nothing from the theranos and WeWorks and even more of a problem is that the vc funding works out for most of these hype trains even if they never develop a real business.
The incentives are fucked up. I’d not blame tech enthusiasts for being too enthusiastic
Might as well talk about how AI will invent sentient lizards which will replace our computers with chocolate cake.
Thinking usually happens inside your head.
What is your point?
If you’re trying to say that they should have kept their opinion to themselves, why don’t you do the same?
Edit: tone down the snark
Holy Spiderman what is your point? That if someone says something dumb I can never challenge them nor ask them to substantiate/commit?
> tone down the snark
It's amazing to me that the neutral observation "thinking happens in your head" is snarky. Have you ever heard the phrase "tone police"?
If the person who is liable for the system behavior cannot read/write code (as “all coders have been replaced”), does Anthropic et al become responsible for damages to end users for systems its tools/models build? I assume not.
How do you reconcile this? We have tools that help engineers design and build bridges, but I still wouldn’t want to drive on an “autonomously-generated bridge may contain errors. Use at own risk” because all human structural engineering experts have been replaced.
After asking this question many times in similar threads, I’ve received no substantial response except that “something” will probably resolve this, maybe AI will figure it out
The bridge scenario is simply addressed: Licensed Engineer has to approve designs. Permitting review process has to review designs. Not sure it matters who drafted them initially.
If the only point being made by “all coders are replaced” is that humans aren’t manually typing the code from their keyboard anymore, I don’t think there’s much interesting to argue there, typing the code was never the hard part.
I am using them in projects with >100kloc, this is not my experience.
at the moment, I am babysitting for any kloc, but I am sure they will get better and better.
I am sure there are ways to get around this sort of wall, but I do think it's currently a thing.
I built a skribbl.io clone to use at work. We like to play eod on Friday as a happy hour and when we would play skribbl.io we would try to get screencaps of the stupid images we were drawing but sometimes we would forget. So I said I'd use claude to build our own skribbl.io that would save the images.
I was definitely surprised that claude threaded the needle on the task pretty easily, pretty much single shot. Then I continued adding features until I had near parity. Then I added the replay feature. After all that I looked at the codebase... pretty much a single big file. It worked though, so we played it for the time being.
I wanted to fix some bugs and add more features, so I checked out a branch and had an agent refactor first. I'd have a couple context/sessions open and I'd one just review, the other refactored, and sometimes I'd throw a third context/session in there that would just write and run tests.
The LLM will build things poorly if you let it, but it's easy to prompt it another way and even if you fail that and back yourself into a corner, it's easy to get the agents to refactor.
It's just like writing tests, the llms are great at writing shitty useless tests, but you can be specific with your prompt and in addition use another agent/context/session to review and find shitty tests and tell you why they're shitty or look for missing tests, basically keep doing a review, then feed the review into the agent writing the tests.
You also need a reasonably modular architecture which isn't incredibly interdependent, because that's hard to reason about, even for humans.
You also need lots and lots (and LOTS) of unit tests to prevent regressions.
> Somehow 90% of these posts don't actually link to the amazing projects that their author is supposedly building with AI.
You are in the 90%.
When you create a blog post about it though, I do agree that showing the projects will greatly increase the value of your claims.
That said, I do catch it doing some of the stuff the OP mentioned— particularly leaving “backwards compatibility” stuff in place. But really, all of the stuff he mentions, I’ve experienced if I’ve given it an overly broad mandate.
Surely it depends on the design. If you have 10 10kloc modular modules with good abstractions, and then a 10k shell gluing them together, you could build much bigger things, no?
Then let me introduce you to a useful concept:
I've learned with LLM coded apps to break stuff into very small manageable chunks so they can work on the tiny piece and not get screwed by big context.
For the most part, this actually produces a cleaner codebase.
SHOW ME THE MONEY!!!
Maybe they don't feel like sharing yet another half working Javascript Sudoku Solver or yet another half working AI tool no one will ever use?
Probably they feel amazed about what they accomplished but they feel the public won't feel the same.
That's the whole point of sharing with the rest of us. If they write for themselves, a private journal to track their progress, then there is no need to share what is actually been built. If they do though make grand claims to everybody then it would be more helpful for people who do read the piece to actually be able to see what has been produced. Maybe it's wonderful for the author but it's not the level of quality required for readers.
GPT-5.2 fixed my hanging WiFi driver: https://gist.github.com/lostmsu/a0cdd213676223fc7669726b3a24...
It's a magical moment when someone is able to AI code a solution to a problem that they couldn't fix on their own before.
It doesn't matter whether there are other people who could have fixed this without AI tools, what matters is they were able to get it fixed, and they didn't have to just accept it was broken until someone else fixed it.
Cue the folks saying "well you could DIE!!!" Not if I don't fix brakes, etc ...
https://apps.apple.com/us/app/snortfolio/id6755617457
30kloc client and server combined. I built this as an experiment in building an app without reading any of the code. Even ops is done by claude code. It has some minor bugs but I’ve been using it for months and it gets the job done. It would not have existed at all if I had to write it by hand.
Nobody is actually using AI for anything useful or THEY WOULDNT BE TALKING ABOUT IT. They’d be disrupting everything and making billions of dollars.
Instead this whole AI grift reads like “how to be a millionaire in 10 days” grifts by people that aren’t, in fact, millionaires.
> This has truly freed up my productivity, letting me pursue so many ideas I couldn’t move forward on before
If you're writing in a blog post that AI has changed your life and let you build so many amazing projects, you should link to the projects. Somehow 90% of these posts don't actually link to the amazing projects that their author is supposedly building with AI.