I’m nearly the same. Though I do find I’m still writing code, just not the code that’s ending up in the commit. I’ll write pseudo code, example code, rough function signatures then Claude writes the rest.
IMHO it's very misleading to claim that some LLM wrote all the code, if it's just a compression of thousands of peoples' codes that lead to this very LLM even having something to output.
They didn’t have to, they decided that it’ll be more stable to revert them for the holidays, so that they won’t be in the office fixing issues on Christmas.
honestly i've been becoming too lazy, I know exactly what I want and AI is at a point where it can turn that into code. It's good enough to a point where I start to design code around AI where it's easier for AI to understand (less DRY, less abtractions, closer to C)
"If the AI builds the house, the human must become the Architect who understands why the house exists."
In Japanese traditional carpentry (Miya-daiku), the master doesn't just cut wood. He reads the "heart of the tree" and decides the orientation based on the environment.
The author just proved that "cutting wood" (coding) is now automated. This is not the end of engineers, but the beginning of the "Age of Architects."
We must stop competing on syntax speed and start competing on Vision and Context.
Claude Code user¹ says Claude Code wrote continuously incorrect code for the last hour.
I asked it to write Python code to retrieve a list of Kanbord boards using the official API. I gave it a link to the API docs. First, it wrote a wrong JSONRPC call. Then it invented a Python API call that does not exist. In a new try, I I mentioned that there is an official Python package that it could use (which is prominently described in the API docs). Claude proceeded to search the web and then used the wrong API call. Only after prompting it again, it used the correct API call - but still used an inelegant approach.
I still find some value in using Claude Code but I'm much happier writing code myself and rather teach kids and colleagues how to do stuff correctly than a machine.
I wonder how.
Everything I let claude code majorly write, whether Go, F#, C or Python, I end up eventually at a point where I systematically rip it apart and start writing it over.
In my study days, we talked of “spikes”. Software or components which functionally addressed some need, but often was badly written and architected.
That’s what I think most resembles claude code output.
And I ask the llm to write todo-lists, break tasks into phases, maintain both larger docs on individual features and a highly condensed overview doc.
I also have written claude code like tools myself, run local LLMs and so on.
That is to say, I may still be “doing it wrong”, but I’m not entirely clueless .
The only place where claude code has nearly done the whole thing and largely left me with workable code was some react front-end work I did (and no, it wasn’t great either, just fair enough).
Used Claude Code until September then Codex exclusively.
All my code has been AI generated, nothing by hand.
I review the code and if I don’t like something- I let it know how it should be changed.
Used to be a lot of back and forth in August, but these days GPT 5.2 Codex one shots everything so far. It worked for 40 hours for me one time to get a big thing in place and I’m happy with the code.
For bigger things start with a plan and go back and forth on different pieces, have it write it to an md file as you talk it through, feed it anything you can - user stories, test cases, design, whiteboards, backs of napkins and in the end it just writes the code for you.
Works great, can’t fathom going back to writing everything by hand.
The guy who write the typescript/bun cli and probably maintains that?
It would be helpful if people also included what kind of code they are writing (language, domain, module, purpose, etc)
The hallucinations are still there, sometimes worse than others but manageable. This is mostly when I have to do some database management style work. This is off the beaten path and hallucinations are crazy.
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[ 2.7 ms ] story [ 48.4 ms ] threadhttps://x.com/trq212/status/2001848726395269619
You can read more about it at https://steipete.me/posts/2025/signature-flicker
And it's probably a bad thing? Not sure yet.
What's with the ad here though?
In Japanese traditional carpentry (Miya-daiku), the master doesn't just cut wood. He reads the "heart of the tree" and decides the orientation based on the environment.
The author just proved that "cutting wood" (coding) is now automated. This is not the end of engineers, but the beginning of the "Age of Architects."
We must stop competing on syntax speed and start competing on Vision and Context.
I wonder how much of these 40k lines added/38k lines removed were just replacing the complete code of a previous PR created by Claude Code.
I'm happy that it's working for them (whatever that means), but shouldn't we see an exponential improvement in Claude Code in this case?
I asked it to write Python code to retrieve a list of Kanbord boards using the official API. I gave it a link to the API docs. First, it wrote a wrong JSONRPC call. Then it invented a Python API call that does not exist. In a new try, I I mentioned that there is an official Python package that it could use (which is prominently described in the API docs). Claude proceeded to search the web and then used the wrong API call. Only after prompting it again, it used the correct API call - but still used an inelegant approach.
I still find some value in using Claude Code but I'm much happier writing code myself and rather teach kids and colleagues how to do stuff correctly than a machine.
¹) me
In my study days, we talked of “spikes”. Software or components which functionally addressed some need, but often was badly written and architected.
That’s what I think most resembles claude code output.
And I ask the llm to write todo-lists, break tasks into phases, maintain both larger docs on individual features and a highly condensed overview doc. I also have written claude code like tools myself, run local LLMs and so on. That is to say, I may still be “doing it wrong”, but I’m not entirely clueless .
The only place where claude code has nearly done the whole thing and largely left me with workable code was some react front-end work I did (and no, it wasn’t great either, just fair enough).
Used Claude Code until September then Codex exclusively.
All my code has been AI generated, nothing by hand.
I review the code and if I don’t like something- I let it know how it should be changed.
Used to be a lot of back and forth in August, but these days GPT 5.2 Codex one shots everything so far. It worked for 40 hours for me one time to get a big thing in place and I’m happy with the code.
For bigger things start with a plan and go back and forth on different pieces, have it write it to an md file as you talk it through, feed it anything you can - user stories, test cases, design, whiteboards, backs of napkins and in the end it just writes the code for you.
Works great, can’t fathom going back to writing everything by hand.
It would be helpful if people also included what kind of code they are writing (language, domain, module, purpose, etc)
The hallucinations are still there, sometimes worse than others but manageable. This is mostly when I have to do some database management style work. This is off the beaten path and hallucinations are crazy.