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).
In two decades I have never met an engineer who joined a project and didn’t at some point suggest starting over.
The world runs on buggy, hack filled, good enough code. The idea LLMs are failing when that’s what they produce is wrong in my opinion.
The other way is to spend a fair bit of time building out a design and ask it to implement it while verifying what it is producing then and there instead of reviewing reams of slop later on. AI still produced 100% - just that it is not as glamorous or as marketing friendly of a sound bite. After all which product manager wants to understand refactoring or TDD or SOLID or design principles etc?
Does it work? How fast can we get it? How much does it cost to use it?
Unless you work in an industry with standards, like medical or automotive. Setting ISO compliance aside, you could also work for a company which values long term maintainability, uptime etc. I'm glad I do. Not everyone is stuck writing disposable web apps.
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.
These tools are somewhat slow, so you need to work on several things at once, so multitasking is vital.
When i get defects from the QA team, I spawn several agents with several worktrees that do each of the tickets- then i review the code, test it out and leave my notes.
Closing the loop is also vital, if agents can see their work, logs, test results it helps them to be more autonomous
With each new drop, they become more and more powerful, so it’s easier and easier to jump in.
Go look at Peter Steinberger’s stuff at https://steipete.me/posts/just-talk-to-it it’s a great way to get going.
Follow him and https://jeffreyemanuel.com/ on X to keep up to date on the latest and most advanced techniques to work with AI. Learned a lot from them.
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 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.
AI optimizes for "Accuracy" (minimizing error), but it cannot optimize for "Taste" because Taste is not a variable in its loss function.
As code becomes abundant and cheap, "Aesthetics" and "Gestalt" will become the only scarcity left. The Architect's job is not to build, but to choose what is beautiful.
The AI is better at that too. Truth is, nothing matters except the maximal delusion. Only humans can generate that. Only humans can make a goal they find meaningful.
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.
It actually didn’t too bad after some back and forth and this too was off the beaten path (hard to find a stack overflow/blog post/etc putting it all together)
Totally worth the $20/mo!!
You can read more about it at https://steipete.me/posts/2025/signature-flicker
Still, I use LLM assisted coding fairly frequently, but this is a nagging feeling I have.
A: The comment is bad for business.
And it's probably a bad thing? Not sure yet.
If it uses anything I don't know, some tech I hadn't grasped yet, I do a markdown conversation summary and make sure to include technical solutions overview. I then shove that into note software for later and, at a convenient time, use that in study mode to make sure I understand implications of whatever AI chose. I'm mostly a backend developer and this has been a great html+css primer for me.
You are treating the AI not as a tool, but as a "Material" (like wood or stone).
A master carpenter works with the grain of the wood, not against it. You are adapting your architectural style to the grain of the AI model to get the best result.
That is exactly what an Architect should do. Don't force the old rules (DRY) on a new material.
What's with the ad here though?
I refuse to believe real AI conversations of any value are happening on X.
Hi I'm Boris and I work on Claude Code. I am going to start being more active here on X, since there are a lot of AI and coding related convos happening here.
In pragmatic terms though, innovation like that doesn't happen often. LLMs could do the things that most developers do.
That said, I don't agree with the notion that LLMs are simply generating content based on their training data. That ignores all the work of the AI devs who build systems to take the training data and make something that creates new (but not innovative) things from it.
