Building a Mac app with Claude code

The reason you can use these tools so effectively across native, mobile, Go, React etc is that you can apply most of what you learned about software development as a Python engineer in these new areas.

The thing LLMs replace is the need for understanding all of the trivia required for each platform.

I don't know how to write a for loop in Go (without looking it up), but I can write useful Go code now without spinning back up on Go first.

I still need to conceptually understand for loops, and what Go is, and structured programming, and compilers, and build and test scripts, and all kinds of other base level skills that people without an existing background in programming are completely missing.

I see LLMs as an amplifier and accelerant. I've accumulated a huge amount of fuzzy knowledge across my career - with an LLM I can now apply that fuzzy knowledge to concrete problems in a huge array of languages and platforms.

Previously I would stay in my lane: I was fluent in Python, JavaScript and SQL so I used those to solve every problem because I didn't want to take the time to spin up on the trivia for a new language or platform.

Now? I'll happily use things like Go and Bash and AppleScript and jq and ffmpeg and I'm considering picking up a Swift project.

Have you seen non-technical people use LLMs to build things? It's usually a lot slower or a disaster. You don't necessarily need to be technical perhaps in time, but you still need to be precise. Just knowing about HTML to the level we do allows us to embed text into it so the LLM can reason more sharply about it, etc.

Being technical still is an advantage, in my opinion.

> My profession, my passion, all the things I worked so hard to learn, all the time and sacrifices, a machine can now do most of it

Can it? It doesn't have experience, it doesn't have foresight nor hindsight, it cannot plan and it just follows the instructions, regardless if the instructions are good or bad.

But you, as a human, have taste, ideas, creativity and a goal. You can convince others of your good idea, and can take things into account that an LLM can only think about if someone tells it to think about it.

I'm not worried about programming as a profession disappearing, but it is changing, as we're moving up the ladder of abstractions.

When I first got started professionally with development, you could get a career in it without knowing the difference between bits/bytes, and without writing a line of assembly, or any other low-level details. Decades before that, those were base-level requirements for being able to program things, but we've moved up the abstraction ladder.

Now we're getting so far up this ladder, that you don't even need to know a programming language to make programs, if you're good enough at English and good enough at knowing what the program needs to do.

Still, the people who understand memory layout, and assembly, and bits and bobs will always understand more of what's happening underneath than me, and probably be able to do a "better" job than me when that's needed. But it doesn't mean the rest of the layers above that are useless or will even go away.

I’m sure the handicrafts laborers prior to the industrial revolution felt the same way.

However, they also likely had little education, 1-2 of their children probably died of trivial illnesses before the age of 10, and they lived without electricity, indoor plumbing, running water or refrigeration.

Yes, blacksmithing your own tools is romantic (just as hand writing python code), but somehow I’m guessing our ancestors will be better off living at higher layers of abstraction. Nobody will stop them from writing python code themselves, and I’m sure they’ll do it as a fun hobby like blacksmithing is today.

Absolutely feel the same way. I have been writing software professionally for over 20 years and truly love the craft. Now that I am using Claude Code basically 100% of the time my productivity has certainly increased, but I agree there is a hollowness to it - where before the process felt like art it now feels like industrialized mass manufacturing. I’m hoping that I can rediscover some of what has kept me so fascinated with software in this new reality, because quite a bit of the joy has indeed been stripped away for me.

Yeah there are a lot of things in programming that I don’t enjoy, that I can now avoid doing, like learning how to do the same technical thing in a different language/framework.

But the stuff I enjoy doing is something I don’t delegate to the agent. I just wonder how long the stuff I enjoy can be delegated to an agent who will do it cheaper and faster.

I think it’s yet another layer of abstraction on top of complex ideas. There will always be room for people working on the infrastructure, tools, maintenance, and operations side of things. The biggest danger is if you stop learning because you trust AI to just do it.

I’ve been (carefully) using AI on some AWS infrastructure stuff which I don’t know about. Whenever it proposes something, I research and learn what it’s actually trying to do. I’ve been learning quickly with this approach because it helps point me in the right direction, so I know what to search for. Of course, this includes reviews and discussions with my colleagues who know more, and I frequently completely rewrite what AI has done if it’s getting too complex and hard to understand.

The important thing is not allowing AI to abstract away your thought process. It can help, but on my terms

Feeling the same, I just started a dialectic blog, with ChatGPT arguing with itself based on my prompt. It can have some biting words. I also have been using Suno AI to make a song with each post; while not perfect, it certainly allows for totally non-musical people like me to have something produced that can be listened to.

One post that fits with this feeling is https://silicon-dialectic.jostylr.com/2025/07/02/impostor-sy... The techno-apocalyptic lullaby at the end that the AIs came up with is kind of chilling.

> Lastly, I use it to ask questions about my codebase, refactor code, let it document my code, even make meaningful commits.

I've found that CC writes really good commits; I added info about Conventional Commits [1] to the CLAUDE.md file with a few examples.

[1]: https://www.conventionalcommits.org/en/v1.0.0/#summary

Will CC automatically backup these personal configs you are talking about, say .zshrc, before making changes?

Yeah, I've built a small iOS app and wordpress plugin for myself and love them. I'm curious if more people will do this in the near future, should we all be sharing our code on github?

Right: tools like Claude Code amplify existing skills and expertise, they don't replace it.

And at the bottom it’s revealed that this costs $200/month. I have trouble convincing myself to give Autodesk $50/month and I need that software for my primary hobby.

And none of these AI companies are profitable. Imagine how much it will cost or how much it will be enshittified when the investors come looking for their returns.

If everyone whose code illegally trained these models won a copyright lawsuit against Claude it would suddenly not be so good at writing swift code.

Do we really want to bet on Disney losing their AI lawsuit?

Honestly I realize my comment is not adding much to the discussion but the AI fatigue is real. At this point I think HN and other tech forums would do well to ban the topic for posts like this.

Imagine if we were upvoting stories about how people are getting lots of coding done easier with Google and StackOverflow. It would be rightfully ridiculed as vapid content. Ultimately that’s what this blog post is. I really don’t care to hear how yet another dingus “programmer” is using AI to do their hobby/job for them.

I write CLI tools with LLMs all the time. I even have a custom Claude Project that teaches the LLM to use inline script dependencies with uv so I can "uv run script.py" without first having to install anything else: https://simonwillison.net/2024/Dec/19/one-shot-python-tools/

I have a collection of tools I've built in this way here: https://tools.simonwillison.net/python/

Maybe you should ask the LLM to write concise documentation for the functions that it generates (or ask it afterwards). Then use that documentation in the context-window instead of the actual, more lengthy code. Compartmentalize your code into modules/functions with a clearly defined boundary (api).