> For personal tools, I’ve completely shifted my approach. *I don’t even look at the code anymore - I describe what I want to Claude Code, test the result, make some minor tweaks with the AI and if it’s not good enough, I start over with a slightly different initial prompt. The iteration cycle is so fast that it’s often quicker to start over than trying to debug or modify the generated code myself.* This has unlocked a level of creative freedom where I can build small utilities and experiments without the usual friction of implementation details. Want a quick script to reorganize some photos? Done. Need a little web scraper for some project? Easy. The mental overhead of “is this worth building?” has basically disappeared for small tools. I do wish Claude Code had a mode where it could work more autonomously - right now it still requires more hands-on attention than I’d like - but even with that limitation, the productivity gains are wild.
So I suppose the chasm is that actually doing programming is dead, or quickly dying, and if that's the thing you actually enjoyed doing, then tough luck.
This era sucks. The suits have finally won.
(emphasis mine)
I'm personally still in the "smarter autocomplete" phase when it comes to LLMs, as I don't trust the vibe-coded "agents" and the outputs they produce to control my computer. But that aside, this part stood out to me:
> I don’t even look at the code anymore - I describe what I want to Claude Code, test the result, make some minor tweaks with the AI and if it’s not good enough, I start over with a slightly different initial prompt.
Honestly, does the author and anyone else using this workflow find this way of working enjoyable? To me programming is not entirely about the end goal. It's mostly the small bursts of dopamine whenever I solve a particular problem; whenever I refactor code to make it cleaner, simpler, and easier to read; whenever I write a test and see it pass, knowing that I'm building a safety net to safely refactor in the future. And so on.
Yes, the feeling of accomplishment after shipping a useful piece of software, be that a small script or a larger part of a system, is also great. But the small wins along the way are the things that make me want to keep programming.
This way of working where you don't even look at the code, but describe the system specs in prose, go back and forth with an extremely confident but highly error prone tool, manually test the result, and repeat this until you're satisfied... doesn't sound fun or interesting at all.
Up to now, my attempts at doing what the author claims to be possible ends up in a broken piece of code that the agent only makes worse when asked to debug, and finally it wont even compile. There seems to be a threshold of difficulty above which the agent will go bug-runaway. I honestly haven't seen this threshold going up. If anything, it seems to be saturating.
Was this article written by AI? If I argue with it, am I arguing with a real person? Is it written by a corporate shill? Again, if I argue with it, am I talking to a wall?
AI (and before that, corporations) makes skepticism more and more a basic survival skill.
Since this is partly an experience report, it is only as trustworthy as its author, whoever that is. What is this person risking by writing it?
The content seems plausible to me. However, what I’m missing here is:
- how does he test?
- how does he keep himself sharp while his tools are doing so much?
- How does he model the failure modes of this approach, or does he just feel it?
I am not having the same feeling of success as this guy is as I experiment with the same tech. Maybe he’s better than me at using it. Or maybe he’s easily impressed.
At this point, I would not advise kids to go into programming.
Not because I’m certain that the jobs won’t be there, but because I think it’s a credible risk. A career is too important to gamble.
> “We’re entering an era of untrustable code everywhere” - This assumes AI-generated code is inherently less trustworthy than human-written code, which isn’t obviously true.
It's not true if your humans are on controlled substances all the time, it is true if we are talking about real humans.
I've been testing coding agents on real code and I can say without a doubt that they make worse mistakes than humans.
When I use an LLM for (much of anything) I always feel like that scene in the first Iron Man movie where Stark is trying to build stuff with the robot and it almost, but doesn't quite, do what he wants, and then screws something all the way up
The chasm between "practical and useful utilities that have long term viability without a vast knowledge of the underlying mechanisms" and what AI-immersed devs consider "practical" and "useful" grows wider every time I check in.
Snarky and dismissive, sure. But the Wii wasn't a "1 to 1 motion matching" machine no matter how many people insisted it was. It was just "better than anything before had ever been". Which is not the same thing as "good". I'm not holding anything against anyone. The Wii was an incredible console, an LLMs are an incredible technology. I'd just like to read some thoughts on the tech from people who are more aligned with myself in their discernment. If, for nothing else, some variety.
I agree they’re better but author should add add
“Disclaimer: I’m the CEO of a company that sells agents as a service”
at the top of and article promoting said agents.