Cursor, Windsurf, Roo Code / Cline, they're fine but nothing feels as thorough and useful to me as Claude Code.

The Codex CLI from OpenAI is not bad either, there's just something satisfying about the LLM straight up using the CLI

The more interesting question is whether this is true across the economy as a whole. In my view the answer is clearly no. Are we already operating at the limit of more software to add value at the margin? No.

So though any particular existing business might stop hiring or even cut staff, it won't matter if more businesses are created to do yet more things in the world with software. We might even end up in a place where across the economy, more dev jobs exist as a result of more people doing more with software in a kind of snowball effect.

More conservatively, though, you'd at least expect us to just reach equilibrium with current jobs if indeed there is new demand for software to soak up.

I know the context window part and Cursor RAG-ing it, but isn't IDE integration a a true force multiplier?

Or does Claude Code do something similar with "send to chat" / smart (Cursor's TAB feature) autocomplete etc.?

I fired it up but it seemed like just Claude in terminal with a lot more manual copy-pasting expected?

I tried all the usual suspects in AI-assisted programming, and Cursor's TAB is too good to give up vs Roo / Cline.

I do agree Claude's the best for programming so would love to use it full-featured version.

I currently use cursor with Claude 4 Sonnet (thinking) in agent mode and it is absolutely crushing it.

Last night i had it refactor some Django / react / vite / Postgres code for me to speed up data loading over websocket and it managed to:

- add binary websocket support via a custom hook - added missing indexes to the model - clean up the data structure of the payload - add messagepack and gzip compression - document everything it did - add caching - write tests - write and use scripts while doing the optimizations to verify that the approaches it was attempting actually sped up the transfer

All entirely unattended. I just walked away for 10 minutes and had a sandwich.

The best part is that the code it wrote is concise, clean, and even stylistically similar to the existing codebase.

If claude code can improve on that I would love to know what I am missing!

Apple builds both the hardware and the software so it feels harmonious and well optimized.

Anthropic build the model and the tool and it just works, although sonnet 4 in cursor is good too but if you've got the 20$ plan often you're crippled on context size (not sure if that's true with sonnet 4 specifically).

I had actually heard about the OpenAI Codex CLI before Claude Code and had the same thought initially, not understanding the appeal.

Give it a shot and maybe you'll change your mind, I just tried because of the hype and the hype was right for once.

it completely blew my mind. i wrote maybe 10 lines of code manually. it’s going to eliminate jobs.

that's the part i'm not sold on yet. it's a tool that allows you to do a year's work in a week - but every dev in every company will be able to use that tool, thus it will increase the productivity of each engineer by an equal amount. that means each company's products will get much better much faster - and it means that any company that cuts head count will be at risk of falling behind it's competitors.

i could see it getting rid of some of the infosec analysts, i guess. since itll be easier to keep a codebase up to date, the folks that run a nessus scan and cut tickets asking teams to upgrade their codebase will have less work available.

Exaggerations like this really don't help your credibility

Brings a crazy new meaning to "fail fast" though

You should never have to copy/paste something from Claude Code...?

I still use the Cursor auto complete but the rest is all Claude Code.

Even without the extension Claude is directly modifying and creating files so you never have to copy paste.

It absolutely aced an old take-home test I had though - https://jamesmcm.github.io/blog/claude-data-engineer/

But note the problems it got wrong are troubling, especially the off-by-one error the first time as that's the sort of thing a human might not be able to validate easily.

I’ve been avoiding LLM-coding conversations on popular websites because so many people tried it a little bit 3-6 months ago, spot something that doesn’t work right, and then write it off completely.

Everyone who uses LLM tools knows they’re not perfect, they hallucinate some times, their solutions will be laughably bad to some problems, and all the other things that come with LLMs.

The difference is some people learn the limits and how to apply them effectively in their development loop. Other people go in looking for the first couple failures and then declare victory over the LLM.

There are also a lot of people frustrated with coworkers using LLMs to produce and submit junk, or angry about the vibe coding glorification they see on LinkedIn, or just feel that their careers are threatened. Taking the contrarian position that LLMs are entirely useless provides some comfort.

Then in the middle, there are those of us who realize their limits and use them to help here and there, but are neither vibe coding nor going full anti-LLM. I suspect that’s where most people will end up, but until then the public conversations on LLMs are rife with people either projecting doomsday scenarios or claiming LLMs are useless hype.

- It generates slop in high volume if not carefully managed. It's still working, tested code, but easily illogical. This tool scares me if put in the hands of someone who "just wants it to work".

- It has proven to be a great mental block remover for me. A tactic i've often had in my career is just to build the most obvious, worst implementation i can if i'm stuck, because i find it easier to find flaw in something and iterate than it is to build a perfect impl right away. Claude makes it easy to straw man a build and iterate it.

- All the low stakes projects i want to work on but i'm too tired to after real work have gotten new life. It's updated library usage (Bevy updates were always a slog for me), cleaned up tooling and system configs, etc.

- It seems incapable of seeing the larger picture on why classes of bugs happen. Eg on a project i'm Claude Code "vibing" on, it's made a handful of design issues that started to cause bugs. It will happily try and fix individual issues all day rather than re-architect to make a less error prone API. Despite being capable to actually fix the API woes if prompted to. I'm still toying with the memory though, so perhaps i can get it to reconsider this behavior.

- Robust linting, formatting and testing tools for the language seem necessary. My pet peeve is how many spaces the LLM will add in. Thankfully cargo-fmt clears up most LLM gunk there.