HN Reader

> What other tasks could be automated today with the current LLMs performance?

CEO speeches and pro-LLM blogs come to mind.

Again, there is a vague focus on "updating dependencies" where allegedly some time was saved. Take that to the extreme and we don't need any new software. Freeze Linux and Windows, do only security updates and fire everyone. Because the ultimate goal of LLM shills or self-hating programmers appears to be to eliminate all redundant work.

Be careful what you wish for. They won't reward you for shilling or automating, they'll just fire you.

> What if Claude Code operated autonomously with massive parallel compute?

Afaik this is not possible as LLMs have linear conversations.

I really enjoyed Claude Code. I was using it on some side projects for about a month with API credits, and I signed up for the Max subscription shortly after it started working with Code. Overnight, my account was banned, and I have no idea why.

It sucks getting banned from such a cool and helpful tool :(

This feels a bit too optimistic, in practice it often gets stuck going down a rabbit hole (and burning up your requests / tokens doing it!).

Like even when I tested it on a clean assessment (albeit with Cursor in this case) - https://jamesmcm.github.io/blog/claude-data-engineer/ - it did very well in agent mode, but the questions it got wrong were worrying because they're the sort of things that a human might not notice either.

That said I do think you could get a lot more accuracy between the agent checking and running its own answers, and then also sending its diff to a very strong LLM like o3 or Gemini Pro 2.5 to review it - it's just a bit expensive to do that atm.

The main issue on real projects is that just having enough context to even approach problems, and build and run tests is very difficult when you have 100k+ lines of code and it takes 15 minutes to clean build and run tests. And it feels like we're still years away from having all of the above, plus a large enough context window that this is a non-issue, for a reasonable price.

in my experience using agents has just wasted my time and money, they are good for small things if you are lazy and watching a movie looking at the results every 10 minutes, reverting and trying again

The recent developments are impressive. I’m now using my IDE as a diff viewer. Everything goes through the terminal. If there is an error, CC can analyse and fix it.

Still needs a lot of handholding. I do not (yet) think big upfront plans will suddenly start working in the enterprise world. Let it write a failing test first.

Wait 'til you see the bill.

Has anyone actually gotten productivity improvements from Claude Code?

What’s the use case?

(I tried some things, and it blew up. Thus far my experience w agents in general)

normal English would be "Why does Claude Code feel like magic?"

edit: or "Why Claude Code feels like magic" without the ?.

Technology feels like magic when you don't understand it.

Well, Intelligence is arguably represented in a “prior” that skews the result to an optimum faster, with fewer iterations. What the article is describing as intelligence is exactly the opposite, it’s just brute force.

I find the use of the word intelligence to be a bit of a misnomer. Is something intelligent if all its doing is pattern matching? Is the evolution that led to owl butterflies appearing like an owl intelligent? Im not sure.

As an aside, its amusing we simulatenously have this article on the front page as well as [Generative AI coding tools and agents do not work for me](https://news.ycombinator.com/item?id=44294633) also on the front page. LLMs are really dividing the community at the moment and its exhausting to keep up with what I (as a dev) should be doing to stay sharp

LLM reflects YOUR intelligence, it's the secret truth.

Kinda reminds me of something my old AI professor used to say, "every problem is a search problem".

Intelligence is really just a measure of ones's ability to accurately filter and iterate over the search space.

Evolution is one extreme where the heuristic is poor so it must do a huge amount of iteration over many bad solution to find reasonably good solutions. Then on the other hand you have expert systems which are great at refining the search space to always deliver quality answers, but filter too much and are therefore too narrow so lack the creativity and nuance of real intelligence.

LLMs provide good heuristics and agents with verifiable goals allow for iteration. This combination results in a system which demonstrates significantly more intelligent than either of its parts.

Usually, I'll go through my coding like I would have pre-LLMs.

Then, when I see something that looks like it can be reliably automated by an AI agent, I'll open up Cline and put Claude or Gemini Flash to work. This has a 90% success rate so far and has saved me hours of work.

Is claude able to write rv64 assembly code?

For instance can you asked for a vector-based quicksort? Well, with a "vector size unit" of a "standard" cache line, namely 512bits/64bytes (rv22+ profile).