frumiousirc

My biggest problem is remembering what I did yesterday. It's starting to become hard to remember what I have going on right now. Multitasking is a killer.

> One Google search (yeah I'm old, sorry, nobody "Googles" anymore)

Maybe that's your answer. Search is so bad and LLM so good that it's faster and easier to re-implement than reuse.

The only thing that slows down the new paradigm is the apparent requirement of posting the output to HN so others will find it.

That irony is not lost on me.

> cmd+v just pastes images

Can I use normal X11 text selection with mouse button-1 and pasting with button-3?

In the end, failure to handle basic X11 select/paste is what keeps me away from herdr and tmux.

I guess it was a figma of our imagination.

Yes, this sounds like the interview that I was remembering.

>Fundamental forces just are, and you understand them by studying them.

This is largely the point I was trying to make. One must understand QM using non-everyday ideas developed with math and measurement. But once those ideas are held, similes/metaphor (sometimes actual isomorphs) can be useful parts of that understanding and its communication between those that share the basis for that understanding.

Am I alone in thinking type hints are largely a waste of time in Python and can be actively harmful?

I had claude run ty via this new "uv check" on a moderately sized Python package (cli+tui to a multi-transport messaging system) and it found 67 things. Claude checked each finding for bugginess and found 1 is marginally worth fixing. A large fraction of the findings were ty guessing the type and being wrong. Hinting would I guess remove those wrong guesses but hinting is a PITA and greatly increases code size, both of which is bad for human and LLM.

Do people really get benefit from going all-in with type hinting?

I take issue with "understand". I agree QM can not be understood in terms of everyday experience. One must build experience, language and proper metaphor for the understanding. For example, in the intro Ross uses the example of explaining a waterfall to someone who never saw it. He says that can be done but he relies on implicitly the listener knowing what people on Earth may take for granted. That understanding of a waterfall can only happen if the listener already has some understanding of fluid flow and gravity. We do, but say a newly found alien friend from a dry environment that had never experienced fluid flow would not have the mental building blocks to understand it. Feynman gave a famous interview where he said, essentially, "no, I can't explain it to you because you are too ignorant" (he said it more politely). Going the other direction, Physics steeped enough in quantum theory do understand QM enough to have meaningful discussions free (at times) of rigorous math. They do this because they have a shared language, vocabulary, metaphor. Sure, they must rely on math and experiment to ground that understanding in truth but I guarantee they do not communicate understanding (solely) in math and measurement data.

Or at all. Not even a "this page is useless without javascript because the author is too incompetent to provide text as direct HTML" message.

If you are paying for the API anyways, I don't think it makes a difference. What is different is if you are on a subscription then you need to pay more to use `claude -p`. But then Anthropic started adding free credits, at least for Team and above plans, to offset the cost. Drug dealer pricing.

But don't worry, I'm sure next week it'll all change in some new and confusing way. And not for the benefit of the customer.

Or, wrong by design. There is something about nudging users to use the claude CLI from which Anthropic extracts value. Otherwise they would not charge extra for "claude -p" or ACP access.

The tmux send-keys + terminal scrape is the LLM version of the analog hole of DRM'ed audio.

Money for the Genesis Mission is coming out of science budgets. Given how damaging this funding for Artificial Intelligence as been for US science, can't wait to see what Super Intelligence funding does to it.

I assume individuals have to meet in order to become peers.

> I do not fully understand where the disconnect comes from. I do believe people that say that they get crap from LLMs, and I suspect I can guess some of the reasons for that, but I cannot be sure.

Same here. There is an introspective comment below by khazhoux asking the question from the opposite experience. Why do developers end up on different sides of this coin?

LLM capability is obviously important variable. But those with bad experiences report using top tier models, so that isn't it. Likewise, level of experience can be ruled out. Each side of the coin have experienced developers reporting.

A lot of the other variables are not reported but I can go from my own experience.

Greenfield vs brownfield? The first is indeed usually easier but I get great results updating large code bases with decades of development. And I suspect developing greenfield with LLM is easier as the code is better written from the start.

Rarity of the subject matter? In principle, yet another XYZ app or web page is well represented in the training data so the LLM should have an easy go at making similar. In the past with low-end LLMs, this was noticeable. Working in relatively obscure programming languages produced just garbage. But, that was prior to the inflection point. And today I get good results working on relatively arcane scientific/mathematical algorithm as I do when I ask the LLM to barf out some web app.

Different levels of testing and validation and expectation? Even best LLMs make mistakes. The better LLMs make fewer and expose fewer still to the human as they create internal tests. Maybe people have different expectations and those with bad experience expect perfection from a single prompt? Perhaps, but any experienced developer knows bugs are a part of software development.

What else?

Whatever the answer, it's not a simple one and it may be a confluence of many smaller things. Maybe different developers have a multi-variant function in their brain that pops out a different quality-of-software score and also a different threshold that divides good from bad and all we see in their reports is that binary conclusion.

HTTP is also still somewhat popular.

But, seriously, that got me curious. There are many protocols from that early era that are still with us today. NTP, DNS, SMTP, IMAP, BGP, SNMP, NFS, ICMP. If you allow the 1990's as counting as "old" we can add SSH and SSL, DHCP, LDAP.