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Doesn’t Sony have the best codec on Bluetooth? It definitely has worse noise cancellation than my AirPod, but afaik it should have better audio quality on paper.

Yeah, but if you're using Apple phones/tablet/computers they only support AAC Bluetooth anyway unless you add a Bluetooth dongle, which kinda defeats the purpose of ever using Airpods.

At least the WH-1000XM6 also has better noise cancellation (on paper).

What does “down” and “stationary” mean? I put my Sony to random paces, mainly just throwing it into my backpack. Would that be considered as down and stationary? Would it be turned off if I’m on the move? In a car? On a bus?

I mean, I regularly leave them on a shelf in my apartment and they apparently do not consider that "down" or "stationary" enough to not just drain the battery completely. Truly a bafflingly bad design from the company that is (was) known for great hardware design.

Do they? I’ve never got a response that something was impossible, or stupid. LLMs are happy to verify that a noop does nothing, if they don’t know how to fix something. They rather make something useless than really tackle a problem, if they can make tests green that way, or they can claim that something “works”.

And’ve I never asked Claude Code something which is really impossible, or even really difficult.


Claude code will happily tell me my ideas are stupid, but I think that's because I nest my ideas in between other alternative ideas and ask for an evaluation of all of them. This effectively combats the sycophantic tendencies.

Still, sometimes claude will tell me off even when I don't give it alternatives. Last night I told it to use luasocket from an mpv userscript to connect to a zeromq Unix socket (and also implement zmq in pure lua) connected to an ffmpeg zmq filter to change filter parameters on the fly. Claude code all but called me stupid and told me to just reload the filter graph through normal mpv means when I make a change. Which was a good call, but I told it to do the thing anyway and it ended up working well, so what does it really know... Anyway, I like that it pushes back, but agrees to commit when I insist.


After such hard-won wins, ask the AI to save what it learned during the session to a MD file.

I've definitely had pushback on what to do or approaches, yes. I've had this more recently because I've been pushing more on a side of "I want to know if this would end up being fast enough / allow something that it'd be worth doing". I've had to argue harder for something recently, and I'm genuinely not sure if it is possible or not. While it's not flat out refused to do it, it's explained to me why it won't work, and taken some pushing to implement parts of it. My gut feeling is that the blockers it is describing are real but we can sidestep them by taking a wilder swing at the change, but I'm not sure I'm right.

We've seen something similar in the past decades: outsourcing. And it worked completely differently how it was envisioned a few decades ago, at least in the field of software development. So let's wait what happens. Some kind of backlash has been already started in the past months.

What is the harm in this case? Shit people are shit even without information. They would be snark about something else then.

I think it was covered during a discussion about immigrants that are easily rejected - because they're immigrants.

The points was that it added another layer of issues for immigrants because they didn't understand the neighbourhood they "should be living in" with their revenue.


Why is this not the “shit people do shit things” category? This happens even without being immigrants. Large part of my family lives in a way poorer neighborhood than what we can afford, because we don’t care to move. People who have problem with this had other problems even before we got richer. There is exactly zero difference. The exact same people are snark as before, just for something else now. They were and would be snark even without this.

This seems to me a very bad attempt to hide xenophobia.


The problem is that average people cannot tell even now. Heck, I'm quite sure that /r/all is completely bot driven, yet I still check it occasionally. I'm not even sure about HN, but I didn't find yet so obvious manipulation than on Reddit.

It's funny when people start accusing eachother of being chatGPT.

That sounds exactly like the kind of thing chatGPT would say to hide the fact it’s chatGPT… :)

Even cutting edge models are not very good. They are not even on mediocre level. Don’t get me wrong, they are improving, and they are awesome, but they are nowhere near good yet. Vibe coded projects have more bugs than features, their architecture and design system are terrible, and their tests are completely useless about half the time. If you want a good product you need to rewrite almost everything what’s written by LLMs. Probably this won’t be the case in a few years, but now even “very good” LLMs are not very good at all.

Not sure why you're being downvoted, this is very much my experience. When it matters (like, customer data is on the line) vibecoded projects are not just hilariously bad, but put you in legal danger.

We've so far found that Claude code is fine as a kind of better Coverity for uncovering memory leaks and similar. You have to check its work very carefully because about 1 time in 5 it just gets stuff wrong. It's great that it gets stuff right 4 times in 5 and produces natural code that fits into the style of the existing project, but it's nothing earth-shattering. We've had tools to detect memory leaks before.

We had someone attempt to translate one of our existing projects into Rust and the result was just wrong at a fundamental level. It did compile and pass its own tests, so if you had no idea about the problem space you might even have accepted its work.


With Claude Code now having a /plan mode - you can take your time and deliberate through architecture and design, collaboratively, instead of just sending a fire-and-forget. Much less buggy and saves time if you keep an eye on the output as you go, guiding it and catching defects, imho.

For that you need to create something which you know exactly how you want to code, or what architecture is needed. In other words, you would win basically nothing, because typing was never the real bottleneck (no matter what VIM and Emacs people would tell you).

LLMs also make mistakes even way lower level than those one pagers allow you to control with the planning mode. Which I use all the time btw. And anyway, they throw the plan out of the window immediately when their tried solutions don't work during execution, for example when a generated test is failing.

Btw, changing the plan after its generation is painful. It happens more than not that when I decline it with comments it generates a worse version of it, because it either miss things from the previous one which I never mentioned, or changes the architecture to a worse one completely. In my experience, it's better to restart the whole thing with a more precise prompt.


Ah, this is true - for my purposes, I've been directing the design and deliberating on the constraints and specifications for a larger system in tandem with smaller planning sessions.

That has worked well so far, but yes, you are totally right, there are still quite a few pain points and it is still rather far from being fire-and-forget "build me a fancy landing page for a turnkey business" and getting enterprise quality code.

edit: I think it is most important that you collaborate with Claude Code on quality in a systematic way, but even that has limits, right now - 1M context changes things a little bit.


You know, with all the babysitting needed, I wonder if effort is not better spent in just, you know, writing code.

Can you actually quantify the time & effort 'saved' letting LLM generate code for you?


For me, personally, I'm building things that would have been impractical for me to do as cleanly within the same amount of time - prototypes in languages that I don't have the muscle memory for, using algorithms i have a surface level understanding of but would need time to deeply understand and implement by hand, and, at my pace, as a retired dev, is probably quantified in terms of years worth of time and effort saved.

edit: also, would I take the time to implement LCARS by hand? No. But with an LLM, sure, took it about 3 minutes or less to implement a pretty decent LCARS interface for me.


That’s not inherent of universal healthcare at all. In Austria, you can go to a different doctor if you wish.

> Couple this with the fact that models respond better/worse to certain prompts depending on the stylistic composition of the prompt itself.

Do we really know this, or is it just gut feeling? Did somebody really proved this statistically with a great certainty?


I hit limit of Pro in about 30 minutes, 1 hour max. And only when I use a single session, and when I don't use it extensively, ie waits for my responses, and I read and really understand what it wants, what it does. That's still just 1-2 hours/5 hours.

What do you do to avoid that?


You're probably having long sessions, i.e. repeated back-and-forth in one conversation. Also check if you pollute context with unneeded info. It can be a problem with large and/or not well structured codebases.

The last time I used pro, it was a brand new Python rest service with about 2000 lines generated, which was solely generated during the session. So how I say to Claude that use less context, when there was 0 at the beginning, just my prompt?

So you had generated 2000 lines in 30 minutes and ran out of tokens? What was your prompt?

I’d use a fast model to create a minimal scaffold like gemini fast.

I’d create strict specs using a separate codex or claude subscription to have a generous remaining coding window and would start implementation + some high level tests feature by feature. Running out in 60 minutes is harder if you validate work. Running out in two hours for me is also hard as I keep breaks. With two subs you should be fine for a solid workday of well designed and reviewed system. If you use coderabbit or a separate review tool and feed back the reviews it is again something which doesn’t burn tokens so fast unless fully autonomous.


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