0 - https://github.com/gastownhall/beads

The issue is the quippy titles, “something - aside - continue” phrasing, and other constructions are feel like they or actually are wholly LLM written. I find a high correlation to this and low density fluff. The author did not have 10 paragraphs of things to say, but used an LLM to inflate a short outline to that. We would all of been better off with a tighter document - either human written or better prompted.

It’s the only 1 out of 200 in that area, so it’s not representative of what data centers sound like. It does show how you can’t trust the operators to do what best for the local community. It does show how a functioning government works because Loudon county increased oversight and changes the rules to stop another project like that. Setup policies to manage externalities, and don’t make ignorant bans.

Put in place sensible rules around noise, locating in pre-planned areas, and covering the cost for electrical upgrades then let the market decide how many to build. Most people appear to be getting their information from TikTok and have developed a very ignorant NIMBY attitude.

To be blunt progress does get made by listening solely to those who get short end of the stick. Japan and China have good rail in large part because the central government can simply make the globally better choice over the objections of those nearby who lose out due to noise and other factors. We don’t need to do that, we simply need to not let ignorance win and instead regulate the externalities properly, and capture value for the public through property taxes.

File system isolation is easy now, it’s not worth HN front page space for the n’th version. It’s a solved problem (and now included in Claude clCode).

So a better question to ask is - Do you have any ideas for an objective way to a measure a performance of agentic coding tools? So we can truly determine what improves performance or not.

I would hope that internal to OpenAI and Anthropic they use something similar to the harness/test cases they use for training their full models to determine if changes to claude code result in better performance.

I can do all that without having to even worry about virtual ends, or Python versions too.

0 - https://github.com/openai/codex

Another way to say it is that people think it’s much more likely for each decent LLM startup grow really strongly first several years then plateau vs. then for their current established player to hit hyper growth because of AGI.

Along the same lines the Meta Wayfarer[2] smart glasses lets you take slice of life photos and videos without needing to whip out your phone. You lose a ton of quality but stay in the moment more. The AI features are getting better so eventually you'll be able to use it for basic information lookup.

0 - https://guide.duo.com/apple-watch

1 - https://guide.duo.com/duo-wear

2 - https://www.meta.com/ai-glasses/wayfarer

> I have woefully little experience with these tools.

> I do not want to be using the cloud versions of these models with their potentially hideous energy demands; I’d like to use a local model. But there is obviously not a nicely composed way to use local models like this.

> The models and tools that people are raving about are the big, expensive, harmful ones. If I proved to myself yet again that a small model with bad tools was unpleasant to use, I wouldn’t really be addressing my opponents’ views.

Then without having any real practical experience with the cutting edge tooling they predict:

> As I have written about before, I believe the mania will end. There will then be a crash, and a “winter”. But, as I may not have stressed sufficiently, this crash will be the biggest of its kind — so big, that it is arguably not of a kind at all. The level of investment in these technologies is bananas and the possibility that the investors will recoup their investment seems close to zero.

I think a more accurate take is this will be like self driving, huge investments, many more losers thank winners, and it will take longer than all the boosters think. But in the end we did get actual self driving cars, but this time it's with LLMs it is something that anyone can use by clicking a link vs. waiting for lots of cars to be built and deployed.

There is known sensitivity (no pun intended ;) to wording of the prompt. I have also found if I am very quick and flippant it will totally miss my point and go off in the wrong direction entirely.

0 - https://news.ycombinator.com/item?id=44164633