Yeah that was what I was most worried about when I read the top comment here. I found the use of language a feature not a bug. I don’t care how good it reads. If I can communicate with it concicely it’s enough to get my work done. I don’t hate the language for copy either, but yeah different users, different problems.

Venting reduces the likelihood of acting in aggressive feelings

All these studies suggest loneliness makes you unhappy, however I feel happiest most when lonely and doing my thing and not with people. With people I just feel frustrated or weird, because I think so different than the others.

Being alone does not equal loneliness.

And merely being with people is not an antidote to loneliness.

Being alone and being lonely are distinct concepts.

But a lot of the research is not about 'loneliness' in particular, but rather how friends or social circles make you happier

Possibly you are conflating being alone to loneliness?

I know the difference, but the studies I’ve heard of seemed to rather focus on the benefits of social circles, not analyzing 'loneliness' in itself. However I haven’t fully digged into all the evidence, but I hope you guy’s are right!

solitude =/= loneliness

First of all that could be a causality ≠ correlation, but more importantly. Even if it might be the biggest predictor, it might not be the biggest lever.

Still interesting train of thought that I might need, but the article is exaggerating the evidence and not adding the right disclaimers.

I’m thinking that since 2015. Like BMW C1 just with doors on the side and a bit more security. This would approx allow 3-4x as many travellers on a given route compared to traditional cars.

A C1 with more security, meaning more material and air between you and a potential high-speed obstacle, is called a car and is sized like one.

Fair point.

I still think you could build single person cars that are more secure than traditional cars and use less space and energy

Terminology is a crazy lever with AI

I think for small projects you need to scale the coders mental model, which afaik works in the fastest time, when you let ai do the exploration and planning, but coder needs to write the code itself and then ai verifies. That generates the best of world codes and the coder at least has written the code. It’s scalable.

In projects that are so big that no single coder or no small group of coders is sufficient to grasp I don’t have personal experience, but my guess would be that they are just a cluster of other small projects.

I don’t want to be a hater, but somehow i still keep throwing vacuum roboters away and prefer the manual machine. It somehow always ends up worrying me more than helping. Crashing, charging putting away, putting things away for it to work (peeping). There are a lot of small things that come to these things that have evolved over the last 100 of years.

When i think about humanoids and household. I have so much particular ways of how I want my household to be done. I find it really hard to believe you can make it act that way. I struggled to teach humans how I want it. So I ended up doing everything myself again.

I think the author means ecomonically valuable not valuable to you.

I’m seeing a lot of people that having that train of thought. I think that is a fallacy. I can understand that some LLM execution can be faster, but definitely not all. Agents need to explore, grep and get back up to speed to get context, if you have a good mental model, you can do changes or adaptions in <7s with a bunch of shortcuts or commands.

One could argue to find the <7s commands in your head takes you more mental power than to just wish it in to the LLM and whilst its running you can wish something else in another session, but I’m thinking that the cost of context is more important than the actual execution time for your task. Every extra task gets more expensive. It’s not a ressource where you have a limit, right from the 2nd task the cognitive load increases.

Therefore I’m thinking one task that can be done in one context window without switching is worth a load in these days of constant distraction.

I get your point but I do prefer delegating almost all of the things to the LLM.

A lot of times human commands are prone to errors / edge cases as well. Example a simple git pull command usually would take < 7 seconds, but then LLM can take care of resolving merge conflicts etc as well.

A simple git push is usually instant but that comes with an overload of some un intended changes being pushed, which LLMs take care of removing themselves.

When LLM is doing its thing, we can spend the same time in writing the next prompt.

> A simple git push is usually instant but that comes with an overload of some un intended changes being pushed, which LLMs take care of removing themselves.

In my experience it can often be the opposite - AI would commit a lot of slop comments and sometimes unnecessary stuff, whereas if you can review things in GitKraken or another program with diffs, things are closer to what you want. Writing commit messages and PR descriptions (maybe change summaries, the intro less so) is easily outsourced to the LLMs though.