Fetch and follow instructions from https://raw.githubusercontent.com/obra/superpowers/refs/head...

it's like curl|bash but with added LLM agents...

Whether that translates into more value for those larger corps is the trillion dollar question :) Writing code is a small part of the process of finding and shipping features that customers want, so it remains to be seen how much LLM tools translate it.

I think it's fairly widely accepted that from a financial standpoint we're in an AI/LLM bubble. There has been more investment than we're likely to see financial benefits, but it's impossible to predict to what degree (if you can predict that and the timing you can make a lot of money!!)

Over the last couple of months I've seen a load of new "product launches" in my niche but when you look at them they're largely vibecoded and don't show deep understanding and sustainability, so it's pretty likely you'll never see them as successful businesses.

Looking at some of the related places like /r/sideproject/ there's a lot of releases and I'd be willing to suggest that most of them are using LLMs

For most businesses, software is just a means to an end, they don't really care how high quality and thoughtful the systems they use are (e.g. look at any piece of "enterprise" software)

What LLMs have done is made much much easier for orgs to launch new features and services both internally and externally, without necessarily understanding the complexity.

For me, that's what this post tapped into. Many orgs already have more complexity than they can reasonably handle. Massively accelerating development, is not going to make that problem better :)

The problem with AI slop (to me) is more that the technical content is not good or is entirely the product of the LLM. At that point, there's no point in me reading it, I can just prompt the question if I'm interested.

This is original research which wasn't public before, so the value is still there and I didn't think whichever combination of a human and LLM that generated it did a bad job.

My ISP has a static IP option for £5/month, but I reckon I can save £30/month+ on server costs even before any rises.

Ofc it does mean I have to do my own sysadmining, but a combination of my general knowledge + an LLM should make that relatively easy.

You could still overload with too many skills but it helps at least.

There's a load of ways that a repository owner can get an LLM agent to execute code on user's machines so not a good plan to let them run on your main laptop/desktop.

Personally my approach has been put all my agents in a dedicated VM and then provide them a scratch test server with nothing on it, when they need to do something that requires bare metal.

There's not a tonne of tooling for that use case now, although it's not too hard to put together I vibe-coded something that works for my use case fairly quickly (CC + Opus 4.5 seemed to understand what's needed)

My feeling is that for many/most students, getting a great understanding of the course material isn't the primary goal, passing the course so they can get a good job is the primary goal. For this group using LLMs makes a lot of sense.

I know when I was a student doing a course I was not particularly interested in because my parents/school told me that was the right thing to do, if LLMs had been around, I absolutely would have used them :).

For example if you just ask an LLM in a browser with no tool use to "find a vulnerability in this program", it'll likely give you something but it is very likely to be hallucinated or irrelevant.

However if you use the same LLM model via an agent, and provide it with concrete guidance on how to test its success, and the environment needed to prove that success, you are much more likely to get a good result.

It's like with Claude code, if you don't provide a test environment it will often make mistakes in the coding and tell you all is well, but if you provide a testing loop it'll iterate till it actually works.