Fully this.

In my day to day life it improves nothing. I certainly could write a complicated harness over a local model to get it to automate a ton of my day to day tasks but… Why?

Why would I do that? Regular deterministic tools and regular programming languages already give me the ability to automate the stuff that is truly tedious. Aside from that most of the tasks that people seem to use it for are tasks were the friction of doing them is were all the benefit lies.

People using this shit for journaling or taking notes is INSANE.

Yeah yeah yeah

But the problem is it will be used to disarm leftists. This regime has already displayed a preference for selectively applying the law to political enemies.

It would be wise for those of us that share a common, human-first, political position to make ourselves extremely unpleasant to interact with. Ideally in large, mobile, groups.

All the money in the world cannot render someone immune to kinetic energy

Create semipermeable intentional communities that center around convivial technology and human empowerment?

For real, this isn’t going to get better and every day that passes I ask myself “what is this actually buying me? Do I even like this?”

I know the common refrain is we can’t “bury our heads in the sand” but history tells us that humans take the path of least resistance and that path is the “sloppening”

What a young account to come into this world, arrive in this thread about an AI violating containment, and then tell an unrelated anecdote about how well an AI agent did a vaguely complicated task when properly harnessed.

Certainly a human being is on the other side of this post and not, say, one of the countless bots out of Eglin AFB.

Certainly

I don’t know I kind of like it.

It’s fun and makes my brain do a few pushups

I can not tell you how tired of seeing these vibe coded projects I am.

You didn’t give nearly enough of a shit to write the application, why should I give enough of a shit to use it? Could you explain, in detail, line by line, what the happy path of a standard web request is in this thing? Could you walk me through the specific engineering decisions that were made and why? Could you point to the specific regions of code that reflect those engineering decisions?

I’m beyond exhausted with these things and honestly I’ve gotten to the point where I’d like for us to ban non-codeberg repos

I’m with you comrade. It’s tough raising a kid in this world but as far as I see it we’re playing the long game now.

Gotta believe that our way of doing things wins out over time. Along with other, more direct, strategies.

You joke but that’s basically the conclusion of both the newer agent studies and the older Xerox park study on peripheral use. Language and logic are stored in an easier to access location in the brain than the kinds of skills used in architecture and planning.

To be clear, I’m no rube. I recognize that these are powerful tools. But I suppose my take here is that if an LLM is necessary to get rid of a lot of the boilerplate and setup for a task that indicates we should explore how we’re doing the task.

What I want to see is using these tools not to delegate our problem solving but finding ways to enhance and accelerate it and I don’t think writing spec sheets is the answer.

One, that sounds truly miserable.

Two, there is a decent body of evidence to suggest that this method does not actually speed up development unless you go full lights out software factory which… Why would you want to do that?

https://ide.mit.edu/insights/ai-productivity-and-roi/

EDIT: As an aside this actually reminds me of the Xerox park study into efficiency gains for keyboard heavy workflows vice mouse heavy workflows. Keyboards were perceived as faster by subjects but when actually measured the mouse was faster.

I genuinely question if they’re thinking very far into the future. Billions of agents doing what? We didn’t need a rogue AI to turn us into paper clips; we’re going to do that ourselves. Is he thinking local AI at everyone’s computer? People barely use the features of the machines they have now.

What is the difference between the models writing code “well” and their performance in this context? Are we referring to readability?

Genuine question. If we use agents to read, edit, and review code, why do we care about readability? That’s a human constraint. Unless attempting to do those three is not effective and thus requires human attention to correct issues which would justify readable code. If that’s the case; why use the agent to edit the code in the first place?

To quote the research paper conclusion…

Conclusion We evaluate the impact of context files on coding agent performance for four common coding agents on SWE-BENCH and the novel CTXBENCH, built from recent GitHub issues and less popular repositories containing developer-written context files. We find that all context files consistently increase the cost and number of steps required to complete tasks. LLM-generated context files have a marginal negative effect on task success rates, while developer-written ones provide a marginal performance gain, neither statistically significant. Our trace analyses show that instructions in context files are generally followed and lead to more test- ing and broader exploration; however, they do not function as effective repository overviews. Over- all, our results suggest that context files don’t improve coding agent performance, and should only contain specific additional instructions beyond what is already available in the codebase. This high- lights a concrete gap between current agent-developer recommendations and observed outcomes, and motivates future work on principled ways to automatically generate concise, task-relevant guid- ance for coding agents.

That sounds like “Agents.MD doesn’t work” to me.

Am I missing something?

This. This 1000%.

Software is not a mass-produced commodity that has to be distributed as fast as possible. People already have a limited attention span for the features of already existing software so speed running even more does not create value.

At some point we’re going to have to rekon with the fact that creating, reviewing, and provisioning aren’t the real bottlenecks.

Humans using the software is the bottle neck. Humans trusting the software is the bottleneck. Humans building communities and cultures around specific tools and methodologies is the bottleneck.

At the end of the day you’re user base isn’t going to be “AI” agents. It’s going to be people.

This might be one of the best summaries of LLMs in their current state I’ve seen here. People claiming they’re useless are stuck in 23’ but to say they’re at AGI/ASI is accelerationist techo-paganism.

Based and levelheaded take

Okay I’m seeing a lot of your replies here this is a really weird argument to make. You’re literally arguing from symantics.

Hi! I use FreeBSD as a daily driver.

I browse the web, code, and game on it. Works great for me.

My current wishlist is for FreeBSD to have a more robust process supervision system (Dinit I’m looking at you) and for pkg to include some kind of declarative way to build.

It’s great, I love it, join devil Linux.

It’s always refreshing to read something that I can be 100% sure was not written by an AI.

A few of the erdos problems have been independently verified. It’s legit.

I’m not a rust programmer, can anyone with experience in systems programming explain a legitimate use case for the uutils other than weakening the GPL? The auther even admits that several coreutils are still GNU in 26.04 which begs one to ask “why the rewrite?”