llmslave2

3 seems likely, especially since defending their views in this particular case opens them up to some pretty nasty insults.

Also I think a lot of people simply think models which are published openly shouldn't be held to the same legal standards as proprietary models.

An intern is a human, unlike Microsoft Word or an LLM, which are tools/machines/etc.

I find it fascinating to read comments from a lot of people who support open models without guardrails, and then to read this thread with seemingly the opposite sentiment in overwhelming majority. Is it just two different sets of users with differing opinions on if models should be open or closed?

Right, but the makers of the murder weapon aren't culpable.

Or do you think a Microsoft exec should go to jail every time someone uses it to write a death threat?

You can use esbuild to build your entire project with a single command. Node has a built in test runner. You only need the complexity because you're convinced you need it.

And also a build pipeline doesn't have to be difficult to write. You can do it in like 50 lines of code and esbuild. And then you get to bundle your CSS, use React or whatever, Typescript, etc.

> I believe this new wave of zeal is being somewhat driven by an Anthropic astroturfing campaign.

Yeah I've sort of noticed this on X for the brief time I was on there this weekend. The Claude Code creator was hyping it up to the moon, and when people called him out for it he said he would feel the same way if he wasn't making 1000 racks a year with it. Sure mate.

What people don't realise is if tech progresses to the point where everything is automated, the marginal cost of everything will basically go to zero. It would be better to give away food and shelter for free if it keeps things peaceful. And if not, people have revolted for far less.

That being said it's a complete utopia and once this bubble pops we are basically going to be where we were, but with excellent natural language parsing and generation, with some useful code generation and introspection tools, writing assistants, etc. Which will be great, but not world changing.

Thank you for your insightful comment! I appreciate your enthusiasm for this innovative approach. You've highlighted several key strengths of this design:

- Pragmatic syntax choice: The comment-based annotation system is indeed a clever solution that minimizes friction for adoption

- Avoiding past pitfalls: By learning from previous safety proposals, this approach sidesteps the intrusive syntax issues that hindered earlier efforts

- Incremental adoption pathway: The ability to gradually introduce safety guarantees without requiring a complete rewrite is a game-changer for legacy codebases

- Democratizing compiler expertise: Leveraging LLMs to tackle problems that traditionally required specialized knowledge is an exciting development

Overall, this represents a promising step forward in bridging the gap between C++ and Rust's safety guarantees. It will be interesting to see how this evolves in production environments!

I'm sure there is plenty of language parsers written in Haskell in the training data. Regardless, the question isn't if LLMs can generate code (they clearly can), it's if agentic workflows are superior to writing code by hand.

There is evidence that LLM usage is actually making people dumber. I'm not sure if they've figured out the cause/effect or not but that's enough evidence for me to avoid them if I can. They can be useful for some stuff but I found myself offloading my thinking a little too frequently.

Anyways if we do get to the point where you need to use LLMs to write code, I can make a decision then, but for now I don't feel the need to adopt agentic workflows and I think the people who don't will be better cognitively positioned in the future.

This is a complete fantasy. If LLM's got to this point of sophistication there would be a total revolution in almost every industry. Society would be radically different. Since LLM's are nowhere near this, I'm not so sure we even have Pandora's box, let alone opened it.

Government adjacent feels directly relevant considering the government is a de facto monopoly.

Ok but you didn't ask any questions in the transcript you provided. Maybe that one was an outlier?

In order to learn you generally need to actually do the thing, and usually multiple times. My point is that it's easy to use an AI to shortcut that part, with a healthy dose of sycophancy to make you feel like you learned so well.

It's all talk and no evidence.

Mmm, I do a lot of frontend work but I find writing the frontend code myself is faster. That seems to be mostly what everyone says it's good for. I find it useful for other stuff like writing mini scripts, figuring out arguments for command line tools, reviewing code, generating dumb boilerplate code, etc. Just not for actually writing code.

Can't believe this car bubble has lasted so long. It's gonna pop any decade now!

With all due respect you were reading, not learning. It's like when people watch educational YouTube videos as entertainment, it feels like they're learning but they aren't.

It's fine to use the LLMs in the same way that people watch science YouTube content, but maybe don't frame it like it's for learning. It can be great entertainment tho.

Perhaps it is a skill issue. But I don't really see the point of trying when it seems like the gains are marginal. If agent workflows really do start offering 2x+ level improvements then perhaps I'll switch over, in the meantime I won't have to suffer mental degradation from constant LLM usage.

Yeah if only Google shipped more crap software that they then go onto cancel, their software would be so much better!!!!!

Calling it now: AI withdrawal will become a documented disorder.

What's the link?

I would never suggest that only I know better. Plenty of other people are observing the same thing, and there is also research backing it up.

Maybe shocked is the wrong term. Surprised, perhaps.

That sounds reasonable to me. AI is best at generating super basic and common code, it will have plenty of training on game templates and simple games.

Obviously you cannot generalize that to all software development though.

> Numbers don't matter

Yes that's already been well established.

No but I don't use it to generate code usually.

I gave agents a solid go and I didn't feel more productive, just became more stupid.

Even 2.5x is absurd. If they said 1.5x I might believe them.

Yes and yes.

Surely searching "centre a div" takes less time than prompting and waiting for a response...

> Even with refinement and back-and-forth prompting, I’m easily 10x more productive

Developers notoriously overestimate the productivity gains of AI, especially because it's akin to gambling every time you make a prompt, hoping for the AI's output to work.

I'd be shocked if the developer wasn't actually less productive.

How are you using AI to learn? I see a lot of people say this but simply reading AI generated overviews or asking it questions isn't really learning.