GP is saying it’s not a very good one.

Everyone in AI used to know this.

It’s a joke. Mt. Scenery is in the Caribbean, part of the Netherlands but not in the flat mainland.

TIL!

Or you know, just better performance for people that know how to use their tool of choice.

Wouldn't such people just pass in

  maintain_order=False

?

That’s an API design question. What is the more common use case.

You seem to suggest they did it for benchmarking reasons only. They could use the option there themselves without changing the default so that is unlikely to be the motivation.

You want to solve a family of problems using some tool. You measure the relevant solutions performance metrics.

Now, you or someone else vibe-coded a new tool. You created new solutions and measure again.

You have just quantified the result of using the new tool.

How do you measure them if you don't understand what you're doing? A shitty benchmark or small test suite is not how solid software gets made.

You measure results, you benchmark what you care about. It works often enough to be useful

Good, you achieved a 10% speedup for a particular workload that some users said they care about. But how do you find out that was really the feature that should have been built next? How do you prevent adding badly factored code? How to make sure you don't pile on top of existing tech debt in the codebase, that you are solving the most fundamental issues first?

> some users said they care about

But how could they possibly know what they should care about if they don't understand the code?

> how do you find out that was really the feature that should have been built next?

Phew right they don't know. Only the devs understand what software should do.

I actually explained well enough why this requires to a large degree a competent developer to judge.

I think a sufficiently smart non-competent developer can still do this to great effect, but it definitely helps if someone is both a competent developer, smart, and a seasoned user of LLMs.

Just because AI is not yet a god that is better than all humans at creativity and product decisions and design does not mean it is not a huge accelerant right now.

I'm working on my typed, fast data frame language Ibex: https://github.com/bobjansen/Ibex

It is usable stand alone but also through an R package:

https://bobjansen.net/faster-than-data-table-introducing-ibe...

It performs better than data.table in my benchmarking on a wide array of tasks and is competitive with Polars on low core counts.

Then you need to read the original. A translator is a product of their time.

Indeed, and this Qwen 3.8 max specific page:

https://artificialanalysis.ai/models/qwen3-8-max

Doesn't have the claim either. Clickbait?

This page has it, scroll to "Intelligence" header (not the highlights one, but second on the page / with black square) and click "Agentic Index"

So the original link should be: https://artificialanalysis.ai/models/qwen3-8-max?intelligenc...

Even then, this seems a much more marginal win than the headline suggested to me.

I went to VB.NET first using a previous generation of LLM's (that was quite manual back then) and then from VB.NET to C# or just keeping the VB.NET around worked very well. The code was not highly complex but more than just CRUD. The porting from VB6 to VB.NET included building tests which helped.

I have solo built this:

https://github.com/bobjansen/Ibex

Ibex is a usable DSL for table manipulation that is quite fast

https://bobjansen.github.io/Ibex/benchmarks.html

I'm still managing to add more features, such as multithreading. The LLM's do make mistakes but they have gotten better and they tend to self correct these days. I'm also comparing results to mature products such as Polars and DuckDB and the results match.

how many users do you have?

Zero. I don’t think that implies the product is bad though. I haven’t marketed it much yet and I’m not great at it either. Even if it is marketed well, integrating the tool into existing workflows would take some effort. This has nothing to do with the suitability of LLMs though.

you replied to a comment asking what you've successfully launched. it sounds like the answer is "nothing"