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I had a bunch of fun writing about this one, mainly because it was a great excuse to highlight the excellent news about Kākāpō breeding season this year.

(I'm not just about pelicans.)





Awww. If there weren’t only 237 of them, I would want to bring one of them home.

> Kākāpō can be up to 64 cm (25 in) long. They have a combination of unique traits among parrots: finely blotched yellow-green plumage, a distinct facial disc, owl-style forward-facing eyes with surrounding discs of specially-textured feathers, a large grey beak, short legs, large blue feet, relatively short wings and a short tail. It is the world's only flightless parrot, the world's heaviest parrot, and also is nocturnal, herbivorous, visibly sexually dimorphic in body size, has a low basal metabolic rate, and does not have male parental care. It is the only parrot to have a polygynous lek breeding system. It is also possibly one of the world's longest-living birds, with a reported lifespan of up to 100 years.

https://en.wikipedia.org/wiki/K%C4%81k%C4%81p%C5%8D


And so the Kākāpō Benchmark was born

and this is my excuse to talk about the :partyparrot: emoji being from an actual real life documentary https://www.youtube.com/watch?v=9T1vfsHYiKY&pp=ygUSa2FrYXBvI...

TIL about a large moss green flightless parrot :)

I'm impressed you have never encountered :partyparrot: in your work Slack.

They're also nocturnal!

Will Kākāpō be riding bicycles soon?

They already ride British nature photographers—what do they need bikes for?

https://youtube.com/watch?v=Jlk9u8MIv7o

The foreplay starts around the 1 minute mark.


as an svg you mean? cause nano banana rides circles around the pelicans

> Skills are a keeper #

Good thinking, I agree actually, however..

> Skills are based on a very light specification, if you could even call it that, but I still think it would be good for these to be formally documented somewhere.

Like a lot of posts around AI, and I hope OP can speak to it, surely you can agree that while when used for a good cool idea, it can also be used for the inverse and probably to more detrimental reason. Why would they document an unmanageable feature that may be consumed.

Shareholder value might not go up if they learnt that the major product is learning bad things.

Have you or would you try this on a local LLM instead ?


These work well with local LLMs that are powerful enough to run a coding agent environment with a decent amount of context over longer loops.

The OpenAI GPT OSS models can drive Codex CLI, so they should be able to do this.

I have high hopes for Mistral's Devstral 2 but I've not run that locally yet.


> These work well with local LLMs that are powerful enough to run a coding agent environment with a decent amount of context over longer loops.

That's actually super interesting, maybe something I'll try investigate and find the minimum requirements because as cool as they seem, personalized 'skills' might be a more useful use of AI overall.

Nice article, and thanks for answering.

Edit: My thinking is consumer grade could be good enough to run this soon.


Something that powerful requires some rewriting of the house.

Local LLMs are better for long batch jobs not things you want immediately or your flow gets killed.




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