Andrew Yourtchenko

I think it’s a skull issue. The little monkey of conscious can focus only on one thing at a time, and sometimes a competing stimulus means that the action is finished on autopilot which puts it into entirely different box, inaccessible to the monkey.

I wonder if a Harvard architecture LLM could be a thing.

Finally, fully automated foss drama

Wait until they hear about dihydrogen monoxide!

Totally! Having been in that position myself (with someone having moved my things behind me without telling), I tell on myself proactively and profusely apologize to them for changing stuff every time this happens and describe why and what has been done. Generally works!

implementable: At 250, start with 1ms delay before the next character shows up and double it with each additional character.

I had a fair few of my ex-colleagues friends at Cisco drop their jaws this week at CiscoLive, when I told them what I see on Bsky and showed some screenshots and GitHub repos 😂

I see the game theory on this one to be the same as behind saying “please“ and not swearing at the machines when asking to do things: if the supposed claim is wrong, nothing big happens. But if it is right, a fair bit of suffering is averted.

I posted a wrong link at first, sorry !

claude.ai/share/4d969f... - I can see this one in a a preview, so should hopefully be accessible.

Oh does it ask you to have the pro ? It is supposed to be “anyone with the link”.

Claude Talk with Claude, an AI assistant from Anthropic

Sure, it was Opus 4.6 - claude.ai/chat/06f52e6...

This is my Claude conversation: claude.ai/share/4d969f...

The literary attempt was inspired by this thread :-) I experimented with the technique I had seen somewhere recently related to jokes, namely “generate 5 options and pick the less likely one“. in my case I asked for the most surprising, and added a few other tweaks.

I will never get tired of my favorite traffic-calming device.

I had Claude Opus 4.6 write a short story. It was kinda fun to read, so thought to drop it here and have the internets rip it apart. :) stdio.be/blog/2026-02...

(Also: I guess ChatGPT *may* have the same problem based on what I had read in www.off-policy.com/alignment-is... ?)

many things are still pretty buggy, but it’s a pretty light and “close to the metal” harness, so I find it using more often these days.

Wonder if it is due to alignment being a separate activity from the main training ?(thus chatgpt should be also vulnerable ?) btw, I grabbed metacog to add to the ape (behind a feature switch, as I think it’s a much sharper razor than a non-sandboxed pty) - in case you find it useful.

By the looks of it, seems like it’s a pretty deep surgery that is required to address that ? and - I guess anthropic models do not have this problem ?

Qwen-coder-next gets a lot more use.

T-shirt for cyclists with, written on the back:

I wouldn’t be in your way
If I had an unobstructed bike lane
To ride in

This is metric billions, they are several times larger, so it all makes sense.

it is already possible, right now, to get 100tok/sec out of 100 watts of air-cooled local inference, and the output is surprisingly good

LLM architecture gains will compound against improved silicon over the next five years to produce serious leverage, WHICH WORKERS CAN OWN OUTRIGHT

maybe give a go to github.com/antirez/flux... - you can do the same with the original, but I find C easier than installing tons of python packages :-)

Beyond agentic coding AI dev tooling can do better than chat interfaces

We should think outside of the chat box when designing AI-assisted software development workflows:

haskellforall.com/2026/02/beyo...

"Are we there yet?"

Even worse when humans do that.

The low pass rate on the simple tasks is a bit odd, I will need to have a look at that - wonder if others might see the same results.

GitHub - ayourtch-llm/kindness: A study of when do the LLMs perform better A study of when do the LLMs perform better. Contribute to ayourtch-llm/kindness development by creating an account on GitHub.

...the personable instructions give a clear advantage, at least with GLM-4.6-flash.

Obviously this is a sample of one - so - if you have the access to the APIs with models to play with - give a go to the github.com/ayourtch-llm... - and let's see how this all pans out!