This is cool, let aside the token usage, perhaps it can help analyze tcp throughput by redirect wire shark/to dump result

How quickly claude responds when it acts like a user space LLM chatbot?

>Fun? Oh yeah!

I think this author and I have different definitions of fun.

Modulo Anthropic messing with the model for load mitigation, I wonder how stable this result is.

1,000 pings, how many correctly ponged?

think about how much faster it would've been with a small local model!

That's why LLM will eventually be used only for initial interaction between the user in their language, to prepare the data to a specialized model.

Imagine face recognition to work like a text chat, where the PC gets the frame from the camera and writes in the chat: "Who's that? Here's the RGB888 image in hex: ...".

Now do the equivalent of just in time compilation. Claude sees that we need to respond to a lot of pings and writes a program to compute it instead of thinking about each one.

Wouldn't this be faster with an agent skill that has code?

/skill-creator [or /create-skill] Write an agent skill with code script(s) that use an existing user space IP library that works with your agent runtime, to [...]

ComposioHQ/awesome-claude-skills: https://github.com/ComposioHQ/awesome-claude-skills

anthopics/skills//skill-creator/SKILL.md: https://github.com/anthropics/skills/blob/main/skills/skill-...

/.agents/skills/skill-name/SKILL.md, scripts/{script_name.py,__init__.py}

https://agentskills.io/what-are-skills

Next up: Claude replacement to handle simdjson processing.

Perhaps one day, all network services will be provided by LLMs natively. Truly, that would be a day in the future.