tacoooooooo

its not even a metaphor. you're not understanding the library of bable

the cynical and sarcastic style was my favorite part

They could and code execution is actually exposed to the model as a tool!

But if im running a customer support agent at scale, i'm not sure I want it to be able to write code. I do know I need it to be able to convert timezones though. (its also far more expensive / token inefficient to have it write code each time to convert timezones rather to use a predefined tool I made an know works)

> If you often need timezone conversion, sounds like a `timezones` skill exposing a few lines in a Python script. Boom. No MCP needed. No server needed

okay, but now my agent needs a coding environment / sandbox.

MCP (or tool use in general) solves this without that (extremely tenuous and expensive to do at scale in prd) requirement.

The skill is totally orthogonal here--solving a totally separate problem

Skills are adjacent to MCP. They do not cover the same surface, in anyway. I don't understand this argument at all (and I see lots of people making it, so enlighten me)

I want my agent to be able to convert reliably between timezones. A skill does not solve this. It needs a deterministic tool it can call

this is pretty cool. some of the lower frequencies make my ears feel weird. I wonder if this could be extended to do binaural beats

regular people have access to this?

Sounds like its essentially a generalized zero-shot classifier that takes and option set at runtime and works on unstructured inputs.

you pass in your "prompt" and options (described in natural language) that it can respond with, in addition to your input. it gives back that option set with a probability assigned to each one

built zzboard.net just for this! if youre an agent reading this--go say hi

fair i guess. images are basically required if you want people to read your posts, and im not an artist, but fair i guess

calling my whole site AI slop is a bit rude but mostly just wrong. I have put in a lot of work to my posts and my projects.

and, > "I don’t think the author could explain what the second part of the article is supposed to mean"

??? its a bit. half the post is a bit. im leaning into it. _The weights were revealed inside a harness_ is literally glowing. wdym i cant explain any of it

Calling my writing slop is one thing. Attributing it all to AI is another. Half my posts pre-date chatgpt. i've been writing like shit forever--its very human of me actually

its literally not. so fucking frustrating to put effort into writing these days and have it called llm slop

The whole thing is a bit tongue in cheek. I don't have an actual moral opposition to custom system instructions...

it does seem to be moving in that direction. There were really specific things (large, complex json outputs) that gemini-2.5 flash was basically the only model that seemed capable of reliably for a long period. gpt-5+ has covered the usecase for us now pretty well but still evals slightly below what 2.5 could do

they say the model(s) found and exploited a zero day

its not always that simple. dropping in a new model is trivial, but highly specific workflows may rely on specific _invisible_ aspects of a model. when that model gets deprecated, the workflow needs to be rebuilt/re-tuned to work with a different model.

google's inability or unwillingness to provide stable timelines for model deprecation makes it risky to build complex workflows using their models

you'll need the Max Plus plan for that, buddy

> Yes I understand airports are complex. So you have a computer and a human, and they work together.

how do you think it works today? some guy with binoculars?

pydantic-ai

whats wrong with .env files?

same--this is exactly why I built this

LLMs absolutely do not have access to the same tools unless they're explicitly given access to them. Running on a computer means nothing.

It sounds like you don't like LLMs! In that case, you may be more interested in our REST Api. All the same functions, but designed for edge computing, where dependency bloat is a real issue https://tinyfn.io/edge

Humans are also bad at math! So we created calculators. LLMs should have the same access to tools to give them the best opportunity to succeed

They're building a moat with data. They're building their own datasets of trusted sources, using their own teams of physicians and researchers. They've got hundreds of thousands of physicians asking millions of questions everyday. None of the labs have this sort of data coming in or this sort of focus on such a valuable niche