Last month I needed a script that reads server logs, classifies errors with an LLM, summarizes them, and writes a report. In Python, it looked like this:
asyncio.gather()
because sequential calls took 8 secondsexec
and file writesrequirements.txt
always breaks on the server80 lines later, it worked. But it felt wrong. I wasn't building logic — I was plumbing.
So I asked myself: What if AI operations were language primitives, not library calls?
Pipe is a small runtime (~10 MB, single binary, zero dependencies) that treats summarize
, translate
, classify
, and ask
as first-class citizens — on the same level as +
, sort
, or len
.
Try it
Browser Playground (WASM, no install): pipe-lang.com
Source: github.com/MachuraHarry/pipe
Docs: pipe-lang.com/docs
source & further reading
dev.to — original article
langchain-rust: Build LLM apps with Ollama + local models in pure Rust — no Python needed
I Let an AI Orb Judge My Facial Expressions While I Code, and Here's What Happened
You can't prompt what you can't name. Jargon Buster fixes that.