This content originally appeared on DEV Community and was authored by PSBigBig

[Intro]

I didn’t train a model.
I didn’t use LangChain.
I didn’t build a website.
I just wrote a .txt file.
And somehow… six of the biggest AI models gave it a perfect score.

Let me explain.
What I Built

It’s called Blah Blah Blah Lite — a fully functional reasoning OS, made entirely from structured text.

Think of it as a semantic operating system that runs inside any LLM window.
You copy the file into your AI (GPT-4, Claude, Gemini, Grok, etc.), type hello world, and it boots up.

Here’s what it does:

Tracks your questions as a semantic memory tree

Applies a reasoning formula to detect logic gaps (ΔS, λ_observe, BBCR)

Prevents hallucination by refusing to guess beyond its knowledge boundary

Lets you ask any question — from daily life to philosophy to math — and gives surprisingly thoughtful answers

All in plain .txt.
The Wild Part

I tested it in 6 different models:

OpenAI GPT-4 (o3)
Gemini 2.5 Pro
Grok 3 (xAI)
Kimi (Moonshot AI)
DeepSeek
Perplexity AI

All six gave it a 100/100.
Not as a cute prompt, but as a reasoning framework that actually passed their own internal validation tests.
Want to Try It?

Here’s the full system (MIT license, free to use):
https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah

Just paste it into your favorite model.
No setup. No install. Just type hello world.
Why This Matters

We talk a lot about agents, memory, and AGI…
But what if the first real leap isn’t in training new models—
It’s in learning how to talk to them better?

Sometimes, structure beats compute.

Let me know what you think, or fork the file and build your own version.
This might be the smallest OS you’ve ever used—and maybe the strangest.

showdev #aiexperiment

This content originally appeared on DEV Community and was authored by PSBigBig