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Agent Braille – 8-bit state encoding for LLM agents, ~92% fewer tokens than JSON

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Agent Braille – 8-bit state encoding for LLM agents, ~92% fewer tokens than JSON
⚡ TL;DR · AI summary

Agent Braille (AB-1) is a new protocol designed for efficient machine-to-machine communication of AI agent states. It uses an 8-bit encoding system that significantly reduces the number of tokens required compared to traditional formats like JSON. The project emphasizes transparency, with a focus on testing and fixing failures to ensure credibility.

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Opening excerpt (first ~120 words) tap to expand

Agent Braille (AB-1) A measured agent-state protocol. Every claim here was tested, including the ones that failed; the failures and the fixes are in the open. AB-1 is a deterministic 8-bit semiotic layer over the Unicode Braille Patterns block (U+2800–U+28FF) for machine-to-machine communication of AI agent state. One code point encodes one machine state across eight orthogonal dimensions of agency. This repository is the reference implementation, the benchmark harness, and the honest evidence ledger behind the paper. The code is the canonical specification. Where the prose and the code disagree, the code wins. What survives measurement (and what didn't) This project's credibility is the arc, not a list of wins: Atomicity — claimed, falsified, fixed with receipts.

Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.

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