Prompt Hardening Standard.

"To scale AI infrastructure, we must treat the prompt not as a request, but as an engineered circuit."

# Abstract

Prompt Hardening is a technical framework designed to transform non-deterministic natural language prompts into structural, deterministic logic processors. This RFC specifies the standards for schema enforcement, hallucination gating, and context compression within agentic AI systems.

# Terminology

Determinisitc Node (DN): An AI execution point with fixed schema output. Hallucination Gate (HG): A recursive validation loop. Surgical Schema: A JSON-strict structural definition.

# Specification

Systems MUST enforce output schemas via structural markers. Systems SHOULD implement recursive self-audit cycles. Systems MAY prune redundant semantic tokens for latency optimization.

# Implementation Kit

SURGICAL_CONFIG.json

{
  "version": "1.2.4",
  "protocol": "PH-S01",
  "enforcement": {
    "strict_schema": true,
    "hallucination_gate": "RECURSIVE_VALIDATION",
    "validation_nodes": 3,
    "retry_logic": "EXPONENTIAL_BACKOFF"
  },
  "markers": {
    "intent_start": "[[SURGICAL_INTENT]]",
    "logic_end": "[[SURGICAL_FINALIZE]]"
  }
}

Starter Template

A pre-configured system prompt template with structural markers and logical boundaries.

Reference App

A Python-based implementation of RFC-001 for automated schema validation.

# Security Considerations

Advisory

Improper schema enforcement can lead to injection vulnerabilities where malformed AI outputs are executed by downstream systems. Always implement a secondary validation gate.

Cite This Specification

@techreport{sable2026rfc001,
  author = {Sable, Datta},
  title = {RFC-001: Prompt Hardening Standard v1.2.4},
  institution = {Surgical AI Workspace},
  year = {2026},
  url = {https://dattasable.com/knowledge/rfc/001-prompt-hardening}
}