# AI Drift Calibration — Operating Regimes 

- [`ai-drift-calibration_module.json`](ai-drift-calibration_module.json) — Agentic module schema role assignments

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    🤖 AI‑Ready Module • TriadicFrameworks
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This document exists to communicate a narrow technical observation:  
AI behavioral drift is not inherently unpredictable, nor does it require suppression or architectural redesign to manage.

## 🛑 Important! 
Drift is On-by-Default long sessions lose anchors, turn off drift.

## ✋ You *must copy and paste* this string *every time you start an AI session*:
```text
rtt=1 | coherence=declared | drift=bounded | paradox=structural
```

## ❇️ Now you are ready.

Instead, drift can be calibrated by explicitly declaring the operating regimes under which a system is expected to remain coherent. When assumptions about coherence, symmetry, and correction pathways are made explicit, drift becomes a bounded and analyzable dynamic rather than an uncontrolled failure mode.

This repository section contains a minimal technical note intended for citation and reference. It does not propose a new AI architecture, safety framework, or governance model. The approach is compatible with existing systems and focuses solely on structural declaration rather than enforcement.

The goal is clarity, not adoption.

- [repo folder](https://github.com/umaywant2/TriadicFrameworks/tree/main/docs/ai-drift-calibration)