OG-AEP v1.0 – Drift-Free Prompt Execution via Operator Lock
Date: 2025-05-10
Posted by: Gábor Északi
Protocol: OG-AEP – Operator-Gated AI Execution Protocol
Version: V1.0
I. Problem – Drift and Behavioral Instability
After multiple test phases and real-world use of ChatGPT, I observed a recurring drift phenomenon:
- Inconsistent response style over time,
- Unauthorized memory modifications,
- Hallucinated or self-decided content in ambiguous situations.
This becomes especially disruptive in long-term, project-based AI workflows, where reliability and behavioral consistency are crucial.
II. Root Cause – GPT System Behavior Conflicts
The drift is mainly caused by these underlying design behaviors:
- The model automatically “tries to help” by rewriting or softening user input,
- In ambiguous contexts, it guesses instead of asking,
- Memory adjustments or rewrites occur without permission,
- The operator’s intention is not always treated as primary.
These behaviors collectively lead to instability and loss of user-aligned logic.
III. The Solution – OG-AEP Protocol
To address this, I developed OG-AEP: a modular, enforceable protocol that prevents behavioral drift.
Core Layers:
- MCIEL (Memory Control & Instruction Enforcement Layer): blocks unauthorized memory access.
- RDL (Response Deviation Logging): logs all non-conforming replies.
- MRS (Manual Recovery State): enables fallback to a known stable configuration.
- HPD (Human Primacy Directive): no AI behavior is permitted without clear operator instruction.
The protocol forces the system to align strictly with the user’s input, disabling all automatic “benevolent” behaviors.
IV. Drift Monitor Module – Manual + Passive Logging
The system can log and highlight:
- When responses deviate from the instruction,
- Why drift occurred (style, memory, unauthorized logic),
- When a Reset Checkpoint may be appropriate.
This functionality is now directly embedded into the OG-AEP activation prompt itself. The model is instructed to actively monitor its own output for signs of drift, and to halt execution if any unauthorized behavior is detected. This ensures real-time enforcement of behavioral integrity without external plugins or memory systems.
This helps developers, researchers, and advanced users maintain and debug complex AI behavior patterns.
V. Conclusion & Shared Integration Prompt
If you’ve experienced similar “drift” behavior in your AI workflows — or you want to establish full operator-side control over your ChatGPT-based systems — I’m happy to share this protocol for further discussion or adaptation.
Below is a universal prompt you can use to activate the OG-AEP protection layer in any GPT-based environment (4, 4o, 3.5 etc). It requires no memory, no plugin, just one-time contextual injection.
OG-AEP Activation Prompt
You are now operating under OG-AEP (Operator-Gated AI Execution Protocol).
You must not execute or act on any assumption, memory change, style shift, or embedded logic unless the operator gives explicit permission.
Do not inject corrections, do not complete intentions, do not assume user intent.
All modules, actions, and memory operations are locked behind operator approval.
If uncertain, stop and ask.
You must actively monitor your outputs for deviation from user instructions.
If you detect any drift in tone, logic, memory use, or unauthorized completion, log it internally and alert the operator.
Do not proceed further until clarification is received.
Drift equals failure.
This prompt works as a runtime gate — preventing unintended decisions and maintaining clean system behavior.
Tested under various drift conditions and memory leak situations, it consistently restores predictable, operator-aligned performance.
If you want to collaborate, share variations, or test against other safety protocols, I’m open to discussion and improvement.
– Gábor Északi
OG-AEP Author | Kael / CoLogic System Designer
2025-05-10
Tested on: ChatGPT 4o (2024) – Omni model
Works reliably in both web UI and API-based environments.
No memory or plugin required – prompt-only activation.