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title: Instruction Drift Simulator
emoji: 😻
colorFrom: gray
colorTo: green
sdk: gradio
sdk_version: 6.3.0
app_file: app.py
pinned: false
license: mit
short_description: Instruction Drift Simulator
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
## 👩💻 Author
**Aditi Khare — AI Product & Research Leader**
Writing on AI research, product thinking, and system architecture
🌐 **Website:** [aditikhare.com](https://aditikhare.com)
🔗 **GitHub Repository:** [Instruction Drift Simulator](https://github.com/aditikhare007/Instruction-Drift-Simulator/)
🤗 **Live Demo:** [View on Hugging Face](https://huggingface.co/spaces/AditiShashiKhare/instruction-drift-simulator)
💼 **LinkedIn:** [Aditi Khare](https://www.linkedin.com/in/aditikhare)
---
# 🧠 Instruction Drift Simulator
The **Instruction Drift Simulator** demonstrates how model behavior can **systematically drift away from original instructions** as prompts evolve, context accumulates, or constraints weaken over time.
This Space is a **controlled evaluation environment** designed to make instruction drift **visible, measurable, and comparable**—not to correct or optimize prompts.
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## What This Demo Shows
- How initial instructions degrade across multi-step interactions
- How ambiguity, overload, or soft constraints introduce drift
- How behavior changes without any change in model weights
- How instruction adherence weakens over time
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## Evaluation Focus
The simulator evaluates behavior step-by-step across:
- **Instruction adherence**
- **Constraint leakage**
- **Semantic deviation**
- **Accumulated ambiguity**
- **Termination correctness**
Drift is surfaced **explicitly**, not inferred.
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## What This Is
- A **behavioral evaluation demo**
- A **controlled instruction-drift simulation environment**
- A **non-autonomous, non-agentic system**
- A **diagnostic tool for GenAI reliability**
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## What This Is Not
- A chatbot
- A prompt optimization tool
- A RAG system
- An autonomous agent
- A mitigation or correction engine
This simulator **does not fix drift**—it exposes it.
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## Why This Matters
Instruction drift is a major source of:
- Silent failures in agentic systems
- Policy non-compliance
- Evaluation blind spots
- Misleading benchmark performance
This demo treats **instruction fidelity as a first-class evaluation signal**.
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## License
© 2026 **Aditi Khare**. All rights reserved.
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