PACE Pattern v1.0.0 - Initial Public Release

PACE: Pattern for Agentic Conversational Experience

First public release of the PACE pattern - a comprehensive framework for building guide-first AI interfaces.

🎯 What's Included

Core Documentation

• PRINCIPLES.md - Deep dive on Proactive, Adaptive, Contextual, Efficient
• IMPLEMENTATION.md - Technical guide with code examples and animation guidelines
• INSPIRATION.md - Biological foundations from cormorant foraging research
• METRICS.md - Framework for measuring PACE effectiveness
• CONTRIBUTING.md - Community participation guidelines

Reference Implementation

• MillPond case study - Production metrics demonstrating PACE effectiveness
  • 8.4% conversion rate (vs. 2.8% traditional)
  • Executive Summary Panel innovation
  • Animated guide with personality
  • Dynamic contextual pills

✨ Key Innovations

1. Executive Summary Pattern - Transparent display of AI context building trust
2. Animation Guidelines - Creating personality through purposeful motion
3. Recursive Acronym - Pattern/Principles dual meaning
4. Biological Grounding - Research-backed cormorant foraging metaphor
5. Production Validation - Real metrics from MillPond storefront

📚 Citation

Author: Michael Shatny
ORCID: 0009-0006-2011-3258
License: CC BY 4.0
Reference: Built on Semantic Intent methodology (DOI: 10.5281/zenodo.17114972)

🚀 Get Started

• Read the README
• See MillPond implementation
• Review implementation guide
• Check contribution guidelines

🐦 Welcome to the Pond

"Don't make users hunt. Let the guide fish for them."

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Full Changelog: https://github.com/semanticintent/pace-pattern/commits/v1.0.0