Core Concepts
Understanding the fundamental principles that power ODIN.
Context engineering is about providing AI models with precisely the right information at the right time. Unlike simple prompt engineering, it considers the entire information architecture around your AI interactions.
ODIN uses a templating system that allows you to create standardized prompts with variable placeholders. This ensures consistency across your team and makes it easy to iterate on prompt strategies.
Every AI model has a limited context window. ODIN helps you manage this constraint by intelligently selecting and prioritizing the most relevant information for each interaction.
Rather than arbitrary splits, ODIN uses semantic analysis to chunk your content at natural boundaries, preserving meaning and improving AI comprehension.
ODIN implements a multi-layered memory system that mimics human cognition, allowing AI to maintain context across sessions and learn from past interactions.
RAG combines the power of large language models with your specific knowledge base, ensuring responses are accurate and relevant to your domain.