External Knowledge
External knowledge refers to information and context sourced from materials outside of an AI system’s training data. This encompasses documents, databases, APIs, and other external sources that augment an AI agent’s capabilities at runtime. By incorporating external knowledge, AI agents can access up-to-date information, domain-specific data, and proprietary materials that would otherwise be unavailable or outdated within static training datasets.
Implementation in AI Agents
AI agents access external knowledge through various mechanisms, commonly including retrieval-augmented generation (RAG), vector databases, and API integrations. Frameworks like LangChain provide structured approaches to context engineering, allowing developers to retrieve and format external information for use in agent decision-making.
Documentation as Context
Effective context engineering often requires structured documentation of the codebase or environment the agent operates within. Tools like OpenWiki: Automated Open-Source CLI for AI Agent Documentation facilitate this by:
- Automating the generation and maintenance of documentation for codebases via an open-source CLI.
- Tailoring output specifically for AI agents to improve their understanding of repository structure and logic.
- Reducing manual overhead in keeping agent context sources up-to-date with code changes.