Context Engineering
Managing inputs, memory, history compression, and Claude skills integration.
Context Engineering: Memory & History
advanced~8hLearn context assembly, the 6 types of contexts for AI agents, memory hierarchies, token compression, and context engineering workflows.
Conversational Memory
intermediate~3hTechniques for persisting context across multiple conversation turns in LLM chat applications: full buffer, windowed buffer, summary memory, and entity memory — and how to choose between them given context window constraints and conversation length.
Context Engineering for Agents: The 6 Types of Context
intermediate~4hThe CPU/RAM mental model for context engineering, the 4 fundamental stages (Write, Read, Compress, Isolate), and the 6 types of context every production agent needs (Instructions, Examples, Knowledge, Memory, Tools, Tool Results).
Build a Multi-Source Context Engineering Workflow [Hands-On]
advanced~6hA full hands-on build of a multi-agent research assistant gathering context from documents, memory, web search, and arXiv — using Tensorlake, Zep, Firecrawl, Milvus, and CrewAI, deployed as a Streamlit app with citations.
Context Engineering in Claude Skills
intermediate~3hAnthropic's Claude Skills mechanism — a 3-layer context system that lets an agent use hundreds of specialized workflows without overloading its context window.
Manual RAG vs. Agentic Context Retrieval: Building for Multi-Source Enterprise Data
advanced~4hWhy naive 'embed it and RAG it' fails for real multi-source enterprise data, and the 3-layer Ingestion/Retrieval/Generation architecture (grounded in the open-source Airweave framework) needed to actually solve it.