Master AI+ Context Engineering for Production-Grade AI Systems
Description
About This Course
Context Strategy & Architecture:Learn how to design robust context architectures that go beyond prompts—managing instructions, memory, tools, and knowledge for reliable AI behavior across sessions and workflows.
Building Context-Aware AI Systems:Gain hands-on skills in implementing context pipelines, RAG architecture, and memory systems that ensure grounded, accurate, and cost-efficient AI outputs.
Context Management & Optimization:Master the Write-Select-Compress-Isolate (W-S-C-I) framework to control relevance, reduce hallucinations, optimize token usage, and scale AI systems effectively.
Enterprise-Grade Context Integration:Learn how to integrate AI safely into enterprise environments with role-based access, compliance guardrails, secure memory, and conflict-free context orchestration.
Future-Ready Agent & Workflow Design:Prepare for the next wave of AI by designing multi-agent systems, automated workflows, and context-driven architectures that remain reliable as models, tools, and scale evolve.
Course Modules
Module 1: Foundations of Context Engineering – Introduction
1.1 What is Context Engineering (Beyond Prompt Engineering)
1.2 From Prompting to Context Pipelines: The 2025 Paradigm Shift
1.3 The Four Building Blocks of Context: Instructions, Knowledge, Tools, State
1.4 Short-Term vs Long-Term Memory in LLM Systems
1.5 Benefits of Context Engineering: Grounding, Relevance, Continuity, Cost Control
1.6 Use Case: Context-Aware AI Travel Assistant
1.7 Hands-on: Designing System Instructions and Memory State for a Role-Based AI Agent
