Context Engineering — Optimize LLM Context Windows for Speed & Cost

Master context engineering to optimize LLM token usage, slash API costs by 40-60%, and build production-grade RAG systems. Hands-on course with 45 lessons, quizzes, and real-world projects.

Core concepts: High — growing rapidly. Covers history, terminology, and why context engineering matters more than model size.

Deep dive into tokenization, context window architectures (sliding vs static), attention mechanisms, and positional encoding. Practical token budgeting.

Prompt compression, KV cache optimization, context chunking, structured context (XML/JSON/schema), dynamic context allocation. Hands-on implementation.

chunk size strategies, overlap tuning, multi-turn memory management, building RAG pipelines. Real production patterns from leading frameworks.

Monitoring context usage, CI/CD for context configs, building context microservices, error handling, cost optimization ($ per token).

Hybrid context windows, cross-attention sharing, context distillation, multimodal context (text+image+audio), real-time adaptive prompting.

Design, build, test, and deploy a complete context-engineered LLM application. Portfolio-ready project showcasing all techniques.

Context Engineering — Optimize LLM Context Windows for Speed & Cost

Course Curriculum

Module 1: Foundations of Context Engineering6 lessons

Module 1: Foundations of Context Engineering

What is Context Engineering? — The Memory Problem

How LLMs Actually See Your Text (Tokenization)

The Context Window: Size, Limits, and Trade-offs

Why Context Matters More Than Model Size

Real-World Analogy: The Tiny Desk

Setting Up Your First Context-Optimized Prompt

Module 2: Token Economics & Context Windows7 lessons

Module 2: Token Economics & Context Windows

Token Economics 101: Counting Tokens Like Money

Context Window Architectures: Sliding vs Static

Understanding Attention Mechanisms

Positional Encoding: How AI Knows What Comes First

Context Fragmentation: The Hidden Performance Killer

Benchmarking Your Context Usage

Token Budget Planning Across a Session

Module 3: Core Context Engineering Techniques8 lessons

Module 3: Core Context Engineering Techniques

Prompt Compression Techniques: The TL;DR for AI

Sliding Window Attention: Seeing Only What Matters

KV Cache Optimization: Speeding Up Repeated Calls

Context Chunking Strategies for Long Documents

Structured Context: XML, JSON, and Schema-Based Approaches

Dynamic Context Allocation: Paying Attention to What Counts

Implementing Compression in Production

Benchmarking Different Compression Strategies

Module 4: RAG & Retrieval-Augmented Context7 lessons

Module 4: RAG & Retrieval-Augmented Context

Building a Context-Aware Chat Application

RAG Chunk Strategies: Size, Overlap, and Retrieval

Handling Multi-Turn Conversations Without Blowing the Budget

Context Budgeting: Planning Token Usage Across a Session

Error Handling: When Context Gets Truncated

Monitoring and Logging Context Usage

Project: Build a Context-Optimized Q&A Bot

Module 5: Production Context Management6 lessons

Module 5: Production Context Management

Frameworks for Context Management (LangChain, LlamaIndex)

Integrating Context Optimization into Existing Pipelines

Building a Context Engineering Microservice

Testing and Validating Context Strategies

CI/CD for Context Configurations

Cost Optimization: Reducing API Bills Through Context Engineering

Module 6: Advanced & Emerging Techniques7 lessons

Module 6: Advanced & Emerging Techniques

Hybrid Context Windows: Combining Short and Long Memory

Cross-Attention Context Sharing Between Models

Context Distillation: Training Smaller Models on Optimized Context

Real-Time Context Adaptation: Dynamic Prompt Rewriting

Multimodal Context: Text + Images + Audio in One Window

Edge Cases: Handling Context Overflow Gracefully

Emerging Research & Future Directions

Module 7: Capstone: Context-Optimized AI System4 lessons

Module 7: Capstone: Context-Optimized AI System

Project Planning: Designing Your Context-Optimized System

Implementation: Building the Full Pipeline from Scratch

Testing and Optimization: Iterating on Context Strategy

Presentation: Showcasing Your Context Engineering Portfolio