Context Engineering
Designing dynamic systems that give LMs the right info, in the right format, at the right time
Beyond simple prompts—building intelligent agent ecosystems for enterprise AI applications
Listen to the Full Guide
Complete audio walkthrough of Context Engineering concepts
Choose Your Learning Path
Fundamentals
Start here to understand what context engineering is, when to use it, and how it differs from prompt engineering.
- • Core definitions and scope
- • 6 essential AI agent components
- • When context engineering applies
- • Foundation concepts
Implementation
Hands-on examples, system prompt structures, and practical techniques for building context-engineered systems.
- • System prompt architecture
- • Real-world examples
- • Multi-agent patterns
- • Advanced techniques
Enterprise
Strategic implementation, governance frameworks, and Salesforce AI stack integration for enterprise environments.
- • Salesforce AI stack integration
- • Governance & compliance
- • Strategic implementation
- • Enterprise architecture
The Context Engineering Difference
Traditional Prompting
Single command → Single response
Stateless • Momentary • Limited
Context Engineering
Dynamic system → Intelligent responses
Contextual • Adaptive • Collaborative
The enterprise AI landscape is shifting from crafting the perfect command to engineering intelligent, interconnected agent systems that understand context, maintain memory, and orchestrate complex workflows.