Context Engineering for Multi-Agent Systems
Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning
Created by Denis Rothman
Discover how to design reliable AI systems by building a transparent Context Engine. Move beyond simple prompting and learn to architect multi-agent workflows that adapt across different domains. Gain practical skills to create structured, context-aware solutions you can trust.
Packt | Nov 2025 | 396 min
What You Will Learn
You will start by learning how to structure context for AI, then progress to designing and orchestrating multi-agent workflows. As you advance, you will add memory, retrieval, and safeguards, culminating in building a resilient Context Engine that can be adapted and deployed in real-world scenarios.
Key Features
- Create semantic blueprints for precise, goal-driven AI context management
- Coordinate specialized agents for adaptable, context-rich reasoning workflows
- Build a transparent Context Engine with robust memory, retrieval, and safeguards
Target Audience
Ideal for AI engineers, software developers, system architects, and data scientists ready to move beyond basic prompting. If you have experience with large language models and want to design structured, transparent, and adaptable AI systems, this course will help you orchestrate agents and enforce safeguards with confidence.
