Context engineering is the skill that separates developers who can prompt from developers who can ship. This live 6-hour workshop shows you how to build production-ready multi-agent AI systems using semantic blueprints, MCP orchestration, and high-fidelity RAG pipelines.
By Packt Publishing · Refunds up to 10 days before
Most AI workshops teach you to call the OpenAI API. This context engineering workshop teaches you to architect reliable, transparent, production-grade AI systems — the skill stack that is defining the next generation of AI engineers.
Context engineering is the discipline of designing AI systems that provide the right information, tools, and context to LLMs at the right time — replacing brittle prompts with reliable, scalable production AI architectures.
Multi-agent systems are AI architectures where specialised agents collaborate to accomplish complex tasks. This workshop shows you how to orchestrate them reliably using the Model Context Protocol and semantic blueprints.
MCP is Anthropic's open standard for connecting AI models to tools, data sources, and other agents. This workshop teaches you to use MCP for building orchestrated multi-agent workflows that are transparent and controllable.
Context engineering and multi-agent systems have almost no quality hands-on resources. This 6-hour live workshop gives you a complete guided build with a bestselling AI author answering your questions throughout.
Six modules. Six hours. A production-ready context engine by the time you finish.
Design structured context that gives AI agents precise, goal-driven contextual awareness beyond simple prompting.
Orchestrate specialised agents using the Model Context Protocol for adaptable, context-rich reasoning workflows.
Engineer retrieval-augmented generation pipelines with citations, memory, and safeguards against hallucination.
Design AI memory systems that maintain context across long conversations and complex multi-step workflows.
Implement moderation, data poisoning protection, prompt injection prevention, and trust mechanisms for production AI.
Build a transparent, traceable Context Engine that gives you complete visibility and control over your AI system.
A working production system — not just architectural knowledge.
A fully working multi-agent system with context engineering
MCP-orchestrated agent workflows you can use in production
High-fidelity RAG pipeline with citations and memory
Semantic blueprints and agent architecture patterns
Production-ready safeguards against hallucination and injection
Certificate of completion from Packt Publishing
Denis Rothman has 30+ years in AI and wrote the book on context engineering — literally.
Denis Rothman is a bestselling AI author with over 30 years of experience in artificial intelligence, optimisation, and agent systems. He has written multiple cutting-edge AI books for Packt Publishing and is the author of the book “Context Engineering for Multi-Agent Systems.” In this workshop he guides you step by step through the practical architecture of production-ready multi-agent AI systems.
This is an intermediate to advanced workshop. You need the basics below.
Common questions about the workshop, what to expect, and how to prepare.
Context engineering is the discipline of designing systems that provide the right information, tools, and context to LLMs at the right time — moving beyond brittle prompt engineering to reliable production AI architecture. In 2026, context engineering has become the foundational skill for building AI systems that actually work in production, not just in demos.
You will build a fully operational Glass-Box Context Engine — a transparent, traceable multi-agent AI system. By the end of this workshop you will have working semantic blueprints, MCP-orchestrated agent workflows, a high-fidelity RAG pipeline with citations, memory engineering, and production-ready safeguards against hallucination and prompt injection.
The Model Context Protocol (MCP) is Anthropic's open standard for connecting AI models to tools, data sources, and other agents. This context engineering workshop uses MCP because it is the most robust and vendor-neutral approach to building orchestrated multi-agent systems — giving you skills that apply across different AI providers and frameworks.
This workshop is designed for developers with intermediate Python experience and basic LLM familiarity. You do not need prior experience with context engineering or multi-agent systems. Denis Rothman builds from first principles ensuring every participant understands the architecture, not just the code.
Prompt engineering means crafting individual instructions for a single LLM call. Context engineering means designing complete systems that manage what information agents receive, how they communicate, what tools they use, and how their outputs are validated and trusted. Context engineering operates at the architectural level while prompt engineering operates at the query level.
Yes. All registered participants receive a full recording of this context engineering workshop after the live session on April 25 so you can rewatch any module at your own pace.
6 hours. Live bestselling AI author. Production multi-agent system by the end. Seats are limited.
Register Now →Saturday April 25 · 9am to 3pm EDT · Online · Packt Publishing