Context Engineering for Multi Agent Systems Cohort 2

Build Highly Scalable Context-Aware RAG-Powered Agents that can Reason and Act

Build production-ready AI that reasons in context using semantic blueprints, multi-agent orchestration, memory, high-fidelity RAG pipelines, and safeguards.

🎟️ Limited seats | April 25 (Saturday) | Live Online (5 Hours)

If your RAG + agent systems work in demos but break in production—this is the workshop designed to fix that.
You’ll learn how to engineer a Context Engine: a transparent, traceable, controllable architecture that makes AI systems reliable, explainable, and scalable.

What You’ll Build & Learn (Hands-On)

In this intensive session, bestselling AI author Denis Rothman will walk you through the real architecture behind stable, production-grade agentic systems:

Semantic Blueprints Design structured, goal-driven context so agents stay aligned and purposeful

Multi-Agent Orchestration (MCP) Coordinate specialized agents with deterministic message passing and controlled state exchange

High-Fidelity RAG Pipelines Build retrieval systems that stay accurate, cite sources, and reduce hallucinations

Memory Engineering Implement short-term + long-term memory models that don’t drift or corrupt behavior

Trust + Safeguards Defend against prompt injection, data poisoning, and unsafe tool usage with guardrails + moderation

Production Readiness Add evaluation loops, observability, and scalable patterns you can reuse across domains

Who Should Attend

This workshop is ideal for:

• AI engineers & developers
• ML engineers & researchers
• Software architects & platform engineers
• Product teams building copilots/agents
• Technical leaders adopting AI automation

Level: Intermediate to Advanced (recommended for builders working with LLMs)