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Advanced Agentic AI: RAG 2.0, SLMs & Multi-Agent Systems

For senior engineers building the next generation of AI systems

2 daysInstructor-led Workshop
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Program Overview

What This Program Covers

This advanced program goes deep into the architectures powering production agentic AI systems in 2026 — RAG 2.0 pipelines, small language models, multi-agent orchestration, and the engineering patterns that separate proof-of-concepts from production systems. Designed for senior engineers who are already building with AI and want to significantly level up their architectural knowledge.

What You'll Learn

  1. 1Design and implement RAG 2.0 pipelines with advanced retrieval strategies
  2. 2Evaluate and deploy small language models for specific enterprise use cases
  3. 3Architect multi-agent systems with proper orchestration and fallback patterns
  4. 4Optimize token consumption across complex agentic workflows
  5. 5Implement production-grade evaluation frameworks for AI systems
  6. 6Apply governance and safety patterns to multi-agent architectures
  7. 7Debug and monitor complex AI systems in production

Outline

Program Snapshot

Module 1 — RAG 2.0 Architecture

  • ›Beyond naive RAG — hybrid retrieval strategies
  • ›Chunking, embedding, and reranking at scale
  • ›Multi-modal RAG and structured data integration
  • ›Hands-on: build a production RAG pipeline

Module 2 — Small Language Models

  • ›When to use SLMs vs frontier models
  • ›Fine-tuning vs prompting vs RAG
  • ›Distillation and quantization fundamentals
  • ›Hands-on: deploy and evaluate an SLM

Module 3 — Multi-Agent Orchestration

  • ›Agent topologies — orchestrator/worker patterns
  • ›State management across agent networks
  • ›Error handling and fallback strategies
  • ›Hands-on: build a multi-agent workflow

Module 4 — Production and Governance

  • ›Evaluation frameworks for agentic systems
  • ›Monitoring, observability, and debugging
  • ›Cost management at scale
  • ›Security and governance patterns

Who This Is For

  • Senior software engineers
  • ML engineers and AI platform engineers
  • Staff and principal engineers
  • Engineering leads building AI infrastructure

Prerequisites

  • Solid software engineering fundamentals
  • Experience building with LLM APIs
  • Familiarity with Python
  • Prior exposure to RAG or agentic patterns preferred

Bring This Program to Your Team

Every bILTup program is fully customized to your team's tech stack, goals, and timeline. Tell us about your team and we'll design something built specifically for you.

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