Persistent Memory in AI Agents: Design Robust Modular Systems with Semantic Kernel and Modern RAG Approaches

By Ethan Tyson

Persistent Memory in AI Agents: Design Robust Modular Systems with Semantic Kernel and Modern RAG Approaches

Are you building AI agents that quickly lose context or hallucinate when facing complex tasks? You're not alone-and the solution isn't another isolated LLM. It's a unified architecture that gives your agents persistent memory, robust reasoning, and seamless data integration.

Persistent Memory in AI Agents delivers a step-by-step blueprint for designing modular, production-ready AI systems using Semantic Kernel and modern Retrieval-Augmented Generation (RAG) techniques. Learn how to structure memory hierarchies, orchestrate multi-agent workflows, and secure dynamic data pipelines-so your agents truly remember past interactions and deliver accurate, context-aware responses.

Inside this book, you'll discover how to:

Build layered memory systems (session, short-term "whiteboard," long-term embeddings) that fuel ongoing conversations without losing track

Integrate RAG pipelines with vector and sparse search, reranking, and knowledge graphs for reliable retrieval from diverse sources

Orchestrate specialized agents-coordinators, retrievers, reasoners, critics-to automate query rewriting, evaluation loops, and secure function calls

Implement security and governance best practices, from access controls and PII redaction to telemetry, auditing, and memory lifecycle management

Deploy and scale your agents in serverless and containerized environments, backed by load testing, model versioning, and MLOps integration

What you'll gain:

Mastery of Semantic Kernel for seamless plugin and agent development

Hands-on skills to assemble RAG-based architectures that minimize hallucinations and maximize relevance

Practical insights into real-world workflows-from video-to-blog pipelines to memory-enhanced help desks and internal knowledge assistants

Strategies for advanced retrieval, including hybrid vector + sparse search and graph-based reasoning

A comprehensive developer checklist to ensure your agents are secure, observable, and ready for enterprise scale

Why settle for one-off AI experiments when you can engineer agents that adapt, learn, and act with institutional knowledge? Whether you're an AI engineer, data scientist, or software architect, this book equips you to push past prototype limitations and deliver intelligent systems that maintain context, comply with governance, and integrate across your organization's data silos.

Ready to transform your AI capabilities? Embrace persistent memory, unlock robust modular design, and elevate your AI agents today-grab your copy of Persistent Memory in AI Agents and start building the future of enterprise-grade intelligence.

• Format: Paperback
• Language: English
• ISBN: B0FHVS5KPB
• ISBN13: 9798292744252
• Release Date: July 2025
• Publisher: Independently Published
• Length: 186 Pages
• Weight: 0.73 lbs.
• Dimensions: 0.4" x 7.0" x 10.0"