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Building Business-Ready Generative AI Systems: Build Human-Centered AI Systems with Context Engineering, Agents, Memory, and LLMs for Enterprise
by Denis Rothman
Sponsored
Synopsis
Supercharge your business with context-aware AI controllers, adaptive agents, multimodal reasoning functionality, neuroscientific memory systems, and flexible handler mechanisms that integrate the emerging generative AI models.
Get with your book: PDF copy, AI Assistant, and Next-Gen Reader ...
Get with your book: PDF copy, AI Assistant, and Next-Gen Reader ...
Supercharge your business with context-aware AI controllers, adaptive agents, multimodal reasoning functionality, neuroscientific memory systems, and flexible handler mechanisms that integrate the emerging generative AI models.
Get with your book: PDF copy, AI Assistant, and Next-Gen Reader free.
Key Features
Build an adaptive, context-aware AI controller with advanced memory strategies
Enhance GenAISys with multi-domain, multimodal reasoning capabilities and Chain of Thought (CoT)
Seamlessly integrate cutting-edge OpenAI and DeepSeek models as you see fit
Book Description
Standalone LLMs no longer deliver sufficient business value on their own. This guide moves beyond basic chatbots, showing you how to build agentic, ChatGPT-grade systems capable of sophisticated semantic and sentiment analysis, powered by context engineering.
You'll design AI controller architectures with multi-user memory retention to dynamically adapt your system to diverse user and system inputs. You'll architect a Retrieval-Augmented Generation system with Pinecone to combine instruction-driven scenarios. Through context engineering, you’ll minimize token usage, maximize response quality, and create systems that reason across complex tasks with precision. You'll enhance your system’s intelligence with multimodal capabilities—image generation, voice interactions, and machine-driven reasoning—leveraging Chain-of-Thought and context chaining to address cross-domain automation challenges. You'll also integrate OpenAI’s suite and DeepSeek-R1 without disrupting your existing GenAISys ecosystem.
With context engineering as the backbone, every step becomes a deliberate act of shaping model behavior. Your GenAISys will apply neuroscience-inspired insights to marketing strategies, predict human mobility, integrate smoothly into human workflows, and connect to live external data, all wrapped in a polished, investor-ready interface.
What you will learn
Implement an AI controller with a conversation AI agent and orchestrator at its core
Build contextual awareness with short-term, long-term, and cross-session memory
Design cross-domain automation with multimodal reasoning, image generation, and voice features
Expand a CoT agent by integrating consumer-memory understanding
Integrate cutting-edge models of your choice without disrupting your existing GenAISys
Connect to real-time external data while blocking security breaches
Who this book is for
This book is for AI and Machine Learning Engineers seeking to enhance their understanding of Generative AI and its enterprise applications. It will particularly benefit those interested in building AI agents, creating advanced orchestration systems, and leveraging AI for automation in marketing, production, and logistics. Software architects and enterprise developers looking to build scalable AI-driven systems will also find immense value in this guide. No prior superintelligence experience is necessary, but familiarity with AI concepts is recommended.
Table of Contents
Defining a Business-Ready Generative AI System
Building the Generative AI Controller
Integrating Dynamic RAG into the GenAISys
Building the AI Controller Orchestration Interface
Adding Multimodal, Multifunctional Reasoning with Chain of Thought
Reasoning E-Marketing AI Agents
Enhancing the GenAISys with DeepSeek
GenAISys for Trajectory Simulation and Prediction
Upgrading the GenAISys with Data Security and Moderation for Customer Service
Presenting Your Business-Ready Generative AI System
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