Empowering AI Agents with Context: Data Integration for Intelligent Decision Making: Learn to Connect Your AI Systems with Real-Time Data Sources ... with Transformers and Context-Aware AI)
Language: English
Published by Independently published, 2025
- Softcover
- New

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- Title
- Empowering AI Agents with Context: Data Integration for Intelligent Decision Making: Learn to Connect Your AI Systems with Real-Time Data Sources ... with Transformers and Context-Aware AI)
- Author
- Quan, Ethan
- Publisher
- Independently published
- Publication year
- 2025
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798296060372
- Series
- Book 3 of 3: AI Agent Mastery Series: Building, Scaling, and Integrating Intelligent AI Systems with Transformers and Context-Aware AI
Elevate your AI agents with Empowering AI Agents with Context: Data Integration for Intelligent Decision Making, a comprehensive guide for developers seeking to enhance AI with real-time data. Authored by Ethan Quan, this 14-chapter book explores context-aware data integration, starting with development environment setup and bootstrapping MCP server projects. Master integration with tools like GitHub, Slack, and Google Drive, and learn secure access and authentication best practices, rate limiting, caching, and logging for efficient operations.
Delve into deploying context-aware agents on cloud platforms, building robust data pipelines for real-time access, and ensuring security and compliance in data-integrated AI systems. With practical code examples in Python and TypeScript, the book offers scalability insights for large-scale data integration and real-world case studies, such as streamlining code management and collaborative workflows. Ideal for developers aiming to build high-performance, secure AI agents, this book requires no advanced prerequisitesnjust a desire to innovate. Featuring concise tutorials and actionable checklists, achieve transformative results quickly.
Key Topics: Context-aware AI, data integration, MCP servers, real-time data access, GitHub/Slack/Google Drive integration, secure authentication, rate limiting, caching, logging, cloud deployment, data pipelines, security compliance, scalability, code management, collaborative workflows, real-world case studies.
Who This Book Is For:
Delve into deploying context-aware agents on cloud platforms, building robust data pipelines for real-time access, and ensuring security and compliance in data-integrated AI systems. With practical code examples in Python and TypeScript, the book offers scalability insights for large-scale data integration and real-world case studies, such as streamlining code management and collaborative workflows. Ideal for developers aiming to build high-performance, secure AI agents, this book requires no advanced prerequisitesnjust a desire to innovate. Featuring concise tutorials and actionable checklists, achieve transformative results quickly.
Key Topics: Context-aware AI, data integration, MCP servers, real-time data access, GitHub/Slack/Google Drive integration, secure authentication, rate limiting, caching, logging, cloud deployment, data pipelines, security compliance, scalability, code management, collaborative workflows, real-world case studies.
Who This Book Is For:
- Developers integrating real-time data into AI systems.
- AI Engineers enhancing agent performance with context.
- Data Scientists optimizing decision-making processes.
- Product Leaders leveraging data-driven AI strategies.
- No prior context-aware expertise needed—just a drive to excel.
- Comprehensive Guide: From setup to scalable deployment.
- Practical Tools: Hands-on tutorials and code for instant impact.
- Forward-Looking: Highlights future trends in context-aware AI.
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California Books
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