Description
Patterns for Building AI Agents is a practical and technical guide for developers and engineers who want to go beyond simple language models to build autonomous, multi-faceted systems. The author explores the complex architectures and practical frameworks that are essential for designing, implementing, and deploying AI agents at an industrial scale. The book focuses on how to break down complex tasks into manageable components and create systems that can learn and adapt to changing environments.
In various sections of this text, concepts such as context engineering, performance quality assessment, and security in AI operating systems are examined in detail. Drawing on the experiences of leading companies and successful startups, the author presents repeatable patterns that help reduce system errors and increase the accuracy of decision-making in AI agents. This book teaches the reader how to balance full machine autonomy with human supervision so that the final output is both reliable and efficient.
Book Features
- Providing key patterns for designing the architecture of AI agents (ReAct, planning and execution).
- Training memory systems including vector, episodic, and long-term memories.
- A detailed examination of recovery-augmented production (RAG) for knowledge-based agents.
- Step-by-step tutorial on working with tools like LangChain and LangGraph to manage workflows.
- Focus on security, monitoring, and performance evaluation of AI systems in real-world environments.
- Includes practical examples in Python and actionable projects for a deeper understanding of the material.
Book specifications
- Publisher: Mastra
- Lecturer/Author: SAM BHAGWAT
- Number of pages: 93
- Number of chapters: 5
- Format: PDF
Headlines
Configure your agents
Engineer Agent context
Evaluate agent responses
Secure your agents
The future of agents
Pictures
User Guide
Extract the file and run it with the appropriate software.
Download link
File(s) password: www.downloadly.ir
File size
2.9 MB
