
How to Give Your AI Agents a Brain
Michael Patterson
This audiobook is narrated by a digital voice.
Most AI agents today impress in demos but fail in real-world applications. They forget context between conversations, hallucinate information, and break down on complex multi-step tasks. If you want...
Location:
United States
Description:
This audiobook is narrated by a digital voice. Most AI agents today impress in demos but fail in real-world applications. They forget context between conversations, hallucinate information, and break down on complex multi-step tasks. If you want agents that can truly think and adapt, you need to give them a brain with memory, reasoning, and decision-making capabilities. How to Give Your AI Agents a Brain is the practical developer's guide to building autonomous AI agents with advanced memory systems and intelligent reasoning. This isn't another surface-level AI book filled with theory. Instead, it provides concrete implementation strategies for creating agents that can handle complex workflows, maintain context across interactions, and continuously improve their performance. What You'll Master: Vector embeddings and semantic search fundamentals that power intelligent memory systems. Learn how to convert conversations and data into mathematical representations that capture meaning and context, enabling your agents to recall relevant information instantly. Building and optimizing vector databases using industry-standard tools like Pinecone, Weaviate, and Chroma. Understand which database architecture fits your specific use case and how to implement retrieval-augmented generation for accurate, contextual responses. Memory management strategies include short-term conversational memory, long-term knowledge retention, and episodic learning patterns. Design systems that know when to remember critical information, what to forget to maintain efficiency, and how to prioritize data for maximum relevance. Large language models programming techniques that go beyond simple prompt engineering. Discover how to chain reasoning steps, implement tool use capabilities, and create feedback loops that help your agents learn from their mistakes. Duration - 3h 20m. Author - Michael Patterson. Narrator - Digital Voice Maxwell G. Published Date - Tuesday, 27 January 2026. Copyright - © 2026 Michael Patterson ©.
Language:
English
Introduction
Duración:00:06:16
Chapter 1: Why Most Agents Fall Short
Duración:00:09:17
Chapter 2: The Architecture of Intelligence
Duración:00:09:05
Chapter 3: Short-Term Memory and Context
Duración:00:10:49
Chapter 4: Long-Term Memory Systems
Duración:00:09:22
Chapter 5: Building a Knowledge Base
Duración:00:10:29
Chapter 6: Retrieval and Context Injection
Duración:00:08:56
Chapter 7: Decision-Making Frameworks
Duración:00:10:31
Chapter 8: Reasoning Loops
Duración:00:09:44
Chapter 9: Tool Use and External Actions
Duración:00:08:55
Chapter 10: Prompt Architecture for Agents
Duración:00:09:22
Chapter 11: Designing Intelligent Workflows
Duración:00:09:16
Chapter 12: Agent Persona and Voice
Duración:00:09:12
Chapter 13: Testing Your Agent's Intelligence
Duración:00:08:44
Chapter 14: Agents for Business
Duración:00:08:26
Chapter 15: Scaling Agent Intelligence
Duración:00:11:22
Chapter 16: Building Prompt Libraries
Duración:00:08:13
Chapter 17: Agent Handoffs and Communication
Duración:00:07:22
Chapter 18: Agent Security and Trust
Duración:00:07:36
Chapter 19: Your First Smart Agent Blueprint
Duración:00:08:47
Chapter 20: Workflow Templates and Prompt Patterns
Duración:00:12:02
Conclusion
Duración:00:06:41