Code: https://github.com/oracle-devrel/orac...

In this video, we explore memory engineering, context engineering, and prompt engineering within AI agents, examining how these disciplines interconnect to create reliable, believable, and capable AI systems.

We explore the agent stack with a focus on reasoning and memory management. We touch on topics that include the core concepts of prompt and context engineering, techniques like few-shot, chain of thought, and react prompting, and the significance of memory engineering inspired by human cognitive processes.

Detailed coding examples and practical applications will be demonstrated, providing a comprehensive understanding of how these engineering techniques optimize AI agent performance. Stay tuned for an in-depth look at how these elements contribute to the continual improvement and sophistication of AI systems.

00:00 Introduction to the session: overview of memory, context, and prompt engineering in AI agents
00:46 Explanation of the agent stack and focus on reasoning and memory managers
01:39 Introduction to the concept of the memory core and its role in agent infrastructure
01:52 Session objectives: understanding the interplay of prompt, context, and memory engineering
02:07 Defining prompt engineering and its key techniques (few-shot, chain of thought, ReACT prompting)
02:53 Few Shot Prompting
03:34 Chain of Thought Prompting
04:21 ReACT Prompting
04:48 Discussion on the evolution of prompt engineering as LLMs improve
05:36 Transition to context engineering: definition and differentiation from prompt engineering
07:26 Techniques in context engineering: context window utility, organization, isolation, retrieval, and reduction
08:51 Emphasis on context engineering as an optimization technique
09:10 Introduction to memory engineering: drawing parallels with human memory
09:45 Defining agent memory and the role of memory management systems
10:28 Types of agent memory: short-term vs. long-term, and their engineering implications
11:01 Memory engineering as a continuation technique and its future as LLMs evolve
12:30 The interplay between prompt, context, and memory in agent design
13:50 Diagram explanation: boundaries between context and memory engineering, and the role of the memory core
14:32 The function of memory managers and their impact on information recall and forgetting mechanisms
16:02 Overview of available code resources and reference to the Oracle AI developer hub

Check out the following playlist:
1️⃣ AI Stack Engineer [Learn Series]: https://bit.ly/4f2p3xg
2️⃣ AI Stack Engineer [Startup Series]: https://bit.ly/4bxnO6d

#ai #contextengineering #promptengineering #memoryengineering #artificialintelligence #aivideosearch

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