In this episode, we explore AI coding agent architectures and compare two distinct approaches to design and implementation. Learn how to leverage Large Language Models (LLMs) for task planning, develop effective code generation and evaluation loops, and integrate contextual information to enhance agent performance. We discuss how applying Test Driven Development (TDD) principles can lead to more robust and reliable AI application design.
Chapters:
0:00 – Introduction
1:23 – Aja’s Agent Design Overview
2:45 – Jason’s Agent Design Approach
3:01 – The Importance of Context
3:38 – LLM Planning in Agent Workflow
4:35 – Code Generation and Evaluation Loops
5:25 – AI Application Design and TDD
6:11 – Final Evaluation and Orchestration
Resources:
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Speakers: Aja Hammerly, Jason Davenport
Products Mentioned: Gemini, Gemma
