WEBVTT

00:00:05 --> 00:01:16
Shifting from chat interfaces to integrated AI agents

00:01:16 --> 00:03:06
Core components of an AI agent architecture

00:03:06 --> 00:04:16
Resolving developer challenges in AI agent implementation

00:04:16 --> 00:05:29
Managing AI development with Azure AI Foundry

00:05:29 --> 00:06:55
Orchestrating enterprise agents via the Agent Service

00:06:55 --> 00:08:29
Aligning AI projects across standard development phases

00:08:29 --> 00:09:41
Testing AI models quickly using GitHub Models

00:09:41 --> 00:12:17
Balancing prompt performance and model cost efficiency

00:12:17 --> 00:13:31
Connecting agents to business tools and APIs

00:13:31 --> 00:15:22
Automating quality testing through CI/CD evaluation pipelines

00:15:22 --> 00:17:40
Analyzing complex contracts using multi-agent workflows

00:17:40 --> 00:19:03
Measuring AI agent performance within GitHub Workflows

00:19:03 --> 00:22:07
Sampling production traffic for end-to-end tracing observability

00:22:07 --> 00:24:36
Selecting communication patterns for multi-agent systems

00:24:36 --> 99:59:59
Building scalable agent workflows using Semantic Kernel