Armchair Architects: Defining AI Agents and Their Core Traits
Microsoft Developer presents a roundtable with David Blank-Edelman, Uli Homann, and Eric Charran, defining the core traits of AI agents and their architectural importance for cloud solution architects.
Armchair Architects: Defining AI Agents and Their Core Traits
Host: David Blank-Edelman
Guests: Uli Homann (CVP at Microsoft), Eric Charran (Executive Director, Intuit)
Series: Azure Essentials Show – Armchair Architects, Season 6
Episode Overview
This opening episode explores AI agents, breaking down what distinguishes them from chatbots and outlining their increasing role in cloud solution architecture. The discussion defines essential agent characteristics, clarifies the relationship between agents and large language models (LLMs), and dives into architectural layers and anomaly handling.
Key Topics
- AI Agents vs Chatbots: Clear definitions, use cases, and differences.
- Architectural Layers: Describes how agents fit within broader system designs.
- LLM Requirements: Discusses when agents need LLMs and when they don’t.
- Agent Capabilities: Empowerment to act, handling anomalies, and decision-making.
- Integration Points: Where agents augment or plug into cloud-based architectures.
Resources
- Agent Factory: Designing the open agentic web stack
- Azure Architecture Center
- AI Architecture Design
- Get started with AI agent development on Azure
Related Episodes
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Outline
- 0:47 Welcome architects
- 2:01 What is an agent?
- 2:43 Empowered to act
- 4:03 Do agents require LLMs?
- 5:45 How is an agent different from a chatbot?
- 6:06 Architectural layers of an agent
- 7:45 Agents 101
- 11:35 Handling anomalies
- 14:42 Where do agents plug in?
- 16:38 Episode 2 preview: Designing effective AI agents
This episode is ideal for solution architects, AI developers, and anyone interested in building intelligent, action-oriented agentic systems using Microsoft Azure.