In this episode of the ODSC Ai X Podcast, host Sheamus McGovern sits down with Michael Lanham, author of AI Agents in Action, to explore the rapidly evolving world of AI agents. Michael brings decades of experience across industries—game development, fintech, oil and gas, and agtech—and provides listeners with a hands-on view into what makes AI agents different from chatbots, how agency enables autonomy, and why frameworks like MCP (Message Control Protocol) are reshaping agent workflows.

This discussion guides listeners from foundational principles of AI agents to advanced topics like memory architecture, agent collaboration, cost-performance trade-offs, and the future of digital coworkers.

Key Topics Covered:

• What defines an AI agent and how it differs from chatbots and automation tools
• The meaning of "agency" in AI and how LLMs are gaining decision-making capabilities
• Importance of prompt engineering in agent design and workflow control
• Overview of MCP (Message Control Protocol): structure, use cases, and why it's gaining traction
• Types of memory in agents: short-term, long-term, episodic, and procedural
• Evaluating agent performance using grounding evaluation, OpenTelemetry, and tools like Phoenix
• Comparison of agent frameworks like AutoGen, CrewAI, and OpenAI’s Agent SDK
• Practical challenges of token cost, latency, and scaling agent workflows
• The rise of multi-agent systems and collaboration patterns
• Future of AI agents as digital coworkers and their role in creative industries

Memorable Outtakes:

• "A key principle that many miss is that an AI agent is about one word: agency."
• "You can now drop in an MCP server, connect it to Claude or OpenAI’s SDK, and your agent can suddenly use six or seven tools without extra wiring. That’s power."
• "We're moving from automation to collaboration. The next shift is treating agents as digital coworkers with decision ownership, not just executors of tasks."

References & Resources:

• AI Agents in Action by Michael Lanham: https://www.manning.com/books/ai-agents-in-action
• Michael Lanham's LinkedIn:  https://www.linkedin.com/in/micheal-lanham-189693123/
• Michael’s Medium blog: https://medium.com/@Micheal-Lanham
• Smithery (MCP server library): https://smithery.ai/
• MCP blog from Anthropic: https://www.anthropic.com/news/model-context-protocol
• OpenAI Agents SDK:https://openai.github.io/openai-agents-python/
• CrewAI: https://github.com/joaomdmoura/crewAI
• AutoGen: https://github.com/microsoft/autogen
• Arize Phoenix (LLM evaluation tool): https://github.com/Arize-ai/phoenix
• LangFuse (evaluation & observability for LLM apps): hhttps://github.com/langfuse/langfuse
• Google Veo: https://deepmind.google/technologies/veo
• OpenTelemetry:  https://opentelemetry.io/
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