Models, Harnesses, and Multi-Agent Systems
About this episode
The episode explores AI models, agents, and the shift towards multi-agent systems in organizations.
AI has moved far beyond chatbots, but what exactly are AI models, agents, agent harnesses, and multi-agent systems, and why do they matter? In this episode, Daniel and Chris break down the terminology behind today's AI landscape, explain the differences between AI features and autonomous agents, and explore why organizations are shifting toward fleets of AI agents powered by multiple models. They also discuss open vs. closed models, enterprise AI architectures, vendor lock-in, and practical ways to begin adopting agentic AI in your own organization. If you feel left behind by this ongoing agentic AI revolution that has rapidly accelerated to warp speed, then this episode is the catch-up primer you've been waiting for! Featuring: Chris Benson – Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack – Website , GitHub , X Sponsors: Framer: The enterprise-grade website builder that lets your team ship faster. Get 30% off at framer.com/practicalai Midwest AI Summit: Join AI practitioners on October 15 in Indianapolis for practical sessions, hands-on discussions, and real-world AI solutions. Use code PracticalAI20 to save 20% on your registration…
People in this episode
Hosts: Chris Benson, Daniel Whitenack
Topics covered
- AI models
- multi-agent systems
- autonomous agents
- enterprise AI architectures
- agentic AI
Keywords
- AI models
- multi-agent systems
- autonomous agents
- enterprise AI
- agentic AI
Sponsors
Framer, Midwest AI Summit, Prediction Guard
More episodes of Practical AI
- Less about Models; More about Architecture
- Building the Foundation for the Agentic AI Era
- AI Proficiency: From Users to Builders
- Reconstructing how OpenAI agents attacked Hugging Face
- Surviving the New Economics of a Post-Agentic World
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