Models, Harnesses, and Multi-Agent Systems - Neural networks - Practical AI

Topics in this episode

Neural networks Computer vision Artificial intelligence Machine Learning Deep Learning

Episode notes

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.