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The agentic transformation isn’t coming. It has already begun.
Companies are deploying thousands — and sometimes tens of thousands — of AI agents. Enterprise software giants are watching their old economic moats erode. Capital is moving, productivity is being redefined, and human labor is being repriced in real time.
In this Fully Connected episode, Daniel and Chris explore the new economics of a post-agentic world: the global order that emerges after agents have been woven into every conceivable aspect of business and life. What happens when digital labor becomes abundant, agents manage other agents, and entire organizations operate at a scale no human workforce could match?
This isn’t another conversation about whether AI will take your job. It’s about what happens when the assumptions underneath jobs, companies, software, and productivity stop being true.
The post-agentic world is already taking shape.
The question is whether you’re preparing for it — or becoming part of what it replaces.
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As AI applications become more complex, the infrastructure powering them needs to evolve. Corey Sanders, SVP of Product at CoreWeave, joins Chris to discuss why AI requires a fundamentally different approach than traditional cloud computing. They explore AI-native infrastructure, training and inference workloads, the rise of agentic development, optimizing GPU performance, AI research workflows, and why the future of software will be built around AI-first experiences rather than websites and apps.
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What does it take to move AI agents from demos to reliable production systems? In this episode, Hamza Tahir explores how MLOps principles are shaping the future of generative AI, covering workflows, agent harnesses, fleets, and the infrastructure needed to build durable, scalable systems. The conversation dives into open source tools, production challenges, and how ZenML's new project, Kitaru, helps developers build resilient, replayable, and observable agent systems.
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How has AI image generation evolved from blurry outputs to powerful visual intelligence models? Dustin Podell, Co-Founder and Researcher at Black Forest Labs, explains the progression from diffusion to flow matching, how modern image models work, and how they're being used for image editing and practical visual workflows. The conversation also explores the FLUX family of models, running image generation locally, and where visual AI is headed next.
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How do we build trust in AI agents before the AI hailstorm arrives? Emil Lassen from the Artificial Intelligence Underwriting Company (AIUC) joins the show to discuss how the enterprise flywheel of standards, certification, audit, and insurance is being applied to AI agents. They explore the AIUC-1 framework, the challenges of securing agentic AI systems, and why red teaming (based on standards) may be key to accelerating enterprise AI adoption.
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As AI agents become more capable and autonomous, they also introduce new security challenges. In this 'Fully Connected' episode, Dan and Chris unpack Anthropic’s Zero Trust for AI Agents security framework and what it means for organizations deploying agentic systems. They examine the key security risks facing agentic systems and discuss how organizations can apply Zero Trust principles to deploy AI agents safely. Along the way, they break down practical security controls and discuss how traditional cybersecurity principles must evolve for the age of AI agents.
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AI models can win math olympiads… but still struggle to read an analog clock. In this fully connected episode, Dan and Chris break down the latest Stanford AI Index Report and explore what it reveals about the current state of AI. They discuss AI adoption and safety, disappearing junior tech jobs, robotics, AI’s “jagged frontier” of intelligence, and the growing race between the U.S. and China. Along the way, they debate whether AI should optimize everything, or if some things are better left human.
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What happens when AI agents start acting less like chatbots and more like coworkers? In this episode, Dan and Chris sit down with Craig McLuckie, CEO of Stacklok to explore MCP, Kubernetes, ToolHive, enterprise AI, and the emerging infrastructure powering AI-native applications. From identity management to agent orchestration and system architecture, this conversation dives into how organizations may soon manage entire fleets of AI agents working behind the scenes.
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Open Source AI is entering a new era, one shaped by self-improving AI Agents, recursive learning systems, and rapidly evolving AI Tools that blur the line between software and autonomous collaborators. In this episode, Daniel and Chris sit down with Nous Research co-founder and CTO Jeffrey Quesnelle to explore Hermes Agent. Along the way, they discuss models vs. harnesses, the changing role of developers, and one of the biggest questions facing the AI Future: what remains uniquely human as AI capabilities continue to accelerate?
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U.S. Congressman Don Beyer returns to Practical AI for another far-reaching conversation with Chris about many of the most important AI challenges facing America and the world. Blending political savvy and statesmanship with his unique technical understanding as an active Ph.D student in AI at George Mason University (making him the coolest member of Congress!), the congressman shares his perspective about the really hard AI concerns that you would have asked him yourself. Together, Congressman Beyer and Chris explore AI regulation, cybersecurity concerns sparked by advanced models like Mythos, bipartisan AI governance efforts, and the growing AI race between the U.S. and China. They fearlessly dived headfirst into AI-driven job displacement, mass surveillance, autonomous weapons, existential risk, and the philosophical questions surrounding consciousness and superintelligence as AI continues to accelerate. This is an unusual and insightful conversation you don't want to miss!
Congressman Beyer was previously on Practical AI episode 271 on May 29, 2024:
AI in the U.S. Congress
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