Practical AI
Articles about Practical AI
Narrative intelligence and the human advantage
As AI reshapes how we work, create, and think about our roles, staying adaptable means understanding not just the technology, but our own stories and identities. Reed Frerichs joins Daniel and Chris to explore narrative intelligence, storytelling, leadership, and personal growth in an AI-driven world. They discuss how entrepreneurs and leaders can use AI tools to navigate changing roles, embrace uncertainty, and develop emotional intelligence along with Reed's “own, author, act” framework.
Open models and the future of Physical AI with NVIDIA
As AI moves beyond the cloud and into robots, vehicles, and other physical systems, new approaches to models, simulation, and inference are emerging. Daniel and Chris are joined by Ming-Yu Liu, Vice President of Cosmos Lab at NVIDIA, who shares his perspective on open models, world models, and the future of physical AI. They explore why open models matter for innovation, how world models can help AI understand and simulate the physical world, and what it could take to build increasingly capable physical AI systems.
From AGENTS.md to Enterprise Deployment
AI agents are moving beyond laptops and prototypes and into enterprise environments where security, compliance, scalability, and reliability matter. Nick Kuhn from VMware Tanzu Platform joins Daniel and Chris to discuss what changes (and what doesn’t) when deploying agents alongside traditional applications. They explore agent build packs, MCP gateways, shared memory, identity, sandboxing, and what enterprises can learn from years of platform engineering.
How to get discovered in AI search
AI search is changing how people discover information and how brands need to think about visibility. Daniel and Chris talk with Liam Dunne and Ben Moore, co-founders of Discovered Labs, about the shift from traditional SEO to AI search, what happens behind the scenes when an LLM generates an answer, and why retrieval and citations don't always tell the whole story. They dig into AI visibility, Reddit strategy, query fan-out, representation in model weights, and consensus.