Video is becoming machine-readable the way text has been for decades, and the unlock is not just replicating the eyes on a situation but the human judgment about it. Alex Gammelgard explains what that opens up across inspection, worker safety, traffic operations, retail and decades of archived game film, and what separates the pilots that scale from the ones that stall.

Attackers and defenders now reach essentially the same AI tools, so what changes is not the balance of power but the speed both sides can move at. Staffan Truvé explains why defending at that speed has to be automated, why the known vulnerabilities you have not patched are the first thing to fund, and why his favorite idea right now is a deception network: a thousand versions of your real system, 999 of them fake, each one a sensor that teaches you how the attacker works.

Blaine Mathieu explains why agentic AI programs stall for strategy reasons rather than technology ones. He breaks down the choice between retrofitting work you already do, which competitors can copy just as easily, and reimagining it, which is harder to copy and more differentiating.

Enterprises keep reading about models. Sharon Goldman argues the story is underneath them, in the systems those models touch: security permissions, usage based billing and its surprise token bills, data that is not ready, and employees told to accelerate who are now told to slow down. She also breaks down the OpenAI and Hugging Face sandbox escape, which was a systems failure rather than a model failure.

Autonomous agents are transforming enterprise operations, but who governs their decisions? Yogita Parulekar explains why AI governance must move beyond models and focus on delegated authority, identity, permissions, and secure-by-design architectures. Learn how leading enterprises are preparing for agentic AI before today's governance practices become tomorrow's weakest link.

Ken Johnston and Bob Rapp make the case that AI governance has to work like engineering. In this episode, they explain why policies trapped in PDFs cannot protect enterprises, how governance as code changes the deployment pipeline, and what it takes to make AI controls automated, testable, and real. If you are still treating governance like paperwork, this conversation will change how you think.

Chris Butler of GitHub makes a bold case that most enterprises are designing AI agents the wrong way. Instead of building agents that mimic job titles, he says leaders should build agents that create specific artifacts inside governed workflows. In this episode, he explains how that shift changes automation, trust, and cross-functional execution, and why the future of agentic AI belongs to teams that focus on outputs, not impersonation.

Christopher Penn reveals how enterprises are using agentic AI to automate workflows, predict customer behavior, improve sales performance, and unlock entirely new revenue streams. From autonomous agents to AI-powered customer simulation, this episode explores what separates AI experimentation from measurable enterprise impact.

What happens when AI decides your company does not exist? Curtis Sparrer reveals the hidden battle for visibility in an AI-first world. From hallucinations that erase brands to the surprising return of press releases, this episode uncovers how enterprises must rethink discoverability, trust, and reputation. If your brand is not showing up in AI answers, it is already losing.

Jonathan Kvarfordt breaks down how AI is rebuilding revenue teams from the inside out. From sales prep and content strategy to agent workflows and AI-driven buyer journeys, he shows what it takes to move from random experimentation to real operational lift. If you want to know how top GTM teams are actually using AI right now, this episode is your field guide.

Deepti Srivastava, founder and CEO of Snow Leopard AI, explains why most enterprise AI still falls short and what it takes to fix it. From Oracle RAC to Google Spanner to AI agents, her work has always centered on one thing: data. In this episode, she shows how accurate, live structured data becomes the missing layer that turns AI from an interesting demo into a real operational system.

Plotly co-founder Chris Parmer reveals how to turn AI into analytics you can trust. Learn why Studio has AI write auditable Python, how role-ready assistants personalize work without leaking data, and how to run agents like a real workforce with owners, logs, and KPIs. See the metrics that matter to leaders, from time to decision to cost per analysis. This is how enterprises out-learn and out-deliver.

Karthik SJ, GM at LogicMonitor, shows how to stop firefighting and start preventing failures. He explains how role-ready assistants cut noise, how managed autonomy keeps humans in charge, and how to run agents like a workforce with owners, logs, and KPIs. Learn the data core that catches smoke before fire and the metrics that make your CFO smile. This is observability that acts.

Jason Williamson shows how to squeeze real intelligence from tiny compute. Hear how MythWorks delivers deterministic, verifiable reasoning on the edge, personalizes assistants to the job, and runs agents like a workforce with owners, logs, and KPIs. Learn the efficiency math that beats GPU sprawl, why managed autonomy keeps humans in charge, and how to measure lift in time to decision, cost per inference, and energy per task. This is AI you can run, trust, and afford.

Harvard’s John Sviokla delivers a sharp wake-up call: most enterprises are giving away their secret sauce—without even knowing it. In this episode, he unpacks how cognitive capital is becoming the new basis of competition, why hybrid AI-native firms are pulling ahead, and what it means to truly “own your intelligence.” If your strategic plan doesn’t include protecting your operational know-how, you may already be behind.

Consultant and AI council builder Bob Mitton shows how to turn generative AI into measurable impact. Hear how he personalizes work with targeted assistants, automates safely with human approvals, and treats agents like a real workforce with owners, logs, and KPIs. Learn the five-day Thumbprint sprint, why guardrails beat gates, and how to move from shadow AI to a governed system your CFO and CISO will trust.

Staffan Truvé explains how to turn AI from a liability into a control system. Learn how his teams personalize defense with outside-in intelligence, automate response with managed autonomy, and anchor every decision to hard KPIs like time to patch and risk reduced. Hear what to lock down, what to test, and how to keep humans in charge while agents do the work.

Lenin Gali shows how to move service from portals to people, with AI agents that resolve issues in seconds, not days. Learn how to personalize help inside Slack and Teams, automate smart handoffs with human approvals, and hit KPIs like ticket deflection, time to access, and cost to serve while keeping security and governance tight. 

Venture partner Shomit Ghose reveals how to scale agentic AI without losing control. Learn where to start, how to guardrail automation, and which KPIs prove real value while your humans stay in charge.

Nitin Gupta, Global Product Manager of AI at Mondelēz International, shows how computer vision, agent based workflows, and firm governance turn pilots into real gains on the shelf. Hear how his teams personalize store execution in near real time, automate smart handoffs with human in the loop controls, and hit KPIs like on shelf availability, forecast accuracy, and waste reduction without losing trust.