Applied Intelligence

In this episode of Applied Intelligence, host Keith Richman talks with Joe Mayberry, Head of AI at SailPoint, about navigating the shift from simple conversational models to the "agentic era." Joe explains why we haven't hit the true AI Industrial Revolution yet and how businesses can practically prepare for a future workforce of autonomous AI coworkers. They dive into the critical need for "agent identity," explaining why AI agents require corporate trust scores, strict governance, and limits just like human employees. Whether you're an enterprise leader managing board expectations or a founder trying to scale, Joe breaks down the actionable steps to build an AI-ready organization, unify siloed corporate data, and safely deploy multi-agent systems. Timestamps 0:00 Introduction: The Agentic Epoch and AI Bosses 0:54 The Agentic Era: Non-Corporeal and Physical Agents 2:28 The Industrial Revolution That Hasn't Happened Yet 5:09 The Three-Step Journey: Data, Enablement, and Governance 9:21 The Complexity Challenge: Big Companies vs. Small Companies 10:00 Agentic Identity: Treating AI Like Humans 11:56 The Dynamic Trust Model for Agents 18:27 Learning from Social Media's Mistakes 20:03 Board Expectations vs. Reality: The AI Strategy Gap 33:09 The Four Essential Board Reports for AI Governance 23:38 Trust as the Competitive Advantage 25:41 The Org Chart of the Future: Human-Directed, Agent-Executed 30:10 Moving Fast vs. Moving Slow: The Startup Advantage 35:43 Joe's Tech Stack: Building on Anthropic Claude 37:36 Scaling the Unscalable: The Future of Personal Expertise 40:30 The Next Generation: Experience vs. Agency in an AI World #ArtificialIntelligence #AI #Business #EnterpriseTech #AIAgents #CyberSecurity #Innovation #FutureOfWork #Technology #Leadership

In this episode of Applied Intelligence, Keith Richman sits down with Graphite founder Marcos Ciarrocchi to explore the massive shift from traditional SEO to AI-driven Answer Engine Optimization (AEO). Marcos explains how Large Language Models (LLMs) and AI agents are changing the way users search, and what this means for both publishers and brands. Learn actionable strategies to optimize your brand for AI consensus, leverage "information gain" to stand out, and structure your website data so AI models can easily cite your products. Whether you're trying to influence ChatGPT, Claude, or Google's Gemini, Marcos breaks down how to build topical authority, track AI citations, and capture high-converting referral traffic in the new agentic search era. TImestamps 0:00 Intro 0:52 How LLMs Changed the Search Journey 1:59 Retrieval, Grounding, and Fresh Data 3:15 What AI Search Means for Brands vs. Publishers 4:32 Authority, Trust, and Spam in AI Search 5:43 The New Search Engine Fragmentation 7:28 How ChatGPT Uses Search to Ground Answers 9:24 “Agent Optimization” and the Future of SEO 9:46 Where Brands Should Start Right Now 11:27 Is AI Search Replacing Google Search? 12:38 Why Off-Site Footprint Matters More Now 13:13 Reddit, YouTube, and Unexpected AI Citations 14:28 How to Build Pages AI Models Can Actually Use 15:08 What Happens When an AI Searches for You 17:03 Citation Rate as a New Marketing KPI 18:37 Consensus, Repetition, and Model Recommendations 19:19 The Modern SEO Content Playbook 20:16 Chunking, Context Windows, and AI-Friendly Content 21:35 Making Product Claims Easy for Models to Understand 22:50 Podcasts, Experts, and Information Gain 24:19 Why Unique Perspective Beats Generic Content 25:23 Interactive Content, Calculators, and Product POV 26:36 Why Brand Personality Matters More in AI Search 28:12 Can Smaller Brands Win in AI Search? 28:40 Topical Authority and Finding Your Wedge 31:12 The Long-Tail Opportunity in Personalized AI Search 33:09 Measuring the Business Impact of AI Search 34:01 AI Referral Traffic and Dark Attribution 36:26 Tools for Tracking AI Visibility 38:46 The Future SEO Job Title 40:12 Which Models Should Brands Optimize For? 42:30 Building a Google Flights MCP Travel Tool 44:33 What Agentic Search Means for Travel and Commerce #ArtificialIntelligence #SEO #AEO #DigitalMarketing #ChatGPT #LLM #BusinessStrategy #MarketingTips #SearchEngineOptimization #TechTrends

In this episode of Applied Intelligence, Keith Richman sits down with Praveen Murugesan, VP of Engineering at Samsara, to explore how AI is transforming physical world operations. Praveen reveals how Samsara leverages massive IoT sensor data to solve complex real-world problems—from catching fleet fuel theft to building smart commercial navigation that dynamically reroutes drivers based on dashcam insights. They discuss the game-changing potential of AI-driven "computer use," how to safely implement internal AI coding tools without breaking production, and why AI is finally democratizing data analysis for non-technical operators. If you want a grounded, actionable look at bridging the gap between AI hype and enterprise-scale deployment, this conversation delivers. Chapters 00:00:00 Introduction: AI at Scale with Samsara 00:00:45 Computer Use: The Most Contrarian AI Take 00:04:52 Empowering Engineers: AI Tools and Guardrails 00:07:49 The Wins: Speed, Prototyping, and Quality 00:10:05 Customer Co-Creation: Solving Fuel Theft with AI 00:15:10 From Sensors to Intelligence: The Fuel Theft Solution 00:16:59 LLMs as Judges: Accelerating Data Labeling 00:19:36 Commercial Navigation: Waze for Enterprise 00:23:24 Predictive Operations: The Future of Strategic Planning 00:26:51 Democratizing Expertise: From Specialists to Superhumans 00:29:36 The New Reality: PMs Shipping Code, Designers in Production 00:30:30 The AI Stack: Blessed Models and Cost Management 00:32:42 The Hidden Value: Physical World Data at Scale 00:35:38 What's Overhyped: Security Fears and the Positive Lens #ArtificialIntelligence #AI #MachineLearning #IoT #EnterpriseAI #DataScience #Engineering #TechPodcast #Innovation #SoftwareDevelopment