Applied Intelligence

Keith Richman

The go-to show for business leaders navigating AI adoption in the real world. Host Keith Richman talks with operators, founders, and business leaders who are actually deploying AI—exploring what works, what doesn't, and how to bridge the gap between AI's capability and practical implementation. Smart, grounded, actionable.

  1. Jul 31

    Why "Mr. Paranoid" Is Right About AI Security

    In this episode of Applied Intelligence, Keith Richman sits down with Polygraf CEO Yagub Rahimov to uncover the hidden cybersecurity risks of everyday AI adoption. Dubbed "Mr. Paranoid," Rahimov explains how seemingly harmless tools—like AI meeting note-takers, QR codes, or even emojis—can be weaponized to expose contextual intelligence, hijack AI agents, and bypass traditional privacy regulations like HIPAA and GDPR. The conversation explores real-world cautionary tales, from $17,000 accidental Gemini API bills to job candidates using undetectable AI teleprompters to cheat in interviews. Rahimov outlines a practical framework for mitigating these risks, advocating for robust, edge-based access controls and in-line behavioral guardrails that secure data without disrupting workflow or AI performance. Timestamps: Chapters 00:00:00 Introduction: The AI Interview Cheating Epidemic 00:00:35 Mr. Paranoid: Why Optimism Requires Seeing the Negative 00:01:59 The Hidden Dangers of QR Codes and Emojis 00:02:55 Contextual Intelligence: The Mosaic That Exposes Everything 00:04:39 Paying AI Twice: Your Data and Your Money 00:05:37 Building Your AI Stack: The Six Critical Variables 00:08:05 The Claude Code Problem: Are You Exposing Yourself? 00:09:19 AI Behavioral Control: Allow, Deny, Fix, Proceed 00:13:23 The Google Gemini API Disaster: A $17,000 Lesson 00:14:57 Meeting Note Takers: Your Data Goes to 7 Different Providers 00:17:01 Deepfakes and Voice Cloning: The 3-5 Second Problem 00:18:21 Meeting Guard: Detecting AI Cheating in Real-Time 00:20:30 The Recruitment Horror Story: 1,200 Candidates, 3 AI Imposters 00:21:33 The CEO Mandate Paradox: Push AI While Managing Existential Risks 00:22:23 The Grammarly Approach: Contextual Privacy for Every User 00:23:44 If You Don't Own Your Data, Someone Else Owns You 00:25:03 The Future Is in Our Control #ArtificialIntelligence #Cybersecurity #MachineLearning #DataPrivacy #TechPodcast #DataSecurity #Deepfakes #AITrends #BusinessTech #tech

  2. Jul 21

    AI Expert Warns of the AI Hacking Epidemic

    In this episode of Applied Intelligence, host Keith Richman sits down with cybersecurity expert David Campbell. They dive deep into the real-world dangers of artificial intelligence, exploring everything from prompt injections to malicious autonomous agents and the growing threat of "shadow AI" in corporate networks. David breaks down how businesses can safely deploy AI by maintaining visibility and implementing classic cybersecurity frameworks, explaining why rushing into AI adoption can lead to massive vulnerabilities. They also discuss AI red teaming, the changing landscape of digital threats, and practical tips for securing your personal and business data. Whether you're a Fortune 100 executive or a small business leader, this episode offers grounded, actionable advice to prevent a dark AI future while safely unlocking its potential. Timestamps: Chapters 00:00:00 Introduction: The AI Hacking Epidemic 00:00:29 The Robotics Capital Challenge and Real-World Model Training 00:01:45 How Screwed Are We? The Doomer Perspective on AI Security 00:03:20 AI Alignment: The Helpful vs Harmless Paradox 00:04:30 Cybersecurity Education: Why Offense Makes Better Defense 00:06:31 What Is AI Red Teaming and Why It Matters 00:09:14 The BIC Framework: Behavior, Identity, and Controls 00:10:18 Shadow AI: The Visibility Crisis in Enterprise 00:12:13 Securing Agentic Systems: The OpenClaw Example 00:14:12 The Speed vs Security Tradeoff 00:17:40 Model Selection and Universal Jailbreaks 00:20:21 Open Source Models and the Pickling Threat 00:21:36 Insider Threats: From Token Drain to Data Exfiltration 00:24:02 The Scale of Modern AI Attacks 00:26:23 Practical Security for Small to Medium Businesses 00:28:43 The Scale AI Experience: Building AI Security from Scratch 00:31:30 Government Preparedness and Policy Education 00:33:31 Choosing Vendors and Avoiding the All-in-One Trap 00:35:00 Personal Tech Stack: How an AI Security Expert Protects Himself #ArtificialIntelligence #CyberSecurity #MachineLearning #BusinessStrategy #Podcast #TechNews #RedTeaming #Technology #DataSecurity #TechTrends

  3. Jul 8

    The Invisible AI Failures Costing Your Business

    In this episode of Applied Intelligence, host Keith Richman sits down with Moritz Sudhof, Co-founder and CEO of Bigspin AI, to uncover the hidden realities of enterprise AI adoption. Moritz introduces the concept of "invisible failures"—when AI errors go completely undetected by users and dashboards—and explains the rising phenomenon of "tokenflation," where AI tokens yield less raw work output over time. They explore why user behavior dictates AI success far more than raw model capability, how to measure true AI ROI beyond basic metrics, and the upcoming challenge of verifying output in a future dominated by AI agents talking to other AI agents. If you want to understand how to effectively manage, measure, and deploy AI in your business without flying blind, this conversation is a must-watch. Chapters 00:00:00 Introduction: The Research Experiment That Went Rogue 00:00:50 What Are Invisible Failures and Why 79% Go Undetected 00:02:04 The User Experience Paradox: Sometimes Brilliant, Sometimes Terrible 00:04:08 The 3% Power Users: Augmentation vs Delegation 00:07:00 The Impossible Question: Defining Good in AI Coaching 00:14:56 Tokenflation: When Your AI Budget Buys Less Over Time 00:19:49 Beyond Productivity: Measuring Compounding Value and New Capabilities 00:23:04 The Slot Machine Problem: Why Passive Users Fail 00:25:57 The Token Maxing Trap: Why Spending Millions Doesn't Guarantee Results 00:27:11 Who Should Lead AI Transformation: Not Your Tiger Team 00:30:21 The Observability Challenge: Mining Session Transcripts for Truth 00:33:33 Designing Interactions, Not Just Capabilities 00:35:02 The Hidden Data Asset: Learning from Every Session 00:36:48 The Agent-to-Agent Future: Who Watches the Watchers 00:37:38 The Verification Bottleneck: Why Creation Outpaces Review 00:42:59 The Scientific Integrity Incident: A Cautionary Tale 00:44:29 Flying Blind: The Cost of No Visibility 00:45:33 The Future Stack: LLMs Watching LLMs 00:47:18 The Attention Economy: Directing Human Judgment Where It Matters #AI #ArtificialIntelligence #EnterpriseAI #FutureOfWork #TechTrends #MachineLearning #BusinessTech #Innovation #TechLeadership #SoftwareEngineering

  4. Jun 16

    The Hidden Threat of Shipping AI Code Faster

    As AI tools like Claude and Codex democratize software development, writing code has never been easier—but deploying reliable code has never been harder. In this episode of Applied Intelligence, host Keith Richman sits down with Pramin Pradeep, founder of Botgage, to explore the hidden dangers of AI-generated "shadow code" and why traditional QA frameworks are breaking under the pressure of hourly release cycles. Pramin breaks down the shift from manual testing to agentic, end-to-end behavioral testing, sharing practical frameworks for budgeting and managing QA in a fast-paced environment. They also discuss his personal AI tech stack, the future of single-screen software interactions, and how businesses can maintain release confidence without breaking the bank. Smart, grounded, and actionable advice for any team building with AI. Chapters 00:00:00 Introduction: The Shadow Code Problem 00:00:50 The Problem-First Approach to Development 00:01:37 The New Era of Code Creation and Testing 00:03:46 From Unit Testing to End-to-End: The Testing Gap 00:05:42 The Speed Problem: Releasing Every Hour 00:09:07 Budget and Time: The QA Investment Question 00:10:12 Shadow Code: Not Bad Code, Dangerous Code 00:10:58 Why AI Can't Just Fix Everything 00:13:15 The 50K Rule: Budgeting for Robust QA 00:15:11 The Future: Single Screen and Agentic Testing 00:16:55 Multi-Model Strategy and Monitoring #AI #SoftwareDevelopment #Coding #QualityAssurance #TechPodcast #BusinessLeaders #ArtificialIntelligence #SoftwareEngineering #AITesting #SaaS

  5. May 28

    The Truth About AI Employees & Agentic Workers

    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

  6. May 20

    SEO is Dead: The Rise of Answer Engine Optimization

    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

  7. May 12

    Processing Trillions of Real-World Data Points with AI

    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

  8. Apr 20

    The AI Testing Framework Every Business Needs (But Few Use)

    Keith Richman sits down with Hamel Husain, machine learning engineer and founder of Parlance Labs, to demystify AI evaluations (evals). Hamel breaks down why generic AI testing metrics fall short and how businesses can actually measure, debug, and improve their AI applications in the real world. They explore the pitfalls of simply slapping a chatbot on an existing product, the importance of iterative error analysis, and why starting simple with the most powerful models beats reaching for immediate complexity. Whether you're an executive fielding AI mandates or a developer building the stack, Hamel shares actionable advice on how to stop building the wrong things faster and start deploying AI that truly moves the needle. Chapters 00:00:00 Introduction: Why AI Testing Matters More Than You Think 00:01:52 What Are AI Evals and Why Every Business Needs Them 00:04:03 The Generic Metrics Trap: Why Off-the-Shelf Testing Fails 00:11:57 The Two Biggest Failure Modes in AI Implementation 00:13:37 Moving Fast vs Being Deliberate 00:15:04 The Slop Problem 00:21:24 Guardrails Done Right 00:23:45 Model Selection Strategy 00:27:25 Build vs Buy: When to Use Consulting vs Internal Teams 00:29:40 The Bootcamp Approach 00:31:19 The Million Lines of Code Myth 00:32:46 Embracing Mistakes and the Experimental Mindset 00:34:33 Personal Tech Stack and the OpenClaw Reality Check #ArtificialIntelligence #MachineLearning #AITesting #TechLeadership #SoftwareEngineering #DataScience #OpenAI #ProductManagement #GenerativeAI #AIEvals

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About

The go-to show for business leaders navigating AI adoption in the real world. Host Keith Richman talks with operators, founders, and business leaders who are actually deploying AI—exploring what works, what doesn't, and how to bridge the gap between AI's capability and practical implementation. Smart, grounded, actionable.

Information

  • Creator
    Keith Richman
  • Years Active
    2026
  • Episodes
    15
  • Rating
    Clean
  • Copyright
    © 2025 Applied Intelligence