How Eric Jorgenson Thinks 30 Years Ahead to Build Companies That Matter in the Age of AI

Eric Jorgenson, CEO of Scribe Media and venture investor, reveals how thinking on a 20-30 year timeline fundamentally changes investment decisions, company building, and personal leverage in an AI-accelerated world. From investing in asteroid mining startups to understanding why most people get the AI revolution wrong, Eric breaks down how to build leverage, develop judgment, and position yourself for the civilization-level changes ahead.

The conversation explores why short-term thinking creates mediocrity while long-term vision enables breakthrough innovation. Eric shares his framework for evaluating startups, explains why energy and consciousness are the real currencies of the future, and demonstrates how AI tools amplify leverage for those who understand fundamental skills. The discussion challenges conventional wisdom about education, productivity, and what it means to contribute meaningfully to human progress.

Key Topics Covered:

• The 20-30 year investment framework and why most opportunities fail this filter

• Why Eric invested in an asteroid mining startup when others called it crazy

• How AI accelerates discovery in physics, biology, and material science beyond information work

• The widening gap between AI adopters and non-adopters in every industry

• Why judgment and taste matter more than technical skills in the AI era

• How to train the next generation when AI can do the execution work

• The difference between learning fundamental skills versus using AI as a crutch

• Applying leverage principles through delegation, automation, and recorded processes

• Why equal opportunity matters more than equal outcomes for civilization

• Viewing consciousness as humanity's core responsibility in the universe

Episode Timestamps:

00:00 - Introduction and Eric's 2025 operating lens
01:41 - The 20-30 year timeframe for investing and life decisions
03:30 - Asteroid mining investment thesis and long-term vision
06:26 - How Eric cultivated the long-term thinking mindset
10:22 - AI as a force multiplier across all technologies
13:54 - How the smartest people are adopting AI differently
17:06 - The thought experiment: training an intern for maximum impact
25:46 - The crisis in education and what students are missing
31:32 - How leverage has evolved and become more accessible
42:11 - Eric's highest leverage activities and what he should be doing more
46:23 - The divergent paths of resourceful versus passive people
50:36 - Why Eric does what he does and his view on consciousness

About Eric Jorgenson:

Eric Jorgenson is the CEO of Scribe Media, a publishing company that helps entrepreneurs and thought leaders write, publish, and market their books. He also runs a pre-seed and seed venture fund investing in long-term technology companies. Eric is best known as the author of The Almanack of Naval Ravikant, a curated collection of Naval's wisdom on wealth and happiness that has reached millions of readers worldwide and been translated into dozens of languages. The book distills years of Naval's tweets, podcast appearances, and essays into a comprehensive guide on building wealth, finding happiness, and living a meaningful life. Eric's deep understanding of leverage and long-term thinking stems directly from his work synthesizing Naval's philosophy.

About Scribe Media:

Scribe Media is a publisher specializing in helping entrepreneurs, executives, and experts transform their knowledge into professionally published books. The company handles the complete book creation process from writing to publishing to marketing, enabling busy professionals to share their ideas without the traditional barriers of book publishing.

How Shopify Is Building The Future of AI Commerce with Andrew McNamaraShopify's Director of Applied ML, Andrew McNamara, reveals how the new Sidekick Pulse and SimGym features are revolutionizing e-commerce for merchants of all sizes. With 15 years of experience building AI assistants—dating back to pre-Siri days—Andrew breaks down how Shopify is using "LLM as a judge" to ensure quality and why "vibe entrepreneurship" is the future of business.Andrew explains how Sidekick has evolved from a simple chatbot into a proactive "AI Co-founder" that can democratize data for small business owners. He shares behind-the-scenes details on Sidekick Pulse, which performs deep research to surface actionable insights (like finding shipping errors that cost sales), and Simgym, a powerful simulator that uses AI shoppers to A/B test store changes before they go live.We also dive into the technical side of how Shopify evaluates these models using statistical rigor and why the ability for merchants to build admin apps with a single prompt is a game-changer for productivity.---Topics Covered- The 15-year evolution of AI assistants from rule-based systems to LLMs- How Sidekick Pulse proactively finds and fixes business-critical errors- Simgym: Using AI shoppers to simulate A/B tests without risking live traffic- The "LLM as a Judge" framework Shopify uses for product quality control- "Vibe Entrepreneurship" and reducing technical barriers for founders- Building custom Admin Apps in seconds using natural language prompts- Real-world examples from Andrew's own maple syrup store- The difference between general chatbots (Copilot) and specialized agents (Sidekick)- How "App Gen" allows merchants to create custom workflows instantlyEpisode Timestamps00:03 - Introduction to Andrew McNamara and his 15-year history with AI01:01 - Comparing early AI assistants (BlackBerry/Samsung) to modern LLMs06:45 - How Sidekick democratizes data analytics for small merchants11:25 - Deep Dive: Sidekick Pulse and proactive business research15:43 - Using "LLM as a Judge" to replace human evaluation at scale18:41 - Generating custom Admin Apps with a single prompt ("App Gen")21:58 - Andrew's personal experience running a Shopify store25:31 - The concept of "Vibe Entrepreneurship" as a North Star26:30 - Using AI to edit online store themes and layouts in real-time37:39 - Simgym: Simulating buyer behavior to predict experiment results42:06 - Why simulation is critical for both small and large enterprise merchants48:04 - The culture of technical depth and passion at Shopify51:34 - Why Andrew has dedicated his entire career to building assistants---## About Andrew McNamaraAndrew McNamara is the Director of Applied Machine Learning at Shopify, where he leads the development of Sidekick and other intelligent merchant features. Previously the Director of the Montreal Research Lab at Microsoft and a key contributor to Bing Chat (Copilot), Andrew has over 15 years of experience building and deploying AI assistants at scale.Shopify is the leading global commerce company, providing trusted tools to start, grow, market, and manage a retail business of any size. It powers millions of businesses in more than 175 countries and offers a unified platform for physical and digital commerce.Resources Mentioned- Shopify Sidekick (AI Commerce Assistant)- Sidekick Pulse (Proactive Research Agent)- Simgym (AI Shopper Simulator)- Microsoft Copilot & Bing Chat- "LLM as a Judge" Evaluation Framework---Partner Links- Book Enterprise Training — https://www.upscaile.com/- Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube

Jason Eubanks on Building Oracel: Raising $30M in 28 Hours to Disrupt the $236B Go-To-Market Tooling Market with AI-Native Sales AutomationJason Eubanks, CEO and Co-founder of Oracel, discusses how the company raised $30 million in just 28 hours—oversubscribed at $40 million—by solving a critical problem in the go-to-market industry. With a $236 billion market opportunity and only a "desert of innovation" since the late 1990s, Aurasell is building an AI-native platform to intelligently automate sales workflows and consolidate the 12-15 fragmented tools that plague modern sales teams. Jason shares how his experience scaling revenue from $1M to $100M+ across five startups—including Twilio (IPO), Meraki (acquired by Cisco for $1.2B), and Harness—directly informed the founding vision of AurasellEpisode Timestamps- 00:00 - Introduction and Jason Eubanks joins the podcast- 00:26 - Why Oracel raised $30M in 28 hours despite initial $40M oversubscription- 01:24 - The "desert of innovation" in go-to-market tooling since the late 90s- 01:42 - History of CRM evolution from mainframe to cloud to niche products- 03:12 - Founding vision: One intelligent GTM sales platform to replace them all- 03:39 - How pain as a CRO across five startups led to Oracel's creation- 05:58 - The X-Ray productivity assessment revealing tool sprawl inefficiencies- 07:59 - Sellers spending 28% of time selling and 70% on manual tasks- 09:03 - First principles AI-native approach with whiteboards in the kitchen- 09:29 - Five key personas: SDR, seller, IC manager, executive, ops team- 12:18 - AI-native architecture: multimodal interface, lakehouse, and 10,000 agents- 14:39 - Unified data model importance for contextualized AI automation- 15:45 - Current hat wearing: product focus and 50% building go-to-market engine- 18:43 - Platform features and customer experience design philosophy- 19:05 - Three wow moments per persona as success metric- 20:39 - Onboarding experience: automatic territory building and customer choice- 21:40 - 10,000 agents discovering ICP, personas, and competitors automatically- 24:07 - Automated account research and value hypothesis creation- 25:34 - Outbound prospecting content generation with propensity scoring- 26:32 - Outbound sequencer integration and email platform plugins- 27:00 - AI voice dialer coming in three weeks with closed-loop automation- 28:47 - What's missing: deep marketing and customer success automation- 30:49 - Ideal customer profiles: startups and enterprises with tool sprawl- 31:30 - Solution for heavily customized legacy systems coming in December- 34:24 - Dynamic change detection layer solving technical debt- 36:23 - Jason's career arc from BMC Software through Harness- 37:09 - Why: helping go-to-market operators solve problems he experienced- 39:55 - Meraki's disruptive cloud-managed network architecture- 41:51 - Three constants: great product builders, important problems, massive markets- 43:22 - Intrinsic motivation as foundation for hiring and culture- 45:31 - Hiring from first job onward to assess character and values- 51:24 - Understanding why someone wanted to work at 14 years old- 53:21 - Importance of formative years for work ethic and intelligence- 55:46 - AI adoption culture: using own product and building agents internally- 56:36 - All employees use AI daily across PMs, engineers, and operations- 59:25 - Ask AI features: analytics dashboards, data enrichment, natural language-

Discover how Anton, one of the most experienced AI and machine learning experts in the industry, discusses his evolution from building matching algorithms at Bright.com to navigating today's AI landscape. With over a decade of experience in large-scale recommendation systems and data processing, Anton reveals how the fundamentals of big data and embarrassingly parallel computing shaped modern AI applications, and why human-centered design is now more critical than ever in building AI-powered products.Episode Timestamps:- 00:00 - Introduction and welcome- 00:47 - Anton's experience at Bright.com and the recruitment matching problem- 03:23 - The big data era, Hadoop, and Spark in the web 2.0 world- 05:00 - Embarrassingly parallel computing and large-scale data processing- 10:00 - How recommendation algorithms work at scale in recruitment- 20:00 - Evolution of the data scientist role over time- 30:00 - Building intelligent matching systems- 40:00 - Understanding user needs and organizational workflows- 50:00 - The shift toward human-centered AI design- 57:30 - Providing pre-filled content and personalization- 58:02 - Anton's vision for the future and human values- 01:01:46 - Closing thoughts on humanity and technologyAbout Anton:Anton is a veteran machine learning and AI engineer with over a decade of experience building large-scale recommendation and matching systems. He played a key role at Bright.com, a two-sided recruitment platform that pioneered transparent scoring algorithms for candidate-job matching. His expertise spans big data infrastructure, recommendation systems, user experience optimization, and the human-centered approach to AI product development.Resources Mentioned:- Hadoop and Spark (big data processing frameworks)- Big data infrastructure and cloud computing platforms- Two-sided marketplace architectures- Recommendation algorithms and matching systems- User workflow analysis toolsPartner Links:- Book Enterprise Training — https://www.upscaile.com/- Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtubeHashtags:#AIAgents #MachineLearningSystems #RecruitmentTechnology #BigData #DataScience #RecommendationAlgorithms #HadoopSpark #AIProductDesign #HumanCenteredAI #LargeScaleML #CloudComputing #AIStrategy #FutureOfWork #TechLeadership #CareerDevelopment

Nick Johnston is the Senior Vice President of Strategic Partnerships & Business Development at Salesforce, where he leads strategic relationships with major technology companies including OpenAI, Anthropic, AWS, Google, IBM, and Workday. In this conversation recorded during Dreamforce 2025, Nick shares how Salesforce closed 12,500 Agentforce deals and navigated the complexities of announcing major partnerships like the expanded OpenAI integration that brings Salesforce's Agentforce 360 directly into ChatGPT. He reveals his unique approach to building win-win partnerships grounded in customer demand rather than competitive positioning.

Key Topics Covered:

• How Salesforce builds customer-driven partnerships with tech giants like OpenAI, Anthropic, AWS, and Google
• The three core hiring values that create high-performing partnership teams: low ego, high curiosity, and grit
• Why uncomfortable conversations are essential for building trust and creating impactful partnerships
• Using AI tools to position partnership proposals and draft joint press releases with strategic clarity
• The Dreamforce partnership strategy and how compelling events drive deal execution
• Career lessons from coaching varsity football wide receivers and celebrating team achievement over personal wins
• Living in Buenos Aires for six months and the value of full cultural immersion for partnership work
• Why getting customer-facing experience early in your career is the best foundation for any role
• The interview question that reveals hero culture versus team players in partnership roles
• Balancing partnership work across multiple departments including product, marketing, operations, and sales
• How human experience will become the ultimate competitive moat as AI automates routine tasks
• The "be great" daily philosophy and applying the same standards to yourself that you set for your team

Episode Timestamps:

03:07 - From college football to coaching varsity wide receivers at Torrey Pines High School in 2006

05:47 - The vibes and trust mentality: lessons from undersized teams that outperform expectations

07:26 - Three core hiring values: low ego, high curiosity, and grit in partnership teams

09:15 - Six months in Buenos Aires learning Spanish through full immersion with Spencer Stuart

12:49 - Customer-driven partnership strategy: building frameworks from market demand to product integration

16:15 - The customer-centric approach at Dreamforce and delivering the Agentforce agenda with partners

18:04 - Using AI to write joint press releases, position partnerships, and create mutually beneficial proposals

21:27 - Career advice for new graduates: get as close to the customer as possible in sales or customer success roles

24:56 - Why human experience and the arts will be the ultimate differentiator as AI automates work

28:02 - Parenting lessons and the "be great" daily motto for building confidence and pushing through challenges

29:06 - Why do you do what you do: achieving hard things in team settings and making family proud

About Nick Johnston

Nick Johnston is the Senior Vice President of Strategic Partnerships & Business Development at Salesforce, where he has spent over 12 years advancing from Customer Success Director to leading strategic technology partnerships. He holds an MBA from UC Berkeley Haas School of Business and a BA with honors in International Relations from UC Davis, where he also played college football. Nick has been instrumental in establishing major partnerships with OpenAI, Anthropic, AWS, Google, IBM, Workday, and other leading technology companies to deliver integrated customer experiences through Salesforce's Agentforce 360 platform.

ransformation and agentic AI.

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Try AI Pals today: http://tavus.io/pals-launch?utm_source=newsletter&utm_medium=email&utm_campaign=theaireportIn this candid conversation with Quinn Favret, and Hassaan Raza, Co-Founders of Tavus, we dive deep into the future of human computing and how AI is learning to communicate like humans. Quinn walks us through their inspiring San Francisco office—a museum of vintage computing that fuels the company's innovation culture.Topics Covered:0:00 — Introduction & Office Tour2:15 — Building an Inspiring Workspace for Innovation5:45 — The Evolution of Human-Computer Interaction (CLI → GUI → Human Computing)8:30 — What is "Human Computing"? The OS for Human-AI Interaction12:00 — The Waltz of Communication: Understanding Turn-Taking, Tone & Body Language15:20 — Tavus Technology: Perception, Understanding, Reaction & Action20:45 — Introducing Tavus Pals: AI Companions That Reach Out to You25:30 — Real-World Impact: The AI Santa Story & Accessibility30:15 — Ethical AI: Human-First Design & Responsibility35:00 — The Future of Work: Invisible Interface & AI Coworkers (10-20 Year Vision)42:30 — Addressing Job Displacement & Automation47:00 — Building an International, Culturally Diverse Team52:15 — What Makes a Great Tavus Hire: Passion, Craft & Opinions57:45 — Employee Challenges That Changed Company Direction62:00 — The "Why Do You Do This?" Question & Personal Motivations67:30 — Closing Remarks & GratitudeKey Takeaways:Human computing is the next frontier: machines that understand you instead of you learning to understand machinesEffective communication involves far more than words—tone, timing, facial expressions, and body language all matterTavus Pals represent a new category of AI application: emotionally intelligent, proactive, and truly conversationalDiversity of perspective—cultural, generational, educational—is critical to building AI that works for everyoneThe future workplace will have AI coworkers that feel as natural to interact with as human colleaguesTimestamps & Chapters:Vintage Computing Culture & InnovationThe Evolution of Computing InterfacesHuman-Centered AI Design PhilosophyReal-Time AI Perception & UnderstandingTavus Consumer Products & APIEmotional Intelligence in AIEthical Considerations & ResponsibilityFuture of Work & The Invisible InterfaceBuilding an International TeamHiring for Passion Over BackgroundLegacy & ImpactWe explore conversations with founders, technologists, and innovators shaping the future. This episode features Quinn Hassan discussing how Tavus is reimagining human-computer interaction through emotionally intelligent AI.#AI #Tavus #HumanComputing #FutureOfWork #AICompanions #Innovation #TechPodcast #FounderInterview #Startups #EmotionalIntelligence

How a Former Startup Founder (Nancy Xu) is Building the Future of AI Agents at Salesforce Agent ForceJoin us for an insightful conversation with a Salesforce Agent Force leader who previously founded Moon Hub and holds a PhD in Computer Science from Stanford. In this episode, Nancy Xu reveals her unconventional hiring strategies, including asking candidates "what tabs are open in your Chrome browser," and shares why relentless curiosity is the top signal she looks for when building AI teams. Discover how she transitioned from startup founder to enterprise AI leader while maintaining a culture of trust and autonomy.Nancy Xu breaks down the future of work with AI agents, explaining how we'll all transition from "producers" to "directors" as agent orchestration becomes central to every role. Learn about Salesforce's trust layer for Agent Force, the importance of humans in the loop for iterative agent improvement, and why the next 100 years of AI development represents humanity's greatest opportunity since mapping the world. This conversation offers tactical hiring advice, leadership insights on managing impatience as a strength and weakness, and a compelling vision for how AI agents will transform customer experience roles.Key Topics Covered:Unconventional interview questions that reveal candidate curiosity and passion beyond traditional resumesThe three intangibles to look for when hiring: relentless curiosity, mastery of craft, and passionWhy future roles will focus on "what and why" rather than "how" as AI agents handle executionAgent orchestration frameworks including MCP and ATA for agents working with other agentsThe critical role of humans in the loop for continuously iterating agent objective functionsHow trust operates as the number one value at both Salesforce and startup environmentsLeadership philosophy of hiring great people and giving them autonomy within clear directionManaging impatience as both a greatest strength and weakness in leadershipThe blending of research, product, and engineering roles in AI-native companiesWhy this moment in history is humanity's chance to positively impact the course of civilization through AIEpisode Timestamps:00:00 - Introduction and unconventional hiring philosophy01:42 - The Chrome browser tabs question and looking beyond traditional resumes03:21 - Hiring for curiosity in a world where jobs will transform in two years05:15 - From producers to directors: The future of work with AI agents07:18 - Comparing culture at Salesforce Agent Force vs Moon Hub startup09:28 - Operating from trust: Lessons from Stanford PhD program on autonomy11:02 - Greatest weakness: Managing impatience as a founder turned enterprise leader13:14 - Advice for 21-year-olds: Pursue passion and blend across departments15:54 - Why now is the perfect moment in human history to work on AI17:10 - Closing thoughts on making positive impact through AI developmentAbout the Guest:This episode features Nancy Xu, a product and engineering leader on the Salesforce AgentForce team who previously founded Moon Hub, an AI-powered talent platform. She holds a PhD in Computer Science from Stanford and brings systems thinking and mathematical rigor to building enterprise AI agents. Her work focuses on agent orchestration, trust layers, and enabling humans to work alongside AI at scale.About Salesforce/Agentforce:Salesforce Agent Force is an enterprise AI agent platform that enables businesses to deploy autonomous agents across customer service, sales, and operations. Built with trust as the number one value, Agent Force includes enterprise-grade governance, security, and a trust layer that handles compliance at scale. The platform focuses on agent orchestration, allowing multiple agents to work together while keeping humans in the loop for strategic direction

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Rohit Khanna on AI Agents in Customer Service: How Smarsh Achieved 56% Deflection with Agentforce 360 Platform.

Rohit Khanna, Chief Customer Officer at Smarsh, reveals how AI agents are revolutionizing customer service automation in financial services compliance. In this episode, learn how Smarsh implemented Salesforce Agentforce to achieve 56% deflection rates, 20% productivity gains, and transformed their customer support operations without hiring additional level-one support representatives.

Discover the complete strategy behind deploying AI agents in regulated industries, from building proprietary compliance models to implementing data governance layers that ensure accuracy and regulatory compliance. Rohit shares insider insights on personalizing AI agents (meet "Archie"), managing the transition from chatbots to intelligent agents, and preparing teams for the future of agentic workflows in customer service.

Key Topics Covered:

- AI Agent Implementation

- How Smarsh deployed Agentforce for customer service automation

- Real Results - 56% deflection rate, 20% efficiency gains, 25% faster resolutions

- Financial Services Compliance

- Building AI models for market manipulation, fraud detection, and surveillance

- Data Governance

- Critical frameworks for deploying AI agents in regulated industries

- Personalization Strategy

- Why naming the agent "Archie" dramatically increased adoption

- Future of Work

- From human-in-the-loop to agent-in-the-loop workflows- GenAI vs Purpose-Built Models

- When to use general purpose vs specialized compliance AI models

- Customer Experience

- Balancing automation with trust in financial services

Episode Timestamps:

00:00 - Introduction to Rohit Khanna and Smarsh

02:44 - What is Smarsh? Compliance technology explained

04:13 - Building AI from the inside out: Proprietary vs partnered models

07:33 - Agentforce implementation journey and challenges

12:26 - Results: 56% deflection rate and productivity gains

15:25 - The power of personalization: Why "Archie" matters

18:21 - Trust and data governance in regulated industries

22:11 - Data governance layers and policy management

25:49 - Human-in-the-loop vs agent-in-the-loop

29:10 - Upskilling teams for the AI-powered future

32:11 - Intelligent agents for financial crime detection

About Rohit Khanna:

Rohit Khanna is the Chief Customer Officer at Smarsh, overseeing global customer support, consulting, migrations, managed services, and Smarsh University. With nearly six years at Smarsh, Rohit has led the company's transformation into AI-powered compliance solutions, managing teams across the Philippines, India, Belfast, Costa Rica, UK, and US.

About Smarsh:Smarsh is the leading compliance technology provider for regulated industries, specializing in electronic communications archiving, surveillance, and AI-powered financial crime detection. For 20 years, Smarsh has been the trusted custodian of communications data for major financial institutions worldwide, using proprietary AI models and GenAI agents to detect misconduct, reduce false positives, and ensure regulatory compliance.

Resources Mentioned:- Salesforce Agentforce

- Salesforce Agentforce for Service

- Digital Reasoning (acquired by Smarsh)

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What's your experience with AI agents in customer service?

#AIAgents #CustomerService #Agentforce #Salesforce #ComplianceTechnology #FinancialServices #GenAI #CustomerExperience #AIAutomation #AgenticWorkflows #DataGovernance #FinancialCompliance #CustomerSupport #AIinBusiness #Smarsh

Subscribe to the newsletter — https://newsletter.theaireport.ai/subscribeBook Enterprise Training — https://www.upscaile.com/Salesforce CMO Ariel Kelman reveals how customer-centric marketing, AI agents, and trust shape the future of enterprise technology. Learn leadership lessons from Amazon, MicroStrategy, and building marketing teams that embrace AI innovation at scale.In this exclusive interview recorded at Dreamforce, Ariel Kelman—President and Chief Marketing Officer at Salesforce—shares his journey from data warehouse consultant to leading marketing at one of the world's most influential enterprise software companies. Discover how the "have you talked to customers" philosophy from Amazon's Andy Jassy transformed his approach to B2B marketing, and why trust has become the cornerstone of successful AI agent deployment.Ariel breaks down the evolution of AgentForce, Salesforce's AI agent platform, and explains why enterprise AI requires more than impressive demos—it demands accuracy, security, and customer success at scale. You'll learn practical insights about hiring for intellectual curiosity over technical skills, building transparent resource allocation systems, and why failure is "the inseparable twin sister of innovation."⏱️ TIMESTAMPS:0:00 - Introduction1:03 - From Data Warehouse Consultant to CMO: Career Journey2:50 - Andy Jassy's Customer-First Philosophy at Amazon4:08 - The Foundation of Customer Success in Marketing5:46 - Trust, CRM, AI, and Data: The Four Pillars7:20 - Building Trust as a Marketing Leader8:56 - Introducing AI Agents to Enterprise Customers10:31 - What Trust Really Means in AI12:02 - President + CMO: The Dual Role Explained13:11 - Training Teams Through Inspiration, Not Just Education14:52 - Hiring for Intellectual Curiosity and Humility17:04 - Creating a Culture Where Failure Leads to Innovation18:45 - How Leaders Use AI Daily at Salesforce20:09 - The Joy of Product Marketing20:50 - Why Do You Do What You Do?💡 KEY TAKEAWAYS:Why customer obsession beats technology-first marketing every timeHow to build trust in AI agents for enterprise deploymentThe hiring questions that reveal intellectual curiosity and low egoWhy 95% accuracy isn't good enough for customer-facing AIHow Salesforce uses 17 customer success stories to market AgentForceThe difference between consumer AI and enterprise AI grounded in dataWhy transparency in resource allocation builds team trust🎤 ABOUT ARIEL KELMAN:Ariel Kelman is the President and Chief Marketing Officer at Salesforce, where he leads global marketing strategy for CRM, AI, and enterprise technology solutions. Previously, he held leadership roles at Amazon Web Services, Oracle, and MicroStrategy, bringing over 20 years of experience in B2B technology marketing and sales engineering.📢 RELATED VIDEOS:Mia Jordan, GTM AI Executive at Salesforce (https://youtu.be/pFOAlZNL_U0?si=2BMuatBIpC0biXZ0)Saket Srivastava, Asana CIO (https://www.youtube.com/watch?v=0TryfgNj3D4&t=1s)🏢 ABOUT THIS SERIES:This interview is part of our Dreamforce leadership series, featuring conversations with C-suite executives shaping the future of enterprise technology, AI innovation, and customer experience.#Salesforce #CMO #AIAgents #AgentForce #MarketingLeadership #EnterpriseAI #B2BMarketing #CustomerSuccess #TrustInAI #Dreamforce #TechLeadership #ProductMarketing #CRM #AIInnovation #MarketingStrategy