AI Tool Report Live

In this episode, Michael J. Domanic, VP and Head of AI at UserTesting, reveals how he drove 70%+ weekly AI adoption across the entire company — turning UserTesting into one of the most AI-mature enterprises in the market. Michael shares why most enterprise AI rollouts fail, and the exact playbook he used to get hundreds of employees building custom GPTs and integrating AI into their daily workflows.Michael breaks down how UserTesting moved from Phase 1 (culture change and grassroots adoption) to Phase 2 (agent orchestration and scaled automation), how he built the governance frameworks that let teams experiment safely without creating chaos, and why the companies that treat AI adoption as a culture problem — not a technology problem — are the ones winning. He also shares his honest take on why AI projects consistently miss expectations and what leaders need to do differently in 2026.Key Topics Covered- How UserTesting achieved 70%+ weekly AI adoption across the entire organization- Why most enterprise AI projects fail to meet expectations — and the root causes leaders miss- How employees built hundreds of custom GPTs for internal workflows without a top-down mandate- The Phase 1 to Phase 2 transition: from culture change to agent orchestration- Building AI governance frameworks that enable experimentation without creating risk- Why treating AI adoption as a culture problem (not a tech problem) is the key to success- How to get executive buy-in for enterprise-wide AI transformation- What "AI maturity" actually looks like inside a real company- Michael's predictions for how agentic AI will reshape enterprise operations- The skills leaders need to drive AI adoption in their organizations*Episode Timestamps*00:00 - Introduction and welcome01:31 - Michael's career background and life journey08:08 - Why AI transformation is about creativity, not technology10:43 - Hiring the right AI transformation leaders14:07 - Building Centers of Excellence for AI17:36 - What UserTesting does and Michael's role32:55 - Achieving 70%+ AI adoption across the company35:41 - How employees built hundreds of custom GPTs39:16 - OKR methodology and governance frameworks43:50 - Creativity as the fundamental skill for future work48:39 - Phase 2: Agent orchestration and advanced AI56:46 - Outlook: Optimism about AI's future impact59:27 - Closing: How honest conversations drive progressMichael's Socials:LinkedIn — https://www.linkedin.com/in/michaeldomanic/Partner LinksBook Enterprise Training — https://www.upscaile.com/Subscribe to our free newsletter — https://newsletter.theaireport.ai/subscribe

This week: OpenAI's Pentagon deal sparked the #QuitGPT movement with 2.5 million supporters, Anthropic got labeled a supply-chain risk by the DOD, AI-driven layoffs hit Oracle and Block hard, NVIDIA teased its biggest GTC yet, and Apple revealed a $599 AI laptop.Key Topics CoveredOpenAI's classified Pentagon deal sparks #QuitGPT revolt with 2.5M supporters and 295% surge in ChatGPT uninstallsPentagon labels Anthropic a supply-chain risk; OpenAI and Google employees rally behind Anthropic in courtOracle eyes 30,000 layoffs and Block cuts 40% of workforce as AI replaces jobs at scaleNVIDIA GTC 2026 preview: $26B open-source investment, new inference chip, and enterprise AI platform expectedApple announces rebuilt Siri with Google Gemini and the $599 MacBook Neo AI laptopEpisode Timestamps00:00 — OpenAI's Pentagon Deal and the #QuitGPT Revolt01:00 — Pentagon vs. Anthropic: The Supply-Chain Risk Showdown02:00 — AI Layoffs Hit Oracle, Block, and Atlassian03:00 — NVIDIA GTC 2026: The Super Bowl of AI04:00 — Apple's Mass-Market AI PlayAbout The AI WhyThe AI Why with Liam Lawson covers enterprise AI — how it's being implemented at scale, and why the people building it do what they do. New episodes every Tuesday (weekly news in 5 minutes) and Thursday (hour-long interviews with founders and C-suite execs).Our LinksFree Newsletter — https://newsletter.theaireport.ai/subscribeWebsite — https://www.theaireport.aiLiam's LinkedIn — https://www.linkedin.com/in/not-the-f1-driver-liam-lawson/Book Enterprise Training — https://www.upscaile.com/

How Coursera's VP of Enterprise Is Reskilling 7,000+ Organizations with AI — Anthony Salcito on the 234% GenAI Enrollment Surge, Verified Skills Paths, and the Human Side of AI TransformationAnthony Salcito is the Vice President of Enterprise at Coursera, where he leads a $239 million enterprise business partnering with over 7,000 organizations globally. In this episode, Anthony breaks down why GenAI enrollments on Coursera have surged 234% year over year, why 84% of leaders plan to increase AI investment while only 38% say their teams are ready, and what it actually takes to build AI skills that stick inside an organization.From his 20+ years leading Microsoft's global education efforts to his work at Nerdy and Varsity Tutors, Anthony shares his framework for human-first AI transformation. He explains how Coursera is using AI-powered coaching, role play simulations, verified skills paths, and Course Builder to close the enterprise AI skills gap — and why critical thinking, not just prompt engineering, is the skill that matters most.Key Topics Covered:The 234% year-over-year surge in GenAI enrollments on Coursera and what is driving global demandWhy 84% of leaders plan to increase AI investment but only 38% say their teams are readyCoursera's verified skills paths and how they provide stackable, demonstrable AI credentialsThe role of AI-powered Coach in improving course completion — 94% report improved experience, 9.5% higher quiz pass rateHow Course Builder lets enterprises customize world-class AI content from Google, Anthropic, and Microsoft for their specific business contextWhy critical thinking enrollments grew 185% alongside technical AI skillsThe four phases of technology adoption: displacement fear, skills erosion, complacency, and true transformationHow gamification and role play simulations make enterprise AI learning stickCoursera's integration with ChatGPT and the future of learning in the flow of workWhy the shift from "4 years for 40 years" to "40 for 4" demands lifelong micro-credentialingEpisode Timestamps:00:00 - Introduction and Anthony Salcito's background01:42 - Growing up in the Bronx and how technology became a catalyst04:10 - Teaching Girl Scouts Visual Basic in 1995 and the education spark06:18 - The through line from Microsoft to Nerdy to Coursera Enterprise08:24 - Walking into Coursera's $239M enterprise business — what surprised him11:22 - 234% GenAI enrollment growth and 15 enrollments per minute13:57 - Verified skills paths and proving AI competency beyond course completions16:19 - Why critical thinking grew 185% and how schools need to change20:41 - Hard skills vs. soft skills and the competency-based education gap23:58 - What makes AI learning stick: personalization, mixed modality, and Coach27:40 - Coach results: 94% improved experience and the power of gamification31:55 - Live role play: pitching AI reskilling to a 1,000-person construction company36:24 - The four phases of technology adoption and why complacency is the biggest threat40:25 - Human-first AI transformation and why people-centric companies win43:39 - How Coursera keeps up with fast-moving AI content creators46:20 - The 3-5 year vision: micro-credentials, learning in the flow of work, and ChatGPT integration50:55 - Why Anthony does what he doesAbout Anthony SalcitoAnthony Salcito is the Vice President of Enterprise at Coursera, where he leads the company's enterprise business serving over 7,000 organizations worldwide. Before joining Coursera, Anthony spent 20+ years at Microsoft leading global education efforts, visiting over 80 countries and nearly 3,000 classrooms. He also served in leadership roles at Nerdy and Varsity Tutors and chairs the nonprofit Network for Teaching Entrepreneurship.

Stripe Solves AI Billing, Nvidia's $30B OpenAI Exit, GPT 5.4 Launches with Computer Use, and OpenAI's Safety ReckoningThis week on AI News in 5 by The AI Report, Liam Lawson breaks down four major stories reshaping the AI industry. From Stripe's new billing infrastructure for AI companies to Nvidia's $30 billion investment in OpenAI that may be its last, GPT 5.4 beating 83% of industry professionals, and OpenAI facing a safety crisis after failing to alert law enforcement about a dangerous user.These stories signal a shift in how AI companies monetize products, how the biggest AI labs will fund themselves through public markets, and what safety obligations come with deploying AI at scale. Whether you are building AI products, investing in the space, or deploying enterprise AI, this episode covers the developments you need to know.Key Topics CoveredStripe's new AI billing feature that passes through LLM token costs to customers with automatic markupHow Stripe's tool integrates with third-party gateways like Vercel and OpenRouterNvidia's $30 billion investment in OpenAI as part of the $110 billion funding roundWhy Jensen Huang says the private mega-deal era for AI labs is endingOpenAI's $730 billion valuation and the path to IPO alongside AnthropicGPT 5.4's native computer use capabilities and 1 million token context windowGPT 5.4 benchmark results showing 83% outperformance versus industry professionals33% reduction in factual errors and 47% token savings in tool-heavy workflowsOpenAI's safety crisis after flagging a dangerous user but never contacting law enforcementSam Altman's pledge to overhaul safety protocols including a direct contact line for Canadian policeEpisode Timestamps00:00 - Introduction to AI News in 501:08 - Stripe solves AI's biggest billing problem02:12 - How 30% automated markup works for agentic workflows02:40 - Why unpredictable token costs threaten AI margins03:17 - Stripe launches its own multi-model gateway03:49 - Nvidia's $30 billion OpenAI investment may be its last04:32 - OpenAI and Anthropic gear up for IPOs04:57 - Inside OpenAI's $110 billion funding round and $730 billion valuation05:57 - GPT 5.4 launches with native computer use06:54 - GPT 5.4 benchmarks crush 83% of industry professionals08:55 - OpenAI flagged a dangerous user but never called police09:46 - Sam Altman pledges safety protocol overhaul10:34 - When does a safety flag become a legal obligationResources MentionedStripe AI billing and cost pass-through featureVercel and OpenRouter third-party gateway integrationsNvidia Vera Rubin inference and training systemsOpenAI GPT 5.4 with native computer useChatGPT, Codex, and OpenAI APIChatGPT for Excel add-onMorgan Stanley conference (Jensen Huang keynote)Partner LinksBook Enterprise Training — https://www.upscaile.com/Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube#AINews #GPT5 #OpenAI #Nvidia #Stripe #AIBilling #JensenHuang #SamAltman #EnterpriseAI #AISafety #AIAgents #ComputerUse #LLM #AIInfrastructure #TokenCosts

In this episode, Christian Lund, Co-Founder of Templafy, reveals how the company built an AI-powered instruction and orchestration layer that helps over 800 enterprise customers — including KPMG, IKEA, and BDO — generate millions of compliant, on-brand business documents 100x faster. Christian shares why the real defensibility in AI isn't the model itself, but the mid-layer that tells the model exactly what to do. Christian breaks down how Templafy turns a simple 8-word user prompt into a 30-page AI instruction book, how their orchestration layer ensures consistent, high-quality outputs across millions of documents, and why enterprises that tried to build AI solutions internally ended up coming back to purpose-built tools. He also shares his honest take on whether AI is a force for good, what skills knowledge workers need to survive, and what he's teaching his three kids about working in an AI-first world. Key Topics Covered - How Templafy's AI instruction layer turns 8-word prompts into 30-page agent briefs - Why the orchestration mid-layer between users and AI models is the most defensible position in enterprise tech - How a Big Four accounting firm became Templafy's very first customer - The transition from rules-based automation to AI-first document generation with agents - Why enterprises took surprisingly long to move from AI toys to enterprise-grade tools - How Templafy integrates with Microsoft 365, Salesforce, and Copilot without getting swallowed by the SaaSpocalypse - The only 2 skills knowledge workers need to stay relevant: setting direction and validating output - Why brand and thought leadership are more important than ever for SaaS companies in 2026 - How BDO Canada saved $1.65 million in one year using Templafy's document automation - Christian's investor perspective on VC moonshots vs. real businesses that generate EBITDA **Episode Timestamps** 00:00 - Introduction and what problem Templafy solves 02:01 - The origin story: from consultants with no product to enterprise SaaS 04:18 - Why finance, law, and pharma became the core customer segment 05:41 - How a Big Four firm became the first customer during the cloud transition 09:02 - What makes a company good at adopting new technology 11:00 - How Templafy sits on top of Microsoft 365, Salesforce, and Copilot 11:37 - Surviving the SaaSpocalypse and finding the new world order 17:08 - Growth in the AI era and why enterprise demand took longer than expected 21:16 - Inside the boardroom: where Templafy fits in the AI landscape 23:31 - The recipe vs. cookbook analogy: how instruction books power AI agents 28:38 - How to become defensible when every company has the same AI models 31:58 - Why humans are more important than ever in enterprise sales 35:11 - The only 2 skills left for knowledge workers 35:52 - Educating children in the age of AI 40:01 - Christian's journey from CEO to CPO to CMO to co-founder 41:17 - Why brand and trust are hyper important in 2026 45:11 - B2B vs. B2C: Templafy's enterprise focus and how it compares to Gamma 49:21 - Christian evaluates the podcast's business model as an investor 54:57 - Is AI a force for good? Christian's honest answer 57:32 - Why do you do what you do? Christian's Socials: LinkedIn — https://www.linkedin.com/in/christianlundcph/ Partner Links Book Enterprise Training — https://www.upscaile.com/ Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube

OpenAI just raised $110 billion — the largest funding round in Silicon Valley history. Meanwhile, the Pentagon is threatening to blacklist Anthropic over AI safety limits. This is the biggest week in AI news — here's everything you need to know.In this episode of The AI Report Podcast, we break down the 5 biggest AI stories from the week of February 23–27, 2026:

Upscaile Partnered with Stanford to Teach a 90-Minute AI for Creativity Masterclass — From Prompting Fundamentals to Full AI Short Film ProductionIn this full Stanford class recording, Arturo Ferreira walks students through the complete creative AI workflow — from foundational prompting techniques to producing a short sci-fi film using only AI tools. The session covers everything from how tokenization and probability engines actually work to building consistent characters and visual styles across an entire production.Arturo demonstrates how he created a multi-character, fully narrated sci-fi short film in just 48 hours using ChatGPT, Sora, Runway ML, 11 Labs, and Final Cut Pro. Students follow along with hands-on exercises, learning the exact prompting frameworks used to go from basic one-line prompts to production-quality AI video output.Key Topics CoveredThe difference between artificial intelligence, machine learning, deep learning, and generative AIWhy AI is a probability engine, not a thinking machine, and why that matters for promptingThree pillars of effective prompting: clarity, context, and specificityHow tokenization works (word-based, character-based, and phrase-based)Using temperature settings to control AI creativity and determinismHashtag prompting technique to create signposts and organize complex promptsRetrieval Augmented Generation (RAG) for uploading references and refining outputTree of Thought technique for generating multiple creative options simultaneouslyCharacter Lock, Style Lock, and Camera Controls for visual consistency across scenesBuilding a complete AI short film workflow from storyboard to final edit in 48 hoursEpisode Timestamps00:00 - Introduction and course overview at Stanford04:18 - How smart is AI? Why AI is fast, not smart06:20 - Tokenization explained: word-based, character-based, phrase-based07:40 - Hallucinations are a feature, not a bug09:59 - Three pillars of prompting: clarity, context, specificity16:41 - Temperature settings for controlling AI creativity21:46 - Retrieval Augmented Generation (RAG) explained27:00 - Hashtag prompting technique for advanced prompt organization32:52 - Tree of Thought technique for multiple creative solutions38:23 - Hands-on with Sora: creating AI video from prompts52:56 - Hashtag prompting vs basic prompting: side-by-side video comparison1:02:37 - Full AI short film reveal: 48-hour sci-fi production1:05:15 - Character Lock, Style Lock, and Camera Controls1:18:46 - Runway ML workflow for reference-shot-to-video production1:19:31 - Using 11 Labs for AI audio and sound effects1:23:09 - System prompts, custom instructions, and persistent memoryAbout Liam LawsonArturo Ferriera is an AI educator and creative technologist who teaches enterprise-level AI training and creative AI workshops. He partnered with Stanford to deliver this masterclass on AI for creativity, covering prompting fundamentals through advanced AI filmmaking techniques. Liam specializes in making generative AI accessible for creative professionals at all skill levels.About UpscaileUpscaile delivers enterprise AI training designed to help teams integrate generative AI into their creative and professional workflows. The company partners with leading institutions like Stanford to provide hands-on AI education that bridges the gap between technical capability and practical creative application.Resources MentionedChatGPT (OpenAI)Sora by OpenAIRunway ML11 LabsFinal Cut Pro / iMovie / Adobe PremiereTree of Thought and Chain of Thought prompting techniquesRetrieval Augmented Generation (RAG)Partner LinksBook Enterprise Training — https://www.upscaile.com/Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube#AIFilmmaking #StanfordAI #GenerativeAI #AIforCreatives #PromptEngineering #ChatGPT #Sora #RunwayML #ElevenLabs #AIVideo #AICreativity #AITools #AITraining #Upscaile #ContentCreation

In this episode, Peter Swartz, Co-Founder and Chief Science Officer at Altana, reveals how the company's AI-powered supply chain knowledge graph has helped stop hundreds of millions of dollars in forced labor goods from crossing borders and contributed to some of the largest counter-narcotics seizures in investigators' careers. Peter shares the real-world impact Altana is making across both the public and private sectors.Peter breaks down how Altana's multi-tier supply chain visibility works to trace forced labor cotton through global networks, how dual-use chemicals are being diverted into fentanyl production, and how the platform helps governments and enterprises collaborate to avoid billions of dollars in trade disruptions while saving hundreds of millions in tariff fees.Key Topics Covered- How Altana blocked hundreds of millions of dollars in forced labor goods at U.S. borders- The role of AI knowledge graphs in mapping multi-tier global supply chains- How Altana supports CBP enforcement of the Uyghur Forced Labor Prevention Act- Product passports and how they expedite legitimate goods through customs- The difference between forced labor entering legit supply chains vs. legit goods entering illicit ones- How logistics companies use Altana to prevent their networks from being misused- Proactive vs. reactive approaches to supply chain risk using probabilistic AI models- Scenario modeling for geopolitical disruptions including Taiwan and global conflicts- Saving billions in supply chain disruptions and hundreds of millions in tariff feesEpisode Timestamps00:00 - Introduction and overview of Altana's real-world impact00:41 - Understanding forced labor as a multi-tier supply chain problem03:09 - Hundreds of millions in forced labor goods stopped at borders03:45 - How the AI knowledge graph maps global supply chain connections04:15 - Working with CBP on the Uyghur Forced Labor Prevention Act04:35 - Product passports and expediting goods through customs04:51 - Counter-narcotics and the dual-use chemical problem05:45 - Helping logistics companies stop network misuse06:27 - From alert to action and the system handoff process06:49 - Responsible AI and the role of human-in-the-loop decisions07:33 - Proactive vs. reactive supply chain intelligence08:08 - Scenario modeling for geopolitical disruptions and resiliencyAbout Peter SwartzPeter Swartz is Co-Founder and Chief Science Officer at Altana. He has spoken on global trade, supply chains, and machine learning at the World Trade Organization, the World Customs Organization, the U.S. Court of International Trade, and the National Academies of Medicine. Previously, Peter was Head of Data Science at Panjiva, listed as one of Fast Company's most innovative data science companies in 2018 and later acquired by S&P Global. He holds patents in machine learning and global trade, and completed his education at Yale, MIT, and EPFL.About AltanaAltana is the world's first Value Chain Management System, providing AI-powered supply chain intelligence to governments, enterprises, and logistics providers. The platform is built on a proprietary knowledge graph comprising more than 2.8 billion shipments, tracking over 500 million companies and 850 million facilities globally. Altana covers more than 50% of global trade, making it the most comprehensive and accurate supply chain map available.Resources Mentioned- Altana Atlas platform and AI knowledge graph- U.S. Customs and Border Protection (CBP)- Uyghur Forced Labor Prevention Act (UFLPA)- Product passports for cross-border compliance- Altana's disruption and tariff scenario modeling toolsPeter's Socials:LinkedIn — https://www.linkedin.com/in/pgswartz/Partner LinksBook Enterprise Training — https://www.upscaile.com/

Louis Shulman on Building a 15-Person Newsletter Agency, Taking 300 Sales Calls in One Year, and Why Email Marketing Is the Most Overlooked Growth Channel. Louis Shulman, founder of Orbit Marketing, returns to the show to reveal how he built a newsletter agency from scratch, scaled to 15 team members, and took over 300 sales calls in a single year. In this candid conversation, Louis shares why most B2B businesses are leaving massive opportunities on the table by ignoring email marketing.From running paid ads directly to newsletters to building full-funnel lead generation systems, Louis breaks down the exact playbook his agency uses to generate qualified meetings for clients. He also discusses the mindset shift from chasing revenue to obsessing over client results—and why that change transformed his business.Key Topics Covered:- Why email marketing remains the most overlooked channel for B2B businesses- The newsletter funnel strategy: running Facebook and Instagram ads to newsletter opt-ins- How to use surveys and Go High Level to qualify leads automatically- Transitioning from commodity service provider to fractional CMO- The difference between "founder growth hires" and "clone hires" when scaling- Why vanilla content gets ignored and opinionated writing drives responses- Building systems and playbooks that make agency work scalable- Using AI to overcome entrepreneurial fears and mental blockers- The shift from chasing client count to producing case studies- How Orbit Flows software was built as an internal tool then monetized- Why incentive alignment is the key to delivering client resultsEpisode Timestamps:00:00 - Introduction and catching up with Louis Shulman01:17 - What Orbit Marketing does and how the business evolved03:51 - Why every B2B business should have an email presence05:13 - Converting sales call rejections into future clients07:23 - Training writers to create opinionated, high-converting content08:47 - B2B vs DTC clients and strategic positioning11:16 - The "sawdust" strategy: monetizing byproducts of your business12:28 - Becoming a full-service marketing agency vs staying specialized16:35 - Finding intrinsic motivation beyond revenue growth20:32 - Is the agency model actually scalable?24:46 - Using AI to overcome fears and mental blockers27:06 - Hiring strategies: patience vs startup chaos mode30:31 - Orbit Flows: building software from internal toolsAbout Louis Shulman:Louis Shulman is the founder of Orbit Marketing, a newsletter agency that helps B2B companies generate qualified leads through email marketing and paid newsletter funnels. He also runs Orbit Metrics, a data and analytics consultancy for e-commerce brands spending $2M+ annually on ads, and Orbit Flows, a content creation and project management software built for newsletter teams.About Orbit Marketing:Orbit Marketing is a full-service newsletter agency specializing in B2B lead generation. The company writes and manages newsletters for dozens of clients, runs paid acquisition campaigns to newsletter opt-ins, and builds complete funnel systems using tools like Go High Level. With a team of 15, Orbit Marketing has written several hundred newsletter issues for clients across industries including finance, e-commerce, and professional services.Resources Mentioned:- Orbit Flows (content creation software)- Go High Level (funnel and CRM platform)- Facebook Ads Manager- Kai Bax (agency scaling strategies)- Alex Hormozi (business growth frameworks)Partner Links:Book Enterprise Training — https://www.upscaile.com/Subscribe to our free newsletter — https://www.theaireport.ai/subscribe-theaireport-youtube#NewsletterMarketing #EmailMarketing #B2BLeadGeneration #AgencyGrowth #LouisShulman #OrbitMarketing #NewsletterAgency #PaidAds #ContentStrategy #Entrepreneurship #MarketingStrategy #FractionalCMO #StartupGrowth #AIinBusiness #EmailFunnels

This week in AI and tech: Google removes medical AI overviews after controversy, Anthropic launches Claude for Healthcare, Slackbot becomes a full AI agent, OpenAI signs a $10 billion deal with Cerebras, and Trump announces 25% tariffs on AI chips.⏱️ TIMESTAMPS00:00 Intro00:30 Story #1: Google Pulls Medical AI Overviews04:15 Story #2: Anthropic Launches Claude for Healthcare08:45 Story #3: Slackbot Becomes AI Agent13:20 Story #4: OpenAI's $10B Cerebras Deal18:00 Story #5: Trump's 25% AI Chip Tariff22:30 Final Thoughts

OpenAI launches ChatGPT Health, Amazon takes Alexa+ to the web, and Google reinvents your inbox—6 game-changing AI updates for operators in under 5 minutes.

How Eric Jorgenson Thinks 30 Years Ahead to Build Companies That Matter in the Age of AIEric 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 filterWhy Eric invested in an asteroid mining startup when others called it crazyHow AI accelerates discovery in physics, biology, and material science beyond information workThe widening gap between AI adopters and non-adopters in every industryWhy judgment and taste matter more than technical skills in the AI eraHow to train the next generation when AI can do the execution workThe difference between learning fundamental skills versus using AI as a crutchApplying leverage principles through delegation, automation, and recorded processesWhy equal opportunity matters more than equal outcomes for civilizationViewing consciousness as humanity's core responsibility in the universeEpisode Timestamps:00:00 - Introduction and Eric's 2025 operating lens01:41 - The 20-30 year timeframe for investing and life decisions03:30 - Asteroid mining investment thesis and long-term vision06:26 - How Eric cultivated the long-term thinking mindset10:22 - AI as a force multiplier across all technologies13:54 - How the smartest people are adopting AI differently17:06 - The thought experiment: training an intern for maximum impact25:46 - The crisis in education and what students are missing31:32 - How leverage has evolved and become more accessible42:11 - Eric's highest leverage activities and what he should be doing more46:23 - The divergent paths of resourceful versus passive people50:36 - Why Eric does what he does and his view on consciousnessAbout 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

Building Teams in the Age of AI: How Slack CMO Ryan Gavin is Reshaping the Future of WorkIn this episode, Ryan Gavin, Chief Marketing Officer at Slack, reveals how self-awareness in leadership and the convergence of marketing and product strategy are creating unprecedented opportunities in the agentic era. Learn why employee productivity through AI orchestration is poised to become the fastest accelerator for top line business growth companies have ever seen, and how Slack is positioning itself as the conversational work platform for this transformation.The conversation explores the critical shift from employees as doers to orchestrators, where every team member—from day-one interns to seasoned executives—will manage digital coworkers and AI agents. Discover the product principles driving Slack's approach to agent integration, the social dynamics of working alongside AI teammates, and why the traditional career ladder is being replaced by immediate access to capabilities across development, creative, analytics, and more. The discussion also covers practical frameworks for building exceptional teams, reducing AI adoption anxiety, and why picking the "right" career path matters less than crushing the job you're in.Ryan delivers actionable insights on leadership development through self-awareness, understanding how team members receive feedback and recognition differently, and connecting business opportunities with talent growth. You'll also hear his compelling argument for why marketing must sit between product and sales as a strategic amplifier, not just a message distributor, and what marketers need to do to earn their seat at product strategy and sales planning meetings.Key Topics Covered:Self-awareness as the foundation of effective leadership and team developmentWhy marketing is product and product is marketing in modern B2B organizationsThe shift from doers to orchestrators in the age of AI agents and digital coworkersHow every employee will manage AI teammates from day one across finance, HR, creative, and developmentEmployee productivity as the most underutilized growth lever for businessesSlack's product principles for agent integration: don't make me think and be a great hostReducing AI adoption fear by showcasing capability expansion rather than job displacementSocial dynamics of agent interaction in channels and preserving psychological safetyWhy there is no "right" career path and how to multiply opportunities by crushing your current roleThe changing consumer patterns of information seeking and their impact on business workflowsEpisode Timestamps:00:00 - Introduction and setting the stage02:16 - Knowing thyself: Ryan's journey to leadership self-awareness through family and life experience05:19 - What makes an amazing marketer in 2026 and bridging the marketing-product divide08:43 - From doers to orchestrators: how AI agents give every employee a team from day one11:24 - Designing agents to work like teammates: Slack's approach to intuitive AI integration14:55 - Addressing AI fear: why productivity gains lead to higher expectations rather than job loss18:03 - Advice for the next generation entering an AI-transformed workforce21:49 - Career lesson from delivering papers in 110-degree Chicago heat24:30 - Final question: why Ryan does what he does and the importance of lasting market impact

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 GoogleThe three core hiring values that create high-performing partnership teams: low ego, high curiosity, and gritWhy uncomfortable conversations are essential for building trust and creating impactful partnershipsUsing AI tools to position partnership proposals and draft joint press releases with strategic clarityThe Dreamforce partnership strategy and how compelling events drive deal executionCareer lessons from coaching varsity football wide receivers and celebrating team achievement over personal winsLiving in Buenos Aires for six months and the value of full cultural immersion for partnership workWhy getting customer-facing experience early in your career is the best foundation for any roleThe interview question that reveals hero culture versus team players in partnership rolesBalancing partnership work across multiple departments including product, marketing, operations, and salesHow human experience will become the ultimate competitive moat as AI automates routine tasksThe "be great" daily philosophy and applying the same standards to yourself that you set for your teamEpisode Timestamps:03:07 - From college football to coaching varsity wide receivers at Torrey Pines High School in 200605:47 - The vibes and trust mentality: lessons from undersized teams that outperform expectations07:26 - Three core hiring values: low ego, high curiosity, and grit in partnership teams09:15 - Six months in Buenos Aires learning Spanish through full immersion with Spencer Stuart12:49 - Customer-driven partnership strategy: building frameworks from market demand to product integration16:15 - The customer-centric approach at Dreamforce and delivering the Agentforce agenda with partners18:04 - Using AI to write joint press releases, position partnerships, and create mutually beneficial proposals21:27 - Career advice for new graduates: get as close to the customer as possible in sales or customer success roles24:56 - Why human experience and the arts will be the ultimate differentiator as AI automates work28:02 - Parenting lessons and the "be great" daily motto for building confidence and pushing through challenges29:06 - Why do you do what you do: achieving hard things in team settings and making family proudAbout Nick JohnstonNick 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.Partner Links:Book Enterprise Training — **https://www.upscaile.com/**Subscribe to our free newsletter — **https://www.theaireport.ai/subscribe-theaireport-youtube**

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

#SalesforcePartner 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 servicesEpisode Timestamps:00:00 - Introduction to Rohit Khanna and Smarsh02:44 - What is Smarsh? Compliance technology explained04:13 - Building AI from the inside out: Proprietary vs partnered models07:33 - Agentforce implementation journey and challenges12:26 - Results: 56% deflection rate and productivity gains15:25 - The power of personalization: Why "Archie" matters18:21 - Trust and data governance in regulated industries22:11 - Data governance layers and policy management25:49 - Human-in-the-loop vs agent-in-the-loop29:10 - Upskilling teams for the AI-powered future32:11 - Intelligent agents for financial crime detectionAbout 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)---Book Enterprise Training — [https://www.upscaile.com/](https://www.upscaile.com/)Subscribe to our free newsletter — [https://www.theaireport.ai/subscribe-theaireport-youtube](https://www.theaireport.ai/subscribe-theaireport-youtube)---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

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

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?

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Sign up to Orbit Flows here: orbitflows.com?via=theaireportSummaryIn this conversation, Ethan Reeves shares his journey from a young programmer to co-founder of Orbit Marketing, discussing the evolution of AI and its impact on marketing. He emphasizes the importance of email marketing, trust, and authority in building successful businesses. Ethan also delves into the challenges of navigating the SaaS landscape, the significance of having a structured process in place, and the joy of creating and building products that provide value to users.Chapters00:00 Introduction to Ethan Reeves and His Background02:57 The Evolution of AI and Machine Learning05:36 Founding Orbit Marketing and Its Journey08:43 The Power of Email Marketing and Newsletters11:31 Trust, Authority, and Credibility in Email Marketing14:09 The Role of Personal Stories in Newsletters17:23 Orbit Marketing's Approach to Client Engagement20:13 Building Trust Through Value in Email Communication23:05 The Challenges of Building AI SaaS Products26:02 The Myth of Easy Software Development28:58 The Reality of SaaS Valuations and Market Expectations32:53 Navigating the Vaporware Landscape35:41 Building a Sticky Software Product37:31 The Evolution of OrbitFlows39:22 The Power of Context in AI42:02 Creating Value and Reducing Friction44:28 The Importance of Stickiness in Software46:00 Execution and Vision in Startups49:56 The Pace of Development56:56 Aiming for the Stars: The Future of OrbitFlowsSign up for the newsletter: https://newsletter.theaireport.ai/subscribeJoin the community: https://www.skool.com/the-ai-report-community/about

This week on The AI Report, Liam Lawson is joined by Eric Sui—indie hacker, AI builder, and creator of Agents Playbook—to talk about designing with agents instead of apps.Eric breaks down how he moved from casual GPT-3 experimentation to building structured AI workflows that solve real problems. They dig into agent UX, why many AI tools fall short, and how indie builders can actually move faster by thinking in systems.Also in this episode: • Why agents are more than just automations • How no-code stacks can launch powerful workflows • Lessons from “building in public” on Twitter • How to find product ideas in your own frustration • The future of indie AI projects and agent-led designWhether you're trying to build smarter tools or just want to understand how agents are reshaping what software can do, this episode is packed with insight.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Intro to Eric Sui(01:12) Hacking on GPT-3 Before It Was Popular(03:05) Where AI Products Go Wrong(04:56) User Experience for Agents(06:29) Thinking in Systems, Not Features(08:15) How LLMs Shift the Tool Paradigm(09:53) Launching With No-Code + GPT(11:27) Product Validation as Self-Therapy(13:10) Getting Better Feedback Faster(14:52) Public Building as a Strategy(16:47) Twitter Feedback Loops(19:01) Starting From Zero Audience(20:45) Workflow Design and Mental Models(22:39) How to Think With Agents(24:26) Indiehacking, Investment, and Staying Lean(26:11) Staying Close to Your Problem Space(27:53) Teaching Builders Through Agents Playbook(29:45) What's Next for Eric(31:22) Where to Connect

This week on The AI Report, Liam Lawson is joined by Quinn Favret, co-founder and COO of Tavus, to explore how digital humans are reshaping communication across industries.Quinn shares how Tavus is building AI agents that can engage in real-time, emotionally intelligent conversations—complete with facial expressions, dynamic tone, and personalized responses. The goal isn't just automation. Its presence. And Quinn believes AI might actually help humans connect more deeply, not less.They dig into how Tavus trains its models, where conversational AI is already creating real impact, and what it takes to design an experience that feels human, without trying to be one.Also in this episode: • Why the uncanny valley is a storytelling challenge • What it means to create “brand as soul” • How Tavus enables sales, HR, education, and therapy • Why cultural nuance and context matter more than realism • The role of AI in making communication more accessibleThis is a forward-looking episode for anyone building or using AI to solve problems that rely on trust, attention, and human connection.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Intro and Quinn's Background(01:03) Engineering, Startups, and YC(03:20) From ML Forecasting to AI Video(05:08) How Tavus Got Started(06:21) Launching During COVID(07:28) What Tavus Actually Does Today(09:05) Real Use Cases in Sales, Healthcare, and Media(11:35) Developer Tools and Agentic Systems(12:31) Building Machines That Adjust to Us(14:39) What Makes a Conversation Feel Real(16:46) Cultural and Contextual Communication(17:52) How AI Understands People Over Time(20:45) Could AI Be Better at Talking Than We Are?(23:03) Why AI Therapy Isn't as Crazy as It Sounds(24:40) The Art of Listening and Speaking(28:33) How Quinn Practices Communication in Life and Work(30:41) The Meaning Behind the Tavus Brand(33:29) Tech, Storytelling, and Soul(35:27) UX Gaps and Human Expectations(36:43) Tavus in Context: Not Just Avatars(38:23) What an AI-Powered Future Might Look Like(40:04) Balancing Tech and Humanity(41:19) Quinn's “Why”(44:54) Where to Connect

This week on The AI Report, Liam Lawson sits down with Gordon Wintrob, co-founder and CTO of Newfront, to talk about bringing AI into one of the slowest-moving industries: insurance.Gordon shares how Newfront is redesigning the broker experience with automation and AI—from parsing 200-page policies in seconds to helping HR teams save weeks of work. They discuss building AI tools that clients actually trust, how to manage risk in regulated industries, and why embedding AI into company culture matters as much as the code.Also in this episode: • Why insurance is one of the last big frontiers for tech • What makes a good AI use case in complex workflows • The story behind Benji, Newfront's internal AI assistant • How to foster internal adoption from hiring to hackathons • What regulation and SOC 2 mean for AI innovationThis is a real look at what happens when AI goes beyond chatbots and into core business infrastructure.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Reimagining the Insurance Stack(01:06) Why Insurance Feels So Behind(02:41) How Brokers Work and Where AI Fits(05:08) Founding Newfront With Future Tech in Mind(06:59) Automating Contract Review at Scale(08:49) Working With Startups and Industry Giants(10:19) What It's Like Serving Diverse Client Profiles(12:17) Making Room for Value-Add Conversations(13:28) Key AI Tools: Benji, Gap Analysis, and More(15:29) Why Products Succeed or Fail in Legacy Fields(16:39) Creating a Culture of Technical Curiosity(18:25) From Engineering to Recruiting: AI in the Org(19:30) Equity, Values, and Ownership at Scale(21:50) What Keeps Traditional Brokerages Behind(23:43) AI as a Signal of Operator Leverage(25:22) Who Newfront Builds For(25:56) Staying Compliant While Moving Fast(28:39) Managing Data Risk in a Privacy-Critical Industry(29:01) Vendor Security and SOC 2 in AI Development(30:25) Expanding AI Beyond the Frontend(31:58) CTO Strategy and Time Allocation(32:54) Staying Up-to-Date in a Fast-Shifting Landscape(34:42) Building With Purpose in a Legacy System(36:11) Connect With Gordon

On this episode of The AI Report, Liam Lawson is joined by Frey Chu—a directory builder, SEO educator, and creator focused on building long-term, high-leverage digital assets.Frey shares how he builds directories that actually work, why so many fail to get traction, and how to combine AI workflows, structured data, and strong SEO fundamentals to make evergreen content that ranks and converts.They discuss the real art of choosing a niche, when to enrich data manually vs programmatically, and why directories—when done right—are still one of the best internet business models available.Also in this episode: • What separates real directories from content farms • How to validate a niche with Reddit and Ahrefs • Why LLMs are forcing a rethink of “content quality” • The pros and cons of exact-match domains • Frey's thoughts on time freedom, creative control, and building slow on purposeIf you've ever wanted to build a niche site, test an idea, or launch a project that runs without you, Frey's approach will give you a grounded, tactical blueprint.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) What Makes a Directory Valuable(01:06) Ranking Local Queries With SEO(02:34) The Difference Between Lists and Real Directories(04:32) Why “Directory of Directories” Doesn't Work(05:36) Finding Balance Between SEO and Passion(07:55) Evergreen Niches That Print Cashflow(10:05) Reviewing His Portfolio: Hits and Experiments(11:15) Why Directories Are Still Relevant(12:19) LLMs and the Future of Structured Data(13:38) Monetize First or Learn First?(15:11) Validating Demand Without Guesswork(16:35) Data Enrichment Strategies That Work(17:54) Choosing the Right Stack for Directory Projects(18:57) Quality Markers That Matter in 2025(20:00) High-Consequence Niches With Real Need(21:43) Feedback Loops and Iterating in Public(23:03) Do Domains Still Influence Trust and Ranking?(24:12) Frey's Monetization Framework(25:19) Getting Ready for the Next Phase of LLM SEO(27:50) How Frey Keeps Learning and Evolving(29:04) The People and Projects He's Studying(30:10) The Multi-Skill Nature of Directory Projects(31:54) Long-Term Goals: SaaS, Marketplaces, and Time Freedom(33:44) Why He's Teaching Now(35:52) Where to Find and Follow Frey

This week on The AI Report, Liam Lawson is joined by Peter, a startup coach and product strategist who's helped dozens of early-stage founders avoid one of the most costly mistakes in tech: building before validating.Peter explains why most startup ideas fail not because the tech doesn't work, but because there's no real demand. He shares the “sandwich method” he uses to get honest, useful feedback in discovery calls, and how founders can avoid building in a vacuum.They also explore the role AI is starting to play in validation workflows—and why it can't replace true customer insight.Also in this episode: • Why product-market fit is not a feeling • How to structure conversations to get real signal • The biggest lies founders tell themselves during early validation • How to use AI tools in discovery without getting misled • Why humility might be the most valuable founder skillIf you're building anything new—especially in AI or SaaS—this episode is a sharp, tactical reset.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Misunderstanding Product Validation(01:15) Who Peter Works With and Why(03:40) The Sandwich Method for Better Discovery(06:05) What He Learned From YC and Startup #1(08:12) Founders as Pattern Matchers(10:33) Detecting and Avoiding Bias(13:00) Identifying Real Market Demand(15:18) The Feature Fallacy(17:50) AI Tools vs Product Necessity(19:36) Where AI Can (and Can't) Help(21:44) Advice for Founders on Day Zero(23:50) Why Peter Keeps Coaching(26:04) Where to Find Him

This week on The AI Report, Liam Lawson talks with Nick Jain, former IdeaScale CEO and founder of Content Hurricane, about how he used AI to completely replace traditional marketing and scale his funnel 50x.Nick shares how a $25 AI agent outperformed his in-house team, created content that outranked McKinsey on Google, and helped him build one of the most efficient B2B funnels in SaaS. He breaks down how he did it, why most marketers are missing the shift, and what the future looks like when AI runs most of your company's creative output.Also in this episode: • Building a 90% AI-powered inbound funnel • Why content teams will be replaced, not reskilled • The new role of product managers in an AI-led org • How Content Hurricane scales enterprise-quality assets with no human input • The future of education, work, and intellectual leverageThis is not a “how to write prompts” episode. It's a front-row view into what happens when a founder goes all in on AI and doesn't look back.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Why Content Marketing Is On Its Way Out(01:14) A $25 Agent vs a Whole Marketing Team(02:26) Nick's Moment of Clarity in Amsterdam(03:28) Scaling Content With ChatGPT in 30 Minutes(05:21) Running Mandatory AI Training at IdeaScale(06:45) Who Actually Adopted the Tech(08:17) From Harvard MBA to Startup CEO(09:00) Inside a 90% Automated Marketing Funnel(10:00) What Good Content Actually Means for SEO(12:31) Why Algorithms Are Not the Point(14:13) Tracking True ROI Across All Content(16:13) The Channels That Still Work(17:08) Nick's Favorite Prompt Strategy(18:34) The End of the Content Marketing Role(20:21) CEO Ethics in the AI Age(22:04) Why Sales and Product Still Matter(24:03) The Future of Product Management(25:31) Why Generalists Have the Edge Now(27:05) What Happens to Traditional Education(28:10) The Chips Are Coming: Post-Human Thinking(30:13) How Content Hurricane Operates(32:01) Awareness to Action With AI(33:36) The Simplicity Advantage in UX(35:09) Prompting for Depth, Not Generic Output(36:03) Product With Purpose(36:22) Massive Growth Metrics From the Funnel(38:12) Why Nick Keeps Building(39:05) How to Connect With Him

This week on The AI Report, Liam Lawson is joined by Lindsay Rosenthal, founder of Synnc and one of the leading voices in the B2B creator economy. Lindsay shares how she went from building a presence on LinkedIn to launching a software platform that connects brands and professionals for high-leverage collaborations.She breaks down what's changing in B2B marketing, why creators are becoming critical distribution channels, and how she built and shipped a product without a technical background, leveraging AI tools to move faster and execute smarter.Also in this episode: • The rise of B2B creators and micro-influencers • How Synnc uses AI to match brands and creators • Why a personal brand is now part of your resume • The challenge of balancing content, consulting, and product building • What it really takes to launch a product with limited resourcesIf you're trying to grow on LinkedIn, launch a tool, or find smarter ways to work with AI, this conversation is full of sharp insights from someone doing all three at once.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Why Community is Career Insurance(01:04) AI Meets LinkedIn: What's Happening Now(02:10) B2B Creators Are the New Growth Engine(03:20) Personal Brand as a Strategic Asset(04:36) Imperfect Content Beats AI-Polished Posts(06:13) The Real Voice of B2B: Messy and Human(07:47) What Synnc Actually Does(09:00) How Brands and Creators Use the Platform(11:09) AI Workflow Automation Behind the Scenes(13:14) Why Creator Rates Are Climbing in B2B(14:21) Big Value From Small Audiences(16:20) Winning With Focused Distribution, Not Virality(17:05) Collabs, Testimonials, and Fractional Roles(18:17) Building and Shipping Without a Tech Background(19:31) The Realities of Building in Public(21:05) Why Speed and Timing Matter Most(22:12) Lindsay's Origin Story and Customer Zero(24:03) From Student Podcast to Software Startup(25:57) Spotting Trends and Building Early(28:02) Why Non-Technical Founders Are Winning Now(29:08) Using AI for Product Design and Dev Work(31:07) AI-Powered Matching and Briefing(32:48) Reducing Friction With Smarter Systems(34:03) How Lindsay Balances Multiple Lanes(35:15) Tools, Systems, and Mental Clarity(36:07) The Value of Doing More to Think Better(37:07) Synnc's Next Moves(39:04) What She's Working on Behind the Curtain(41:12) How to Connect With Lindsay and Try Synnc

This week on The AI Report, Liam Lawson sits down with Celeste Yamile, a personal brand strategist who went from selling Fiverr gigs to building a six-figure business, powered by AI and a loyal LinkedIn audience of 20,000+.Celeste breaks down how she bootstrapped her business using content, systems, and ChatGPT. She shares why most creators fail to connect, how she builds content with her own voice, and how storytelling and structure helped her grow faster than she imagined.We dive into her actual workflow, her AI stack, and the mindset shifts that helped her turn monetizable knowledge into a real income engine.Also in this episode: • Her transition from teaching English to coaching creators • Why ChatGPT still beats Gemini and Claude for her content process • What most creators get wrong about authenticity • How she helps clients build their first digital product • The story behind matching her dad's 25-year salary with content and coachingThis is an inspiring and tactical breakdown for anyone building a business with content, community, and AI.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Why “How I” Beats “How To”(01:19) From Mexico to the World: Learning Online at 15(03:20) Making Money With Tutorials and Fiverr(06:01) Building a Foundation With YouTube(08:07) The Daily Habit of Taking Action(09:20) LinkedIn vs TikTok: Building with Intention(11:17) The Truth About Good Content(12:10) How Posting Three Times a Week Changed Her Life(13:13) Studying Top Creators With Clio(14:00) A/B Testing Frameworks for Better Results(16:02) Growing From 300 to 86,000 Impressions(17:02) Storytelling as the Ultimate Growth Lever(18:17) Her Daily ChatGPT Workflow(20:18) Batching Content to Beat Creative Burnout(22:09) Custom GPTs That Sound Like You(24:01) You Don't Need to Sound Like AI—Just Sound Better(26:03) Building a High-Ticket Coaching Offer(28:11) Picking the Right Clients(30:03) Action > Information(33:14) “Buy Back Your Time” by Delegating Right(35:00) Hiring Your First Assistant(36:27) Scaling Toward In-Person Community(37:27) From Corporate Salary to Creator Income(39:01) Why She Wants to Help Others Be Seen

This week on The AI Report, Liam Lawson is joined by Jake George, founder of Agentic Brain, to cut through the noise on AI agents.Jake shares why most AI agent projects fail, what everyone gets wrong about automation, and why a generalist chatbot will never run your sales team. With experience training agents to act like departments complete with project management, team roles, and reasoning models,  Jake walks us through building systems that scale.They talk about how models like o3 and o4-mini are changing the game, why prompting alone won't get you far, and what innovative businesses are doing to stay competitive in the era of reasoning AI.Also in this episode:The myth of the $20 agentWhy sales automation is still mostly garbageBuilding “department-level” agents from scratchThe new consulting model for AI integrationHow to spot companies faking their AI credibilityJake doesn't sugarcoat it. He brings the hard truths and deep insights you need to integrate AI into your workflow.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) The Myth of $20 AI Employees(02:22) Why Even Smart People Struggle With Agents(04:02) o3, o4-mini, and the New Era of Reasoning(06:05) What Makes an Agent Think(07:01) Building Agents That Act Like Teams(08:25) How Models Reshape the Agentic Brain Playbook(10:07) Why Access to Context Beats Raw Intelligence(12:07) Building for Specific Use Cases(14:03) Training AI the Way You Train People(17:11) Department-Level Agent Workflows(18:24) AI Tools That Will and Won't Survive(20:12) Where AI Still Fails in High-Ticket Sales(21:02) What Agentic Brain Offers Clients(23:12) The Role of Context in Cold Outreach(25:17) A New Model for AI Consulting(27:00) Why Real Companies Don't DIY This(29:04) Telling Real and Fake AI Startups Apart(32:27) Pricing Mindsets: $500 vs $5,000 Clients(34:45) Enterprise Expectations and PM Discipline(36:12) Claude's Secret Advantage(38:05) Model Flexibility and Why OpenAI Still Wins(41:13) Balancing Cost and Accuracy(42:11) Where to Connect With Jake

This week on The AI Report, Liam Lawson is joined by journalist Kate Farmer to discuss a growing trend in mental health: the rise of AI therapy apps.Kate recently published an investigative piece on Wysa, Woebot, and other mental health platforms that use AI to simulate therapy conversations. In this episode, she shares what it was like to interact with these tools firsthand, what users are actually experiencing, and why many of these apps are skating a dangerous line between wellness support and clinical treatment.They also explore how these apps bypass regulatory scrutiny, the ethical challenges of relying on AI for emotional support, and how vulnerable users, especially those waiting for real therapists, are often left with few other options.Also in this episode: • Why rule-based AI might be better than LLMs in mental health • How companies use marketing language to dodge legal oversight • The limits of empathy, personalization, and context in AI • What's actually happening with your health data when you use these tools • Why CBT still matters and how to use these platforms safelyThis is a powerful, clear-eyed look at how AI is entering spaces once reserved for humans and what this means for trust, privacy, and care.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Why AI Is Not a Therapist(01:06) Kate's Background and Reporting Focus(04:35) Revisiting AI Therapy Post-ChatGPT(06:13) How Wysa Actually Works(09:45) Empathy, Context, and Their Limits in AI(11:13) Why Intake Matters in Mental Health(13:39) False Personalization in Therapy Apps(14:47) Real User Reactions to Wysa and Woebot(16:28) When AI Becomes a Stopgap for Care(18:05) The Case for Rule-Based CBT Tools(22:08) AI Safety in Mental Health Tools(27:30) Scale vs Support: The Infrastructure Gap(29:25) Avoiding FDA Regulation with Clever Framing(31:06) “Line Skating” and Legal Grey Zones(34:42) The Health Data Economy Behind These Apps(39:00) How Much Your Mental Health File Might Be Worth(43:04) Accepting Flaws When There's No Alternative(44:02) CBT's Real Strengths and Use Cases(45:18) How to Use These Tools Without Risk

This week on The AI Report, Liam Lawson is joined by Matthew Cohn, the founder of Future Flow, to talk about one of the most practical applications of AI today: voice agents.Matt doesn't write code. He's not a machine learning engineer. But he's built a thriving business that automates sales, lead qualification, and customer follow-up using tools like Vapi, N8N, and custom GPT agents. In this episode, Matt explains how he went from university marketing projects to running voice agents that act as round-the-clock sales assistants for real businesses.They dig into the real pain points these agents solve—missed calls, slow follow-ups, and overworked sales reps—and how small to mid-size businesses are starting to catch on.Also in this episode: • What makes a great voice agent prompt • Why prompting is the core skill for non-technical AI builders • How Matt handles imposter syndrome and subcontracting • A breakdown of the orchestration layers and tools he uses daily • What it takes to serve enterprise clients with AI systemsIf you've been curious about AI agents, automation workflows, or what it takes to build a lean, scalable AI business without writing code, this is a must-listen.Subscribe to The AI Report:https://theaireport.beehiiv.com/subscribeJoin the community:https://www.skool.com/the-ai-report-community/aboutChapters:(00:00) Why Speed-to-Lead Still Wins Deals(01:13) Matt's Non-Technical Path to Building With AI(03:45) Early AI Projects and First Use Cases(06:05) Automating Business Docs With ChatGPT(08:14) Leaving the Agency to Go All-In on Future Flow(11:00) Pitching AI Solutions From a Sales Job(13:20) Ghostwriting With GPT and Finding a Real Offer(15:30) How Voice Agents Handle Inbound and Outbound(17:45) The End-to-End Sales Process With AI(20:00) End-of-Call Reporting and CRM Automation(23:00) The Tools Behind It All: Vapi, N8N, GoHighLevel(25:00) Leveraging Subcontractors to Scale(28:00) Building With Confidence as a Non-Engineer(30:30) Thinking Bigger: Serving Enterprise Clients(33:00) Advice for Non-Technical AI Builders(36:00) Start With Prompting, Then Automate(39:00) What's Next for Matt and Future Flow

On this episode of The AI Report, Liam Lawson sits down with Avi Hacker, founder of the AI Consulting Network and one of the most prolific solo operators in the AI world.Avi doesn't know how to code, but that hasn't stopped him from building a business powered entirely by custom GPTs, Airtable workflows, Make.com automations, and a relentless commitment to experimentation. He's automated everything from daily newsletters to podcast production and does it all without a technical team.This conversation dives into:How Avi scaled from law school grad to AI consultantWhy he operates like a 20-person team with zero employeesThe real cost of automation and what clients often misunderstandHow he built tools for LinkedIn growth, blog creation, and deep researchThe tech stack behind his daily content engineIf you're interested in the intersection of AI, automation, and solopreneurship, this is one to queue up.Subscribe to The AI Report:theaireport.aiJoin our community:skool.com/the-ai-report-community/aboutConnect with Avi:linkedin.com/in/avihackerChapters:(00:00) Building Anything Without Knowing How to Code(01:00) From Law School to AI Consultant(03:05) Starting the AI Consulting Network(05:12) What Clients Get Wrong About AI(07:00) Understanding Time ROI in AI Projects(08:14) Live Walkthrough: Automating The AI Report Newsletter(11:00) Building a Custom Workflow with Make and Airtable(13:20) Why He Doesn't Do One-Time Builds(15:00) The Internal Tools That Power His Growth(17:45) Working Like a 20-Person Team Using AI(19:14) Future Plans and Scaling the Business(21:00) Experimenting With AI Agents(23:00) Training AI-First Operators(25:00) Big Ideas, Small Teams, and the Power of Leverage(30:00) Explaining His Job to Non-Tech Folks(32:00) Where to Find Avi Online

In this episode of The AI Report, Christine Walker joins Arturo Ferreira to launch a new series on the legal side of artificial intelligence. Christine is a practicing attorney helping businesses understand how to navigate AI risk, compliance, and governance in a rapidly changing policy environment.They explore how the shift from the Biden to the Trump administration is changing the tone on AI regulation, what the EU AI Act means for U.S. companies, and why many of the legal frameworks we need for AI already exist. Christine breaks down how lawyers apply traditional legal principles to today's AI challenges from intellectual property and employment law to bias and defamation.Also in this episode: • The risk of waiting for regulation to catch up • How companies can conduct internal AI audits • What courts are already doing with AI tools • Why even lawyers are still figuring this out in real time • What businesses should be doing now to reduce liabilityChristine offers a grounded, practical view of what it means to use AI responsibly, even when the law seems unclear.Subscribe to The AI Report:theaireport.aiJoin our community:skool.com/the-ai-report-community/aboutChapters:(00:00) The Legal Risks of AI and Why It's Still a Black Box(01:13) Christine Walker's Background in Law and Tech(03:07) Biden vs Trump: Competing AI Governance Philosophies(04:53) What Governance Means and Why It Matters(06:26) Comparing the EU AI Act with the U.S. Legal Vacuum(08:14) Case Law on IP, Bias, and Discrimination(10:50) Why the Fear Around AI May Be Misplaced(13:15) Legal Precedents: What Tech History Teaches Us(16:06) The GOP's AI Stance and Regulatory Philosophy(18:35) Most AI Use Cases Already Fall Under Existing Law(21:11) Why Precedents Take So Long—and What That Means(23:08) Will AI Accelerate the Legal System?(25:24) AI + Lawyers: A Collaborative Model(27:15) Hallucinations, Case Law, and Legal Responsibility(28:36) Building Policy Now to Avoid Legal Pain Later(30:59) Christine's Final Advice for Businesses and Builders

Welcome back to The AI Report, where Liam Lawson speaks with the people shaping the future of AI, one breakthrough at a time.This week's guest is Adam Biddlecombe, co-founder of Mindstream, the daily AI newsletter that was acquired by HubSpot just 17 months after launch. Adam shares how he went from posting on LinkedIn during his lunch breaks to building a globally recognized media brand with over 150,000 engaged readers.In this conversation, Adam breaks down how to grow and monetize a newsletter, what most people get wrong about AI adoption in companies, and why editorial quality still matters more than ever. He also shares the realities of startup life. from managing deliverability nightmares to building a distributed team across Lebanon, Iran, Pakistan, and beyond.We talk through how to drive real AI literacy in teams, how to think about pricing ads for sponsors, and why being early matters less than being consistent.Subscribe to The AI Report and stay sharp on everything happening in AI:theaireport.aiConnect with Adam:linkedin.com/in/adambiddlecombeChapters:(00:00) Why AI Literacy is the New Career Edge(00:43) How Adam Sold Mindstream to HubSpot(03:07) Growing the Newsletter from Scratch(06:17) Building on LinkedIn in 2025(09:25) Talking AI Fear and Workplace Buy-In(12:21) Rolling Out AI Internally at Scale(15:10) Educating Without Overwhelming(19:06) The Mindstream Monetization Model(22:18) Differentiating Through Editorial Voice(27:02) Deliverability, List Hygiene, and Real Engagement(30:47) Hiring Internationally and Building Culture(35:00) Why Young, Global Talent Was the Secret(40:14) The “Doppelgänger” Way to Train New Hires(44:17) The Truth About Deliverability Pain(48:08) The Email That Led to a HubSpot Acquisition(49:19) Adam's 4-5-Mile Clarity WalkFollow the show and leave a rating if you found this episode valuable. It helps new listeners find the pod.

Learn AI in 5 Minutes Per Day: https://www.theaireport.ai/In this episode of The AI Report, Liam Lawson sits down with Frank Greeff, former chef-turned-tech founder who built and sold Realbase for $180M, to explore how AI, founder relationships, and radical action are reshaping the future of entrepreneurship in the AI era.Frank shares the full story behind Realbase's growth—from a garage-based signboard company to Australia's #1 real estate marketing platform. He dives into the mindset behind building a company to acquisition, why most founders struggle post-exit, and how he's now leveraging AI to build a lean, billion-dollar business with fewer than 100 employees.From creating AI-powered org charts and automating operations to hosting $55K yacht events for 8-figure founders, this episode is packed with insights on scaling, brand-building, and creating leverage through people and systems. Frank also unpacks how he uses ChatGPT like a third co-founder, why resilience is more important than routines, and what the real differentiator will be in a world where AI does everything—human relationships.But it's not just about AI tools—this episode is a masterclass in modern founder psychology: why doing what “doesn't make sense” might be your greatest edge, how to stay in the game long enough to win, and how to align business with purpose at scale.Want to understand what the future of work, leadership, and founder-led growth looks like in an AI-native world?Tune in now! Don't forget to like, comment, and subscribe for more expert insights!Over 400,000 OpenAI, Apple & NASA professionals read The AI Report. We'll teach you how to leverage AI to make money/save time in just 5 minutes.Join our free community now: https://www.skool.com/the-ai-report-community/aboutConnect with Frank: https://au.linkedin.com/in/frankgreeff(00:00) Intro(02:08) Realbase Origin: From Garage Startup to Market Leader(04:55) The $180M Exit to Domain: Behind the Deal(07:46) Launching The Founder's Table(09:58) Building a Network Like the PayPal Mafia(13:57) Why Top-of-Funnel Content is a Game Changer(18:34) What Successful Founders Actually Eat(23:31) Traits of Successful Founders in the AI Era(27:58) The #1 Trait Founders Need to Thrive with AI(31:36) Only 3% of Founders Are Truly Using AI(33:44) Frank's AI Org Chart Explained (Router, Agents, Managers)(36:30) Using AI as a Third Co-Founder(38:30) Designing a Lean AI-First Company(41:31) Hosting $55K Founder Dinners on Yachts(43:34) Why Relationships Are the Ultimate Moat in an AI World(45:04) Frank's New Business Vision