The AI Why with Liam Lawson

Brian Alvey, CTO of WordPress VIP and veteran publisher-technologist, has built 24+ CMS platforms and advises enterprise publishing teams. He discusses embedding AI into newsroom tools, AI-powered headline testing and cross-linking, charging AI crawlers with Tollbit, keeping humans in the loop at scale, and how open web standards matter as publishers adapt.

Apple switches Siri to Google Gemini on a billion devices. GPT-5.4 gains real computer control and massive context capacity. A European AI founder raises over $1B and robotics startups pull in $1.2B in a single week. U.S. agencies fund AI for national challenges while legal and regulatory fights heat up around procurement and liability.

Michael J. Domanic, VP and Head of AI at UserTesting, led company-wide AI adoption and built scalable governance. He explains how 70%+ weekly use was achieved, why AI rollouts often fail, and how custom GPTs and agent orchestration drove viral adoption. He also covers building CoEs, motivating experimentation, and treating AI adoption as a cultural challenge rather than just a tech project.

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/

Anthony Salcito, VP of Enterprise at Coursera who scaled global education programs from Microsoft to Coursera. He discusses a 234% GenAI enrollment surge, verified skills paths and Course Builder for role-based learning. He covers AI-powered coaching, roleplay simulations, and why critical thinking is rising alongside technical AI skills.

Stripe unveils billing that passes LLM token costs to customers with automatic markups and gateway integrations. Nvidia’s huge investment signals a shift toward public-market funding for big AI labs. GPT 5.4 gains native computer use, a one million token context window, and top-tier benchmark performance. OpenAI faces scrutiny after failing to alert police about a flagged dangerous user, prompting promised safety reforms.

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:🏛️ Pentagon vs. Anthropic — Defense Secretary Hegseth demands Anthropic remove safety guardrails from Claude or face a $200M contract cancellation and federal blacklisting💻 Perplexity Computer — A new AI agent system that orchestrates 19 models to execute complex tasks end-to-end📱 Samsung Galaxy S26 — Samsung's most AI-forward phone yet, featuring proactive AI nudges and built-in agents from Bixby, Gemini, and Perplexity🤝 Meta x AMD $60B Deal — Meta diversifies away from Nvidia with a massive 6-gigawatt AI chip agreement💰 OpenAI's $110B Round — SoftBank, Nvidia, and Amazon back the largest private funding round ever⏱️ Timestamps:0:00 – Introduction0:15 – Pentagon threatens to blacklist Anthropic1:20 – Perplexity launches Computer2:25 – Samsung unveils Galaxy S26 AI features3:30 – Meta and AMD sign $60 billion chip deal4:35 – OpenAI raises $110 billion5:40 – Closing📩 Subscribe to The AI Report newsletter for daily AI news: https://newsletter.theaireport.ai/subscribeGet Enterprise Training — upscaile.com

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/