The CMS Running NASA & 2,000 Stories a Day | Brian Alvey, WordPress VIP

In this episode, Brian Alvey, CTO of WordPress VIP (Automattic's enterprise platform), reveals how the platform powering NASA, CBS, NBCUniversal, Rolling Stone, Samsung, and the White House is integrating AI into enterprise publishing at massive scale. Brian shares how he's built over 24 content management platforms throughout his career — and why the current AI moment is the most transformative shift he's ever seen in publishing technology.Brian breaks down how WordPress VIP is embedding AI into tools like Parse.ly to give editors conversational content insights, how their AI-powered "editorial recipes" turn hours of manual headline testing and cross-linking into minutes, and how a new tool called Tollbit lets publishers actually charge AI crawlers for accessing their content. He also shares his philosophy on keeping humans in the loop at enterprise scale, how 200-person newsrooms and 11,000-contributor content teams are navigating AI adoption, and why the open web matters more than ever when everyone's fighting for attention in an AI-first world.Key Topics CoveredHow WordPress VIP powers mission-critical content for NASA, CBS, the White House, and hundreds of enterprise brandsBrian's journey building 24+ content management platforms and what he's learned about great CMS architectureHow WordPress VIP takes open-source WordPress and locks it down with enterprise governance for massive newsroomsThe AI tools WordPress VIP is building: conversational analytics, headline testing, engagement optimization, and automated cross-linkingHow Tollbit lets publishers charge AI companies for crawling their content — a new revenue stream for mediaWhat "human in the loop" actually means when you're managing 11,000 contributorsThe Agentforce integration with Salesforce: bringing AI-powered chat and lead generation directly into WordPress sitesWhy the open web still matters in the age of AI and how publishers are fighting backHow enterprise publishing teams are adopting AI without sacrificing editorial qualityBrian's honest take on where AI helps editors vs. where it still falls shortEpisode Timestamps00:00 - Introduction and welcome00:35 - Brian's career building publishing platforms before Google existed03:22 - AI as an equalizing paradigm shift07:20 - Generalist superpower: bridging art and science09:46 - Human skills vs AI: lessons from The Founder13:36 - Career advice for his kids in the AI era16:01 - WordPress VIP and enterprise publishing at scale18:28 - Core mission: speed and stability without breaking things23:06 - AI content intelligence tools and MCP adapters28:39 - Media business fundamentals: attention and monetization35:27 - Customer segments and AI crawler strategies40:12 - Trust and credibility in the AI-generated content era44:25 - From competing against WordPress to leading it48:15 - Obsession with automation and future of work51:51 - Building products in days with AI tools like Claude56:47 - What truly drives him58:40 - Closing and where to find BrianBrian's Socials:LinkedIn — https://www.linkedin.com/in/brianalvey/Website — https://brianalvey.comPartner LinksBook Enterprise Training — https://www.upscaile.com/Subscribe to our free newsletter — https://www.theaireport.ai/subscribe

Apple confirms Google Gemini will power the new Siri — dropping OpenAI as the default on a billion devices. GPT-5.4 Thinking becomes the first AI to beat the human baseline at navigating a computer. Yann LeCun raises $1.03B in the largest seed round in European history to build a new kind of AI. Robotics companies pull in $1.2B in a single week. And the U.S. Department of Energy puts $293M behind AI for national challenges.Partner LinksBook Enterprise AI Training — https://www.upscaile.com/Subscribe to our free newsletter — https://www.theaireport.ai/subscribeGet our free AI resource pack — https://community.theaireport.ai/checkout/the-ai-report-welcome-gift?coupon_code=WRTHConnect with Liam — https://www.linkedin.com/in/not-the-f1-driver-liam-lawson/About The AI Why:The AI Why breaks down what's actually happening in AI — who's building it, how it's being deployed, and why the people building it do what they do. New episodes every Tuesday (AI News in 5) and Thursday (founder and exec interviews).

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 $255.3 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:🏛️ 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/