Podcasts about prompt engineering

Don't fear losing your job to AI—fear losing it to someone who knows how to use AI better than you. It's time to stop treating AI as a tool and start treating it as your default way of working.Human by Design, AI by Default: Rewriting the Way We Work #110What does it actually look like to rebuild a global, legacy brand with years of technical debt into a completely AI-native business from the ground up? As it turns out, it isn't just a technological challenge—it is fundamentally an HR and communications mountain to climb.This week, Gary and George are doubly thrilled to welcome back Groupon's Chief People Officer, Nick Walker (marking his record third appearance on the show!), alongside Groupon's VP of Comms, Engagement, and Inclusion, Emma Coleman. Together, they take us behind the scenes of Groupon's massive cultural and structural transformation under their AI-savvy CEO, Dushan.From reshaping employee mindsets and restructuring traditional departments into lean "speedboats" to managing the psychological fear of redundancy, Nick and Emma share the unfiltered reality of rewriting the way we work. They discuss why AI adoption is actually a massive transfer of power from legacy systems back to human beings, and how human judgment remains the ultimate corporate superpower.Key takeaways from this episode:Speeding Fines vs. Parking Tickets: To build an AI-native culture, leaders must encourage risk-taking. Groupon welcomes "speeding fines" (mistakes made while pushing boundaries and moving fast) but has zero tolerance for "parking tickets" (complacency or refusing to try).Ditch the "Hand-Off Tax": Legacy organizations slow down because of continuous hand-offs between bloated, siloed teams. By structuring operations around "speedboats"—lean teams of 2 to 3 people running a complete workflow—you eliminate the friction and move exponentially faster.Close the Execution Gap, Not the Judgment Gap: AI is incredibly efficient at closing the execution gap (handling processes and grunt work). However, humans still own the judgment gap. Your ability to understand context, see around corners, and apply emotional intelligence is irreplaceable.Prompt Engineering is a Non-Negotiable Skill: Good inputs yield rich outputs. Investing time in mastering prompt engineering (sometimes spending up to an hour crafting a single prompt) is a major career differentiator that prevents "sloppy AI work."Send us Fan MailLinks & references: https://www.thecompanydoctor.com/Gary Gamp: https://www.linkedin.com/in/garygampGeorge Clode: https://www.linkedin.com/in/georgeclodeGary's new book, Career Catalyst - available online now: https://www.amazon.co.uk/Career-Catalyst-Secret-Skills-School-ebook/dp/B0DFYVG6XY/ref=tmm_kin_swatch_0?_encoding=UTF8&qid=&sr=

Founding PM chez The Mobile-First Company, Yassine était seul PM face à une équipe de 20 ingénieurs.Résultat : le PM devient un véritable goulot d'étranglement car les ingénieurs vont plus vite avec l'IA.Les questions s'accumulent, la data aussi, et le temps, lui, ne s'étire pas. C'est le déclic qui a poussé Yassine à créer son alter ego IA pour changer sa façon de travailler. Il a construit 3 agents qui tournent pour toute l'équipe, pas seulement pour lui : Un Weekly Customer Pulse qui remonte chaque lundi les signaux Slack, Intercom et data produit dans un rapport Notion.Un Competitor Monitor qui scrape les pages pricing des concurrents.Jassine, un PM virtuel sur Slack, calibré sur les préférences de chaque ingénieur. Le tout piloté depuis Claude Code.Désormais, Yassine passe 100% de son temps sur ce qui compte vraiment : le contact avec ses utilisateurs. Au cours de cet épisode : Comment il a inversé le rapport 60/40 avec 3 agents ?Sa méthode pour distribuer le rôle de PM à chaque ingénieur de l'équipeLe data lake construit en 6 semaines qui alimente tout le systèmePourquoi il personnalise la façon dont l'agent s'adresse à chaque devComment il construit un agent en 15mn (demo live)AI Club est une émission soutenue par Weglot, une solution tout-en-un qui traduit, gère et affiche votre site web dans 110+ langues, sans nécessiter de code. 

Sponsored by Blocks: Save at least 20% on your AWS costs with AI-powered optimization and enterprise discounts. Get your free Cloud Check at blocks.cloud/alphalist → https://blocks.cloud/alphalist?utm_source=alphalist&utm_medium=podcast&utm_campaign=blocks-podcast-2026 Vaibhav Gupta built computer vision for the original Microsoft HoloLens, optimized AR at Google, and wrote high-performance assembly at D.E. Shaw, then left it all to start from scratch. After a YC pivot away from a Slack competitor he was told not to build, he landed on something foundational: BAML, a programming language for a world where humans increasingly don't read code. His thesis: every software leap came from a new compute paradigm getting its own language assembly, C, Java, JavaScript and LLMs are the next primitive. They're probabilistic and non-deterministic, which breaks our deterministic tooling. In this episode, Vaibhav explains why "shipping at agent speed" is really a problem of trust and control, why 90% of engineering is plumbing AI will delete, why "English as a programming language" can't work, and why the world has a mathematically infinite appetite for software. Topics covered: - Why LLMs are a new compute primitive and why that justifies a new language - BAML: an embedded, type-safe language for structured LLM outputs across any language - Shipping at agent speed as a problem of trust, locking, and granular control - Why traditional CI/CD breaks in an agent loop - The "data trench" one type system across code, backend, and data - Why 90% of engineering is plumbing, and what changes when AI removes it - Where SaaS pricing and product models are heading

Matt Wynne, co-creator of Cucumber and BDD practitioner, joins Joe for the first time in over a decade to talk about what two years inside a Silicon Valley AI startup taught him about the future of software testing. Matt spent time at Mechanical Orchard working alongside experienced XP practitioners to modernize legacy COBOL mainframes using LLMs, and then spent a week with the team that coined the term "software factory," where the rule was simple: humans never write the code, never read the code. In this episode, Matt breaks down what harness engineering actually means, why shared understanding is still the real bottleneck even in an agentic world, and how testers can use multiple LLMs to review AI-generated pull requests without reading every line. He also gets honest about the grief that comes with realizing you can encode years of hard-won expertise into a Markdown file, and why that does not mean your skills are worthless. If you are working in a brownfield codebase, wondering how to handle the flood of agentic PRs, or trying to figure out where testers fit in a world where agents write the code, this conversation is worth your time. Find Matt at: mattwynne.net leansoftware.ai Also check out his course: Build a Software Factory: Hands-off agentic coding for experienced engineers https://testgld.link/mattcourse

Prompt engineering is useful, but it isn't the marketing skill that will define the future. In this episode, Lori Jones and Dan Nestle explain why strategic thinking, authority, and AI-powered research are becoming the real competitive advantage for modern marketers.And don't forget! You can crush your marketing strategy with just a few minutes a week by signing up for the StrategyCast Newsletter. You'll receive weekly bursts of marketing tips, clips, resources, and a whole lot more. Visit https://strategycast.com/ for more details.==Let's Break It Down==01:56 Dan's marketing journey and building enterprise brands04:41 How AI would have transformed marketing at Mitsubishi Heavy Industries12:25 AI's biggest impact on content creation and research15:15 Can AI shorten complex B2B sales cycles?17:25 Using AI to improve organizational alignment19:47 Competitive analysis in minutes instead of weeks23:57 Rethinking audience segmentation with AI26:57 Where marketers still misunderstand AI29:04 Executive authority, thought leadership, and AI credibility33:15 Building authority that AI can recognize34:11 Final marketing lessons and key takeaways==Where You Can Find Us==Website: https://strategycast.com/Instagram: https://www.instagram.com/strategy_cast/Facebook: https://www.facebook.com/strategycast==Leave a Review==Hey there, StrategyCast fans!If you've found our tips and tricks on marketing strategies helpful in growing your business, we'd be thrilled if you could take a moment to leave us a review on Apple Podcasts. Your feedback not only supports us but also helps others discover how they can elevate their business game!

By all logic, one would assume entering 2026 meant executing a clean strategy for automation and growth. Unfortunately, trapped in a cycle of reckless tech binging, many leaders are drowning in unexpected bills, digital mediocrity, and operational chaos while leaving real value buried under routine noise. This week, we are doing a mid-year audit on the 2026 predictions I made earlier this year. While I predicted the year of the AI Hangover, we aren't just nursing an AI hangover; we are staring at real corporate property damage. From runaway token costs and "vibe-coded" app failures to a total lack of workforce guidance, the hype cycle has officially hit a brick wall. My goal is to challenge your perspective by breaking down how these predictions are playing out on the ground, and the mandatory, conscious choices you must make to clear the slop: The Corporate Scapegoat: Public anti-AI sentiment is exploding, but society is pointing the finger at the wrong thing—using the machine to shield bad leadership, reckless deployments, and a total lack of baseline governance. The Wearable Paradox: Consumers loudly reject physical AI hardware like smart glasses while quietly surrendering their agency and pouring intimate proprietary data into software text boxes. The Workslop Epidemic: Automated mediocrity is rampant as employees try to keep their heads above water. Now, executives are facing massive invoice shock from runaway token costs and useless $80k vibe-coded apps. The Tech Hierarchy Realignment: Anthropic holds the capability crown but has no path to profitability. OpenAI and Grok are flying straight into the sun, while Google remains the underestimated enterprise giant. The Innovation Plateau: The "WOW" moments are gone, replaced by incremental updates. Meanwhile, humanoids have devolved into memes, plagued by scandals where robots were secretly teleoperated by offshore VR labor. The Enablement Void: Prompt engineering is dead, and basic LLM use is a baseline expectation. Yet, companies provide zero formal training, leaving teams to bumble around with powerful tools. The H2 Recovery Playbook: Climbing out of the mud pit requires four immediate moves: stop buying tools and invest in human effectiveness, rebuild employee trust, ruthlessly simplify your tech ecosystem, and lock in on your specific operational "why". By the end, I hope you're convinced that if you aren't seeing wins with AI, something is broken in this chain. Capturing this upside requires hard work. If you're ready to make intentional choices, audit your current ecosystem, and anchor your strategy in human capability, the light at the end of the tunnel is incredibly bright. ⸻If this conversation was helpful, make sure to like, share, subscribe, or buy me a coffee at https://buymeacoffee.com/christopherlind And if you'd benefit from help balancing performance, technology, and people, check out my website at https://christopherlind.co ⸻Chapters00:00 – Introduction: The January Thesis vs. July Pacing03:00 – Point 1: The Anti-AI Revolt & Technology as a Corporate Scapegoat10:55 – Point 2: The Wearable Paradox & The Erosion of Human Agency17:41 – Point 3: The Workslop Epidemic, Tokenmaxing, and $500M Invoices27:07 – Point 4: The Tech Hierarchy—Pure-Play Burn vs. The Google Ecosystem35:46 – Point 5 & 6: The Innovation Plateau & Humanoid Teleoperation Fraud42:07 – Insight 7: Prompt Engineering is Dead, Enablement is Absent44:50 – Actions: Four Surgical Leadership Moves for H2 202653:00 – Conclusion: Breaking the Tribal Extremes and Finding the Win #AIStrategy #AIHangover #OperationalExcellence #TechGovernance #WorkforceTransformation #FutureFocused

Benjamin est à la fois CTO en CDI chez Panopli, freelance et Indie Hacker. Avant l'IA, il n'aurait pas pu allier ces 3 fonctions sans sacrifier sa vie perso. Aujourd'hui, il a construit un système qui lui permet d'avancer sur les trois en parallèle, sans rallonger ses journées. Dans ce nouvel épisode, il développe un exemple de flow IA à travers une démo : → Dictée d'un besoin dans SuperWhisper→ Création de 3 tickets dans Linear→ Transformation des tickets en features→ Mise en pull request des features sur GitHub Au final, il passe moins de 6 minutes sur une tâche qui lui aurait pris 1 heures sans IA.Au cours de cette épisode :Sa méthode en 4 étapes applicable à n'importe quel métier, pas seulement la techComment il pilote 5 à 10 sessions d'agents en parallèle sans perdre le contrôlePourquoi l'humain reste le facteur limitant même quand les agents vont 10 fois plus viteCe que l'IA a changé (et abîmé) dans le rapport des développeurs à leur propre travailAI Club est une émission soutenue par Weglot, une solution tout-en-un qui traduit, gère et affiche votre site web dans 110+ langues, sans nécessiter de code. 

Legal AI Tools werden überall diskutiert, aber was steckt eigentlich technisch dahinter?Wir haben bei recode.law in den letzten Monaten mit mehreren Legal AI Anbietern gesprochen und sie ihre eigene Sicht auf Legal AI Tools erklären lassen. Der Auftakt unserer neuen Serie ist deshalb bewusst keine Interview-Folge: Annika und Simon erklären die Grundlagen: ganz ohne Tool-Empfehlung, damit man erstmal versteht, worum es geht und was wir uns daraus eigentlich erhoffen können.In der Folge geht es unter anderem um: Sprachmodelle, Chatbot-Format und Prompt-Engineering als technische Basis Wie „RAG" (Retrieval Augmented Generation) Datenbanken einbindet und Antworten überprüfbar macht Die zentralen Funktionen von der Recherche bis zu Workflows Warum Richtigkeit und Berufsrechtskonformität (Datenschutz, Verschwiegenheit) essenziell sind Was Datenbank, Ansatz, Jurisdiktion und Preis für Unterschiede zwischen den Tools machen Wie sich der Berufseinstieg für Studierende und WisMits dadurch verändertIn den nächsten Folgen sprechen wir dann mit den Anbietern direkt!

Kostenfreie Online-Events:https://kalifornische-terrassen.de/eventsPersonen:Claus Triebiger · triebiger-coaching.de · systemischer Berater mit Schwerpunkt auf philosophischen und psychologischen FragestellungenKevin Baron · @hausdesbarons · https://www.instagram.com/hausdesbarons/BeschreibungHerzlich willkommen bei „Kalifornische Terrassen".Hier geht es um psychologischen und systemischen Austausch – und darum, guten Ideen Gehör zu verschaffen.ZusammenfassungIn dieser Folge sprechen Claus Triebiger und Kevin Baron darüber, wie sich ein verantwortungsvoller Umgang mit Künstlicher Intelligenz gestalten lässt, ohne dabei die eigene Urteilsfähigkeit und Ausdrucksfähigkeit zu verlieren.Ausgangspunkt ist die Aussage eines KI-Unternehmenschefs, der für eine gesellschaftliche Atempause bei der KI-Entwicklung plädiert hat. Von dort aus öffnet sich ein Möglichkeitsraum: Welche Interessen – wirtschaftlich, politisch, persönlich – wirken hier zusammen, und wie lässt sich das Modell von Spiral Dynamics nutzen, um unterschiedliche Haltungen im Umgang mit Technologie sichtbar zu machen?Im Zentrum steht ein Bild, das die beiden als „kognitive Pornografie" beschreiben: die Gefahr, sich beim Prompten selbst sprachlich und gedanklich zu verlieren, weil die KI den Weg des geringsten Widerstands anbietet. Persönliche Erfahrungen aus Beratung und Unternehmensalltag zeigen zugleich, wie aus dieser Beobachtung ein produktiver Umgang entstehen kann – etwa indem eigenes Wissen zunächst selbst durchdrungen wird, bevor die KI als Werkzeug zur Erweiterung eingesetzt wird.Das Gespräch bewegt sich damit zwischen gesellschaftlicher und persönlicher Ebene und fragt, wie Bewusstheit, kritisches Prüfen und ein systemischer Blick auf Wechselwirkungen helfen können, Technologie als Ergänzung statt als Bedrohung zu erleben.Dabei wird deutlich:Bewusstheit über die eigenen Denkprozesse eröffnet einen Weg, KI als Ergänzung zu nutzen, ohne sich selbst darin zu verlieren.KeywordsKünstliche Intelligenz, Spiral Dynamics, systemisches Denken, Bewusstheit, Prompt Engineering, Verantwortung, Ethik, Perspektivwechsel, Systemisches Zentrum, wispo, Systemischer Club, Kalifornische TerrassenHast du Fragen, Gedanken oder willst deiner Idee Gehör verschaffen?Schreib uns gerne an:support@systemischer-club.de

This episode was too good to leave in the archive! As part of our Summer Replay Series, we're revisiting my conversation with consultant, SaaS founder, and self-described AI fanatic Andrew Ansley — and honestly, his advice is even more relevant today.Andrew breaks down exactly how he uses ChatGPT and Claude to run multiple businesses, why "clouding up the context window" is killing your AI outputs, and how to train an AI assistant on your business in 30 minutes or less. Then we go deep on SEO: what actually changed after 2022, how Google understands content through entities and embeddings, and what it really takes to build topical authority today.Whether you're an SEO, a small business owner, or just AI-curious, this replay is packed with practical workflows you can put to work this week.What You'll LearnWhy you should delete the messy middle of your AI conversations (and keep only the first prompt + final output)How to set up AI "projects" for each client or task — with business info, SOPs, examples, and your unique perspectiveThe 4 pieces Andrew uploads to train an AI on any workflow in about 30 minutesWhy you must define abstract concepts (like "write an email" or "SEO strategy") instead of letting AI decide what they meanDefinition + example + template: the simple prompt formula that upgrades your outputsClaude vs. ChatGPT: where each tool shines (projects, styles, voice transcription, and more)How SEO changed after 2022: entities, semantics, and user metricsWhat topical authority actually means — going deeper, faster, or wider with your content clustersWhy the real ranking signal is whether searchers end their journey on YOUR siteThe "Could ChatGPT give them this?" test for creating content that still winsEpisode Highlights & Timestamps(00:00) Welcome + meet Andrew Ansley(01:00) Consultant, SaaS founder, community leader: how Andrew wears all the hats(02:00) Why Andrew (and Crystal!) are learning Python(03:30) Inside Andrew's Skool community: automate marketing with AI + n8n(05:30) The one-person, AI-powered business (could you scale to $10M solo?)(07:30) Don't cloud the context window: Andrew's clean-conversation trick(09:45) Building SOPs with AI in an hour instead of a week(10:30) ChatGPT Pro vs. Claude: Andrew's honest comparison(11:00) How to set up an AI project: business info, ICP, SOPs, examples & styles(16:00) The power of templates (stop reinventing the wheel!)(21:30) Screen share: how Andrew organizes projects, prompts & custom styles(28:00) From aspiring pastor to bartender to SEO: Andrew's origin story(36:00) AI as the ultimate learning tool for curious kids (and adults)(45:00) How SEO changed: keyword matching → RankBrain, BERT & semantic search(48:30) User metrics, mobile-first indexing, and ending the search journey(51:30) Topical authority explained: embeddings, content clusters & internal links(54:00) Why sites dip after agencies leave (core algorithm updates + historical metrics)(56:00) The "Could ChatGPT give them this?" content test(56:45) Where to connect with AndrewQuotable Moment"You cannot let the AI decide what abstract concepts mean. You have to define it — and if you give it an example, that's even better." — Andrew AnsleyConnect with Andrew AnsleySkool Community (AI Marketeers)YouTubeAndrew's article on Search Engine LandMentioned in This EpisodeContent Sprout (Andrew's SaaS)n8n (open-source automation alternative to Zapier)GoHighLevelKoray Tuğberk Gübür (topical authority & entity SEO)Bill Slawski (SEO research pioneer)Alex Hormozi & Sam Ovens (Skool)Connect with CrystalWebsiteLinkedInText me your questions or comments!Hey, Shopify store owners! (Especially if you're selling on Etsy, too!)Here's a quick question: Are people actually finding your products on Google?If SEO feels confusing, overwhelming, or like something you'll "get to later", this is for you.I'm hosting a free, seven day Shopify SEO challenge that breaks it down into simple, doable steps.No tech headaches, no fluff. Join us at  Hey, Shopify store owners! (Especially if you're selling on Etsy, too!)Here's a quick question: Are people actually finding your products on Google?If SEO feels confusing, overwhelming, or like something you'll "get to later", this is for you.I'm hosting a free, seven day Shopify SEO challenge that breaks it down into simple, doable steps.No tech headaches, no fluff. Join us atSupport the showFree checklist: Is your Shopify store quietly losing sales? Run the 5-minute self-check →Book a Shopify Store Strategy Call With Crystal!Want to follow up on what you've heard? Search the podcast!AFFILIATE LINKS:Start your Shopify Store!Get SurferSEO!Metricool (to be everywhere online, you NEED a social media scheduler!)Grid and PixelNote: If you make a purchase using some of my links, I make a little money. But I only ever share products, people, & offers I trust & use myself!

Savinien Lucbéreilh est CPO chez Partoo. Il n'est pas développeur. Pendant des années, il rencontre un problème simple qui paraît pourtant insoluble :Les employés posent toujours les mêmes questions. Et à chaque fois, il perd du temps à chercher les mêmes réponses parmi des sources éparpillées (wiki,help center, SIRH) Jusqu'au jour où il décide de construire lui-même l'agent qui relie ces différents éléments.Résultat : une app Slack fonctionnelle, hébergée en ligne, disponible 24h/24 pour tous les employés de Partoo. Développée entre deux calls, sur ses heures perdues, en un mois. Savinien montre en live l'agent en action : une question posée dans Slack → une réponse générée depuis plusieurs sources internes avec citation des sources. Au cours de cet épisode :Comment il est passé d'une app locale à une app déployée en prod pour 400 personnesPourquoi il n'a pas changé un seul outil pour centraliser toute la knowledge de la boîteLa faille de sécurité qu'il a découverte au dernier moment, et comment il l'a corrigéePourquoi l'adoption reste le vrai chantier une fois l'app en ligne___AI Club est une émission soutenue par Weglot, une solution tout-en-un qui traduit, gère et affiche votre site web dans 110+ langues, sans nécessiter de code. 

What's up folks, welcome to our 4 part series of Crawling through the dungeon of martech architecture. You've arrived at Part 2: The Eye of Context.We cover:(00:00) - Intro (00:56) - In This Episode (01:28) - Sponsor GrowthLoop (02:32) - Sponsor: GrowthBench (03:32) - Welcome Back (04:09) - FLOOR 2: THE EYE OF CONTEXT (06:15) - Why AI Produces Believable Nonsense (09:00) - BOSS BATTLE: The Hallucination Oracle (10:07) - Data Quality: When Agents Read Your Messy Data (22:33) - Context Engineering: What It Is and Why It's Not the Same as Prompt Engineering (24:28) - Sponsor: MoEngage (25:25) - Sponsor: Knak (26:30) - Context Eng vs Prompt Eng (38:58) - Why the Industry Built the Wrong Semantic Layer in 2012 (46:33) - How Context Rot and Fragmentation Break AI Agent Performance (49:59) - BOSS BATTLE: Rotten Context Mage (50:37) - How to Build a Shared Context Layer for AI Agents (58:17) - Testing Whether Your Context Layer Works (01:01:35) - NEW ACHIEVEMENT: The Meaning Layer Is Live ---------------------------------------------------------------------------OPENING---------------------------------------------------------------------------Welcome back to the Dungeon of Martech Architecture.You've arrived at part 2. If this is your starting point, check out part 1 where we cleared the first floor's boss in 2 forms: The False Truth King in the CRM, and The Export Hydra that spread it everywhere. That said, if you already have a data warehouse, you might be able to start right here.Episode 1: CRM GravityWe conquered the source of truth and discovered that the data warehouse replaces the CRM with portable audiences.Episode 2: The Eye of ContextToday, we learn why AI fails without shared meaning, build the context engineering layer, and dig into why the industry built the wrong kind of meaning infrastructure in 2012.Episode 3: The Correlation MasqueradeNext, we escape the correlation trap and build the causal memory layer that separates agents that optimize correctly from agents that confidently scale the wrong behavior.Episode 4: The Dispatch TowerThen, we tackle the governance chaos of 30 vendors all claiming authority, and confront the interface decision that most organizations already made without realizing it.Let's start our descent.---------------------------------------------------------------------------FLOOR 2: THE EYE OF CONTEXT — AI Hallucinations, Data Quality, and Context Engineering---------------------------------------------------------------------------The layout of the second floor down the dungeon of martech architecture actually looks pretty fancy. It's cozy, it looks modern, the whole palace is lined with mirrors. But it's a bit creepy because once you look a little closer at the reflections, you notice that some of the details are off. The boss on this floor is low key danger that sneaks up on way too many teams – not like the big flashy monsters from the past 2 floors.Let's say you have a new AI system running on your marketing data. You've got it producing stuff like scores, recommendations, campaign ideas. Initially, it actually looks solid.There's no obvious AI sentence structures in the summaries, they read well.The scores next to accounts seem to make sense: higher ones next to well known brands and lower ones are gmail accounts.The campaign ideas are actually pretty fresh, you can tell that it's tailored for your ICP.Every output is delivered with impeccable confidence.So the next step is asking yourself… how would you know if it was wrong?There's a lot of obvious hallucinations that you probably catch when you chat with GPT or Claude, like totally inventing stuff. I'm talking about the details. The kind of wrong that passes the first glance. We've all seen that viral post on r/analytics about a company that found out AI has been making up analytics data for 3 months. Whether this post is from a real story or not, some versions of this are happening inside companies today. But this is happening everywhere right now. Even at some of the top AI companies on the planet. I've talked to technical marketing leaders that have greenlit agentic tools at their startups before the data definitions were settled. One of them called it ‘believable nonsense', and that term kinda stuck with me. It's the most dangerous form of hallucination, it sneaks up on you.This floor is harder than the last because the traps on the previous level were visible, once you knew what to look for: CRM exports nobody trusted, audience logic duplicated across platforms, copies drifting from the original. You felt that, you saw that. This floor's failures are designed to look like success, until you dig into the details and look under the hood.Let's look at the origins of The Hallucination Oracle boss. Why AI Produces Believable NonsenseHumans are wired to trust smooth, confident talkers. It's actually baked into our evolution and how our brains develop from infancy. Studies on babies and brain scans show this is an innate thing that kicks in early.A person who sounds certain usually knows something, right?LLMs and AI systems break this calibration, they produce fluency without necessarily producing correctness. At first glance, the output sounds right for structural reasons, not evidential ones. And once something sounds right, we engage with it differently. We forward it. We build on it. We present it to stakeholders who don't have the context to question it.This is similar to the The False Truth King boss from the first floor in episode 1, but this is at the intelligence layer: output that has been processed, synthesized, and returned with all the structural markers of a trustworthy answer, but the problem is the reasoning underneath it is hollow.That's Jason Dobbs, Head of Marketing & GTM Engineering at Kumo. He greenlit agentic analytics and predictive workflows at his startup before the team had settled on shared data definitions. The system produced outputs that looked reasonable right up until someone started asking follow-up questions:JASON DOBBS, Kumo AI"What made it dangerous wasn't really like the obvious hallucination. What we were seeing looked polished enough to be operational. At first glance the scores looked precise, the summary sounded coherent, the recommendations felt data-backed. But the moment you ask the simple follow-up questions -- why did you choose this account? What data drove this decision? -- the logic started to thin out. The lesson wasn't that the data was bad or the warehouse was bad or the model was bad. What was wrong is we were trying to automate ambiguity. We were asking AI to solve for confusion that we hadn't yet ourselves solved for internally. And once you do that, you enter the danger zone because the failure is essentially believable nonsense."This is some scary stuff right? When this believable nonsense gets trusted long enough to make it into a campaign, a decision, a board slide. Obvious hallucinations are easy to catch. Confident, polished, data-backed nonsense gets through more often than we think.The good news is that we already have a weapon perfect to slay this boss, we shaped it in the last episode: the data warehouse. It houses data. Data is how we defeat believable nonsense… but we need to enhance it.---------------------------------------------------------------------------BOSS BATTLE: The Hallucination Oracle----------------------------------------...

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On this episode of KeyLIME+, Adam sits down with 'the medical futurist', Dr. Bertalan Meskó, to explore what it means to prepare for the future of medicine in an era currently shaped by artificial intelligence. Using prompt engineering as a starting point, the conversation moves beyond the technical to focus on a deeper shift in how clinicians adapt in the face of rapid change. Together, they examine the risks of over-reliance on AI, the pitfalls of bold predictions, and the enduring role of human connection in healthcare. The discussion ultimately reframes AI not as the destination, but as a tool for helping clinicians prepare for what lies ahead.  Length of Episode: 39:23  Resources to check out:  Meskó B. Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial. J Med Internet Res. 2023 Oct 4;25:e50638.    Episode 38 AI and Emerging Skill Gaps: Deskilling, Never-Skilling, Mis-Skilling – and What Educators Can Do About It All  Contact us: keylime@royalcollege.ca     Follow: Dr. Adam Szulewski https://x.com/Adam_Szulewski           

The evolution of software development toward a loop-driven era, where autonomous AI agents transition from simple code generation to independent system orchestration. Central to this shift is compound engineering, a methodology that treats every development task as a reusable investment to achieve massive productivity gains. This paradigm emphasizes that code verification, rather than generation, is now the primary bottleneck in engineering velocity. To address these risks, the texts advocate for a robust execution harness—such as those developed by Harness AI—which provides the necessary memory, governance, and real-time context for safe deployment. Furthermore, the documents highlight community innovations like Lore, a tool designed to extract developer judgment from session histories into reusable agent skills. Ultimately, the materials illustrate a transition from manual programming to the design of sophisticated autonomous verification platforms that operate within live cloud-native environments.

How do you stay in control of AI while still benefiting from everything it can do? As AI becomes more powerful, many leaders are focused on getting AI to do more work. But perhaps the better question is: How do you make AI more effective without letting it influence your thinking, your brand, or your business direction? In this episode of Grounding AI, Donna Peterson explores why leaders must remain the decision-makers while using AI as a tool to strengthen expertise, deepen customer relationships, and improve business outcomes. You'll learn why AI should enhance your knowledge rather than replace it, how to train AI around your company's goals and values, and the questions every leader should ask before using AI-generated recommendations. If you're responsible for marketing, sales, leadership, customer relationships, or business strategy, this episode offers practical guidance for maintaining control while leveraging AI effectively. In This Episode: Why AI naturally influences decisions and direction The difference between getting AI to do more and getting AI to be more effective How leaders can maintain ownership of their expertise Why your brand voice must remain stronger than AI suggestions The importance of building AI libraries and organizational knowledge Questions to ask before every AI prompt How to keep customer relationships at the center of AI adoption A simple test to determine if AI is helping or leading your business Key Takeaway Before every prompt, ask yourself: What am I trying to accomplish? Why does it matter to my audience? What action do I want people to take? Does this align with our company values and goals? The more direction you provide, the more valuable AI becomes. Connect With World Innovators // Website: www.worldinnovators.com Subscribe for weekly conversations on AI, leadership, trust-building, marketing strategy, and practical business growth. *** Reach out to dpeterson@worldinnovators.com if you'd like help building a marketing strategy that builds relationships and/or AI training for individuals or full teams.*** Visit www.worldinnovators.com for more resources on building stronger marketing and leadership strategies.*** Subscribe to the Grounding AI podcast for weekly insights into marketing, leadership, and the future of AI.

Stewart Alsop sat down with Michael Shackelford to discuss their experiences building applications through vibe coding—the practice of using AI to create software without traditional programming expertise. Stewart, who runs the AI Whispers community in Buenos Aires and hosts the Crazy Wisdom podcast (with over 660 interviews), shared how he went from teaching people prompt engineering to building his own video conferencing software as a Riverside.fm replacement, while Michael opened up about his year-long journey creating Genrupt Inc, an AI-powered content generation tool for e-commerce sellers. The conversation covered everything from the decline in quality of Claude's reasoning capabilities and how Chinese companies used distillation attacks to copy Anthropic's models, to the importance of spaced repetition systems for managing knowledge in the age of LLMs, with both sharing battle-tested prompting strategies like asking AI to "explain it to me in genius terms" and using deep research queries to reverse engineer how competitors build their products.Show Notes:- Dan Martell's book "Buy Back Your Time" was mentioned as one of the best business books for thinking about life and business- Check out John Vervaeke's "Awakening from the Meaning Crisis" for understanding relevance realization and why AI fundamentally cannot determine what's relevant to humans without being toldTimestamps00:00 Michael discusses being exhausted from getting his app ready for launch, working nonstop with AI to prepare landing page for podcast traffic driving beta signups05:00 Stewart explains starting AI Whispers in Buenos Aires after leaving OpenAI vendor company, meeting early adopters like Torin who was building mind-reading EEG technology10:00 Discussion of how corporations resist AI adoption due to political games and job security fears while some companies use AI as excuse for pandemic-era layoffs15:00 Stewart describes teaching workshops on using LLMs as linguistic tools rather than coding tools, noting technical people often lack humanities background needed for prompting20:00 Explaining chatbot wrappers, API calls, and how Anthropic's reasoning quality declined after Chinese distillation attacks copied their secret sauce developed with philosophers25:00 Technical discussion of model training, fine-tuning versus RAG for new information, and different approaches to updating AI knowledge beyond initial training30:00 Stewart describes building podcast recording software to replace expensive Riverside, struggling with syncing audio and video files across different computer clocks35:00 Discussion of critical factors in vibe coding, discovering unknown technical requirements, and how AIs don't automatically reveal missing information40:00 Stewart's reverse engineering process using deep research function to study competitors' hiring and technology stacks, separating planning agents from coding agents45:00 Prompting techniques including "explain like I know everything" and using spaced repetition systems to capture valuable prompts and technical knowledge50:00 Michael explains his Generux app for generating ecommerce content using Amazon review data analysis to inform high-converting listing images and videos55:00 Discussion of founder mentality involving self-delusion about project timelines, Michael working nine-plus hours daily for nine months on app development60:00 Comparing Amazon's expert software to prosumer software approach, discussing distribution challenges and future robotics applications for customized products65:00 Stewart demonstrates spaced repetition app for memory improvement and knowledge retention, explaining relevance realization problem that AI agents cannot solve without embodimentKey Insights1. Stewart Alsop started AI Whisperers in Buenos Aires after leaving his role at Invisible Technologies, which was OpenAI's largest vendor for RLHF work. He noticed that machine learning engineers at tech companies lacked the humanities background needed to properly interact with large language models, which are fundamentally linguistic tools. This led him to create weekly workshops teaching non-technical people how to use AI effectively, running events every Thursday for two years straight. The group attracted intense geeks from the start and eventually led to Stewart speaking right after Vitalik Buterin at DevConnect, marking a significant milestone for the community.2. Large corporations are resistant to AI adoption due to multiple factors including political dynamics within organizations and employees fearing job loss. Many companies that grew during the pandemic are now using AI as an excuse to downsize when the real issue is inefficiency from rapid expansion. Stewart observed that even technical people in machine learning often don't understand how to properly use AI tools because they lack linguistic and humanities training. The fundamental problem is educational, requiring companies to train people how to use these new tools while those same people resist learning them.3. Vibe coding has evolved significantly with Claude Code being a game changer that reduced the technical barrier to entry. Before Claude Code, developers needed substantial technical knowledge to work through constant doom loops and debugging cycles. The success of coding AI tools stems from thirty years of testing infrastructure that provides clear yes or no feedback on whether code works. This infrastructure doesn't exist in the same way for manufacturing, science, and other fields, which is why software became the dominant area for AI assistance initially.4. Claude's quality degradation over recent months resulted from multiple factors including distillation attacks by Chinese companies who reverse engineered Anthropic's reasoning capabilities. Anthropic had hired philosophers, sociologists, and psychologists to develop exceptional reasoning in Claude 4.5, but this was expensive to run. When Chinese models like Kimi copied these capabilities at one tenth the cost, and when mainstream users flooded the platform before Anthropic's planned IPO, the company had to reduce quality to manage computational costs. This represents a significant loss for power users who relied on Claude's superior reasoning abilities.5. Stewart built a podcast recording application to replace Riverside because he needed API access to automate workflows, which Riverside wanted one thousand dollars monthly to provide. The technical challenge involves syncing audio and video from local recordings on multiple computers with different clocks through a server, then merging them so voices match lip movements. This problem requires understanding complex timing issues across different network conditions and file formats. Stewart has been working through AI psychosis for months on this FFMPEG pipeline problem, illustrating how vibe coding still requires building intuition about technical problems even without traditional coding knowledge.6. The transition from expert software to prosumer software represents a major opportunity for AI-enabled tools. Expert software like Photoshop, Blender, and terminal interfaces have extreme complexity that intimidates beginners, but AI is making these capabilities accessible through natural language. The reign of specialists is ending as generalists with broad knowledge and curiosity can now build complete applications by leveraging AI to fill technical gaps. This shift particularly benefits entrepreneurs and founders who specialize in getting into difficult situations and figuring them out, even when they originally thought tasks would be easier than they turned out to be.7. Building applications with AI requires accepting massive time investments beyond initial estimates and developing strategies for overcoming knowledge gaps. Michael estimated his ecommerce content generation app would take months but spent nearly a year working over nine hours daily, while Stewart spent months solving audio-video sync issues. Success requires using tools like deep research to understand how competitors solve problems, maintaining separate planning and coding agents, and learning to ask the right questions. The key insight is that vibe coders can achieve ninety percent of functionality independently, but the final ten percent often requires understanding specific technical concepts that AI cannot intuit without proper context and domain knowledge.

Conference season is back, and so are the real conversations. In this episode, Peter Maddison and Dave Sharrock catch up after a busy stretch of travel and dig into something Dave has been road-testing at conferences: why most people given access to AI tools freeze up, and what actually helps them move past that.Dave ran a workshop at the Global Scrum Gathering in Vancouver for non-technical roles - product managers, Scrum Masters, agile coaches - people who've been told "use AI" but have no clear picture of where to start. What he found is that the problem isn't motivation or technical ability. It's the lack of scaffolding. Give people the right structure and the right room to experiment, and things shift pretty quickly.The conversation then moves into multi-agent systems - how Dave's team built a group of agents that continuously refresh the workshop itself based on current thinking. Peter adds his own take on testing these systems with personas and automated quality evaluation. It gets a bit technical, but in the best way.This is a good episode if you're thinking about how to help your organization actually use AI, not just adopt it on paper.Key Takeaways:Context beats generic. Prompts work when they're specific to your role and your actual problems. A product manager needs product management context, not a one-size-fits-all example.Think in teams, not steps. Multi-agent systems work best when you treat them like a team reviewing an artifact, each agent checking for something different, rather than a linear build process.Don't assume everyone gets it. The gap between people who use AI daily and people who tried it once and gave up is wider than most of us realize. Getting both groups in the same room is where the real learning happens, for everyone.Have a question or something to add? Reach out at feedback@definitelymaybeagile.com or find us at definitelymaybeagile.com. And if you're finding the show useful, subscribing and leaving a review goes a long way.

In this episode of The Masonic Roundtable, we explore the cutting edge of the digital age with Prompt Engineering Your Lodge Experience. We discuss how real-time generative AI can be utilized as a modern "working tool" to enhance various aspects of our fraternal life, from streamlining administrative tasks to deepening our educational research. Our panel examines the practical applications of AI in crafting engaging presentations, organizing complex schedules, and even generating thought-provoking prompts for lodge discussions. Join us as we consider the balance between traditional methods and new technology, and how the art of the "prompt" can help us build a more efficient, informed, and connected brotherhood in 2026. 

Effective artificial intelligence (AI) prompting is essential for students to use AI to enhance critical thinking and clinical decision-making skills. Dr. Zeigler shares a framework she and a colleague developed for effective prompting: the CARE (Context, Action, Role, Expectation) Prompt Engineering Framework. The CARE framework provides a systematic outline for nurse educators to use in teaching students clinical decision-making skills and to ensure that effective AI prompts are used.

Recorded live at Smart Marketer Mentor Tables in Nashville, this is Kurt's full talk on why most people are bad at AI and what to do about it. The pitch was that AI would let you do less work and produce better output. What actually happened: everyone is producing more slop, faster. Inside: the RTF framework that fixes any prompt in 30 seconds, the 10 AI tools Kurt actually uses every day (not the ones he gets paid to recommend), and why Claude Cowork is the single tool worth your attention in 2026. SPONSORS Swym - Wishlists, Back in Stock alerts, & more getswym.com/kurt Cleverific - Smart order editing for Shopify cleverific.com Zipify - Build high-converting sales funnels zipify.com/KURT LINKS Smart Marketer: https://smartmarketer.com Microsoft Clarity: https://clarity.microsoft.com Topaz Labs: https://www.topazlabs.com Adobe Enhance: https://podcast.adobe.com WhisperFlow: https://wisprflow.ai Whisper Transcription (Mac app): https://goodsnooze.gumroad.com/l/whisper-transcription Adobe Firefly: https://firefly.adobe.com Nano Banana (Google): https://gemini.google.com Grok: https://grok.com Claude Code: https://claude.com/claude-code Claude Cowork: https://claude.com Crisp Chat: https://crisp.chat Tidio: https://www.tidio.com Matrixify: https://matrixify.app WORK WITH KURT Apply for Shopify Help ethercycle.com/apply See Our Results ethercycle.com/work Free Newsletter kurtelster.com The Unofficial Shopify Podcast is hosted by Kurt Elster and explores the stories behind successful Shopify stores. Get actionable insights, practical strategies, and proven tactics from entrepreneurs who've built thriving ecommerce businesses.

This episode of Inspiration Nation sees Ryan Boniface and Jose Noya exploring content absorption, social media addiction, dopamine hits, and how different generations have experienced the shift from pre-internet childhoods to today's always-on digital world. From three-channel television, newspapers, and Dallas hysteria to TikTok, Instagram reels, AI, and algorithm-driven attention, the conversation asks a powerful question: are we using technology intentionally, or is it using us? The central quote, “We don't think our way to action, we act our way into habits of thinking,” shapes the whole episode, reminding us that real change does not come from endlessly scrolling, overthinking, or consuming more content, but from taking small, deliberate actions that build better habits and a better mindset.Ryan and Jose reflect on boredom, planning, execution, the attention economy, doom scrolling, phone addiction, and how tools like Google, AI, AutoTrader, Facebook Marketplace, and smartphones can either distract us or help us move forward. It is an honest and relatable discussion about media consumption, digital habits, productivity, and making technology work for your goals instead of against them. Enjoyed the episode? Be sure to like, subscribe, and leave a review for the podcast, follow Inspiration Nation on X at @ListenToIN, and visit www.InspirationNation.org.uk for more.

In this episode of Inspiration Nation, Lee Kemp and Ryan Boniface explore how social media, AI, short-form content, dopamine-driven scrolling, and the speed of modern news are reshaping the way we think. Using the quote, “We don't think our way to action, we act our way into habits of thinking,” they unpack whether we are truly developing deeper thought or simply reacting faster to an always-on digital world. From attention spans and doom scrolling to clickbait, algorithms, validation, and the rise of AI tools like ChatGPT, this conversation digs into how our opinions are formed and why intentional thinking matters more than ever.At the heart of the episode is a powerful reminder that today's challenges are not entirely new, they are just arriving in a different form: a devil in a different dress. Lee and Ryan discuss AI as a crutch or catalyst, the value of consuming diverse opinions, and why changing your mind based on informed thinking is a strength, not a weakness. If you are interested in mindset, critical thinking, social media habits, attention span, AI, personal growth, and modern decision-making, this episode is packed with insight. Like, subscribe, and leave a review to support the podcast, follow Inspiration Nation on X at @ListenToIN, and visit www.InspirationNation.org.uk for more.

En este episodio vamos a charlar sobre algunas técnicas que podemos usar para mejorar las respuestas y la calidad de nuestros prompts.

Ansh Mehra is the Founder at the Cutting Edge Group, and has trained global enterprises in UAE & India on AI and Automations. He's also represented India at the Global Prompt Engineering Championship 2025. Ansh is also the official instructor for OpenAI Academy as well, where he teaches the basics of Prompt Engineering in Hindi & English. He's competed at MIT, Harvard and Microsoft Imagine Cup as a student and also judged Stanford TreeHacks.His organisation, The Cutting Edge School has trained teams for The Economic Times, The Times of India, Dubai Future Foundation, Dubai Holdings, Lenskart, Reliance Digital, HP, Intel and many other global brands. They were also awarded the Best AI Educator of the Year by Economic Times Edge as well. His cohorts have been attended by professionals across 55 countries. His online courses have students from age 8 to 89!His profiles have a following of more than 800K+ audience of AI Learners and Developers across social media. Check him out

“If you don't specify, it will fill in the gaps itself… and that's when you go wrong.” This episode of Inspiration Nation dives into the art (and myth) of “prompt engineering,” breaking it down into something far more relatable: communication. Lee, Ryan, and Jose explore how using AI tools like ChatGPT can feel frustrating when you can't quite articulate your thoughts—but also how small changes, like setting a role, giving context, and defining the output, can transform your results. From Excel struggles to tennis coaching, the trio share real-world examples that show AI isn't magic—it's a powerful “intelligent toddler” that thrives on clear direction.Packed with practical insights and humour, this episode is a must-listen for anyone using AI for productivity, learning, or everyday problem-solving. Whether you're refining prompts, exploring tools like Microsoft Copilot, or just curious about how to get better results, you'll walk away with actionable tips to improve your workflow and confidence. Enjoyed the episode? Don't forget to like, subscribe, and leave a review! Follow us on X @ListenToIN and visit www.InspirationNation.org.uk for more inspiring content.

This Podcast is sponsored by Team Simmer. Go to TeamSimmer and use the coupon code DEVIATE for 10% on individual course purchases. The Technical Marketing Handbook provides a comprehensive journey through technical marketing principles. (Getting an update soon) Sign up to the Simmer Newsletter for the latest news in Technical Marketing. NEW SIMMER COURSE ALERT!  - Data Analysis with R - taught by Arben Kqiku LIMITED 20% off offer on the Javascript for Digital Marketers Course - Get it while it lasts! Latest content from Simo Ahava Add IPv6 Support To Your Server-side GTM Load Balancer Latest content from Juliana Jackson The business model is THE strategy (subscribe to the newsletter for more amazing content) LIVE from Measurecamp Helsinki - 40' of content about main effects & interactions with Matt Gershoff - will be available to all my Substack subcribers - sign up to my newsletter here: https://julianajackson.substack.com/ Mentioned in the episode: META announcement for new Click-Through Measurement Definition STAPE Content re: Meta Conversion tracking (comment from Stape team - Meta have changed the definition of view-through and added engaged-through etc., but it didn't affect how you report to pixel/capi) - https://stape.io/solutions/facebook-capi-tag - CAPI tag- https://stape.io/solutions/facebook-pixel-tag - pixel tag- https://stape.io/gtm-set-up-assistant Google Universal Commerce Protocol Agentic Misalignment (Anthropic): https://www.anthropic.com/research/agentic-misalignment Natural Emergent Misalignment from Reward Hacking (Anthropic): https://assets.anthropic.com/m/74342f2c96095771/original/Natural-emergent-misalignment-from-reward-hacking-paper.pdf This podcast is brought to you by Juliana Jackson and Simo Ahava.

Why 90% of organizations use AI but only 9% have mastered it — and how that gap is your golden ticket to freedom https://DarkHorseEntrepreneur.com Episode Summary Discover the 9 essential AI skills every digital entrepreneur and busy parent should master to create profitable side hustles and replace their paychecks. In this episode, we explore how AI-driven online entrepreneurship offers incredible marketing strategies and income opportunities. Learn why AI-skilled professionals earn significantly more and how this trend is reshaping the work-from-home landscape for parents seeking flexible, passive income streams. We'll guide you through step-by-step methods to develop these in-demand skills starting today, helping you balance entrepreneurship with family life. Tune in to gain insights into digital marketing tips, online business strategies, and how to harness AI for sustainable financial freedom while preserving precious family time. Key Timestamps & Insights 00:00 - Opening 01:15 - Episode Overview 05:00 - The Discovery 06:00 - Skill #1: AI Literacy 07:30 - Skill #2: Prompt Engineering 09:15 - Skill #3: AI Tool Proficiency 10:45 - Skill #4: Critical AI Evaluation 12:00 - Skill #5: AI-Powered Data Analysis 13:30 - Skill #6: AI Automation Engineering 15:30 - Skill #7: AI Ethics and Governance 17:00 - Skill #8: Human-AI Collaboration 18:15 - Skill #9: Continuous Learning and Adaptation 20:30 - The Bigger Picture 21:45 - Whiskered Wisdom Strategies Shared AI Literacy Development Strategy Daily 30-minute experimentation with AI tools Challenge AI responses and ask for reasoning Build intuition through hands-on practice Prompt Engineering Mastery Four-part formula: Role, Context, Command, Format Develop master prompts for recurring tasks Focus on one task type before expanding Tool Proficiency Approach Pick one AI tool and master it completely Depth over breadth strategy Integrate tools into existing workflows Critical Evaluation Framework Three-question system for every AI output Cross-reference important information Understand AI limitations and biases Automation Implementation Start with one repetitive task Use no-code platforms connected to AI services Build workflows that run independently Resources Mentioned AI Tools: ChatGPT (OpenAI) Claude (Anthropic) Microsoft Copilot Google Gemini Automation Platforms: Zapier Make.com n8n Microsoft Power Automate Learning Frameworks: OECD AI Literacy Competencies Partnership for 21st Century Learning Pyramid Principle (referenced in style) Research Sources: World Economic Forum skills projection BBC AI accuracy study Stanford University collaboration research Microsoft Copilot productivity data Action Steps to Take Immediate (This Week): Choose one of the 9 AI skills that resonates with your situation Spend 30 minutes researching that specific skill Sign up for one AI tool (ChatGPT, Claude, or Copilot) Practice the three-question evaluation framework Short-term (Next Month): Develop your first master prompt for a recurring task Identify one repetitive workflow to automate Join AI communities and networks Create a learning schedule for skill development Long-term (Next Quarter): Master your chosen foundational skill completely Begin developing a second complementary skill Apply skills to create income-generating opportunities Document your progress and results Subscribe to the AI Escape Plan newsletter for parents ready to break free from the 9-to-5 grind. Get praical, AI-powered strategies to start, grow, and streamline side hustles while protecting family time.   DarkHorseInsider.com

In this episode of CDW Tech Talks, Brian Matthews and Ashley Otto explore how organizations can train and leverage AI Copilot agents effectively within their workflows. They focus on practical strategies, real-world use cases and best practices to maximize AI agent impact. To learn more, visit cdw.ca Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The truth is, most financial advisors know they should be using AI. Very few know where to actually start. Too many tools. Too many platforms. Too much noise. But the advisors who take the time to learn it now will have a significant edge over those who wait. In this special edition of Advisor Talk, Frank LaRosa is joined by Chief Information Officer Sue Cheema, Chief Marketing Officer Brian Lutz, Director of Marketing and Brand Strategy Wade Shields, and co-host Stacey Frank for a wide-ranging roundtable on what AI actually means for financial advisors today. The group breaks down how advisors can use AI to grow their business, serve clients more effectively, and free up time, including how to build custom GPTs, craft better prompts, and choose the right platform for the right task. They also address the bigger picture: what AI will never be able to replace, why the human side of financial advising remains irreplaceable, and why advisors who ignore AI risk being left behind by the ones who embrace it. Frank and the team also discuss how AI is changing the way advisors should think about their brand, their marketing, and the client experience, and why the advisors who lean into what AI cannot do will be the ones who win long term.   Questions answered in this episode include: Will AI replace financial advisors? How should a financial advisor start using AI in their practice? What is the difference between ChatGPT, Claude, and Gemini? What is a custom GPT and how can advisors use one? What is prompt engineering and why does it matter? How is AI changing financial advisor marketing and branding? What can AI never replace in the advisor-client relationship?   Chapters: 00:00 – Introduction and Why AI Matters for Advisors 03:57 – How Firms Are Already Using AI to Scan Books of Business 07:03 – What AI Cannot Replace: Empathy and the Human Edge 11:23 – Prompt Engineering: How to Get Better Answers from AI 14:10 – Building Custom GPTs for Your Advisory Practice 22:37 – ChatGPT vs. Claude vs. Gemini: Which One Should You Use 44:08 – Why AI Will Not Replace Advisors But This Will 49:05 – How to Reach the Team at Elite Consulting Partners   Learn more about Elite and our resources: Elite Consulting Partners | Financial Advisor Transitions https://eliteconsultingpartners.com Elite Marketing Concepts | Marketing Services for Financial Advisors https://elitemarketingconcepts.com Elite Advisor Successions | Advisor Mergers & Acquisitions https://eliteadvisorsuccessions.com JEDI Database Solutions | Technology Solutions for Advisors https://jedidatabasesolutions.com Listen to more Advisor Talk episodes: https://eliteconsultingpartners.com/podcasts/ Follow us on LinkedIn: https://www.linkedin.com/company/elite-consulting-partners/ Listen to more Advisor Talk episodes: https://eliteconsultingpartners.com/podcasts/

Die größte Chance für Organisationen seit Jahrzehnten

Send a textFirst Aired Apr 23, 2025If you've been following the AI space lately, this episode hits differently the second time around.When Al sat down with Ruchir Puri — Chief Scientist of IBM Research, IBM Fellow, and the architect behind Watson and watsonx — the conversation covered ground that's only gotten more relevant since: the death of prompt engineering, the rise of agentic AI, and why 2025 was always going to be the year agents broke through in the enterprise.Ruchir doesn't deal in hype. He deals in systems — real ones, running at scale, in industries where a hallucinated number has consequences. In this masterclass, he walks through inference scaling, memory in AI systems, and what it actually means to build AI that's useful rather than just impressive.If you're new to the show, this is the episode to start with. If you've heard it before — trust us, it lands differently now.Key moments:12:21 — Why prompt engineering is already fading (and what replaces it)13:39 — Inference scaling: the frontier that's not about training anymore16:26 — Why AI systems that "forget" are failing us17:56 — The full agentic loop: Think, Plan, Act, Execute, Observe, Reflect23:45 — Why enterprise AI agents are no longer a future stateMaking Data Simple is hosted by Al Martin, WW VP Technical Sales, IBM.Ruchir's LinkedinAl's LinkedInExplore IBM's WatsonxWant to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. 

Send a textFirst Aired Apr 23, 2025If you've been following the AI space lately, this episode hits differently the second time around.When Al sat down with Ruchir Puri — Chief Scientist of IBM Research, IBM Fellow, and the architect behind Watson and watsonx — the conversation covered ground that's only gotten more relevant since: the death of prompt engineering, the rise of agentic AI, and why 2025 was always going to be the year agents broke through in the enterprise.Ruchir doesn't deal in hype. He deals in systems — real ones, running at scale, in industries where a hallucinated number has consequences. In this masterclass, he walks through inference scaling, memory in AI systems, and what it actually means to build AI that's useful rather than just impressive.If you're new to the show, this is the episode to start with. If you've heard it before — trust us, it lands differently now.Key moments:12:21 — Why prompt engineering is already fading (and what replaces it)13:39 — Inference scaling: the frontier that's not about training anymore16:26 — Why AI systems that "forget" are failing us17:56 — The full agentic loop: Think, Plan, Act, Execute, Observe, Reflect23:45 — Why enterprise AI agents are no longer a future stateMaking Data Simple is hosted by Al Martin, WW VP Technical Sales, IBM.Ruchir's LinkedinAl's LinkedInExplore IBM's WatsonxWant to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. 

In this episode of the Scrum.org Community Podcast, Eric Naiburg, COO at Scrum.org  and Darrell Fernandes, Executive Advisor at Scrum.org continue to dive into how to make AI a true teammate in product development while answering questions from a recent webinar on the topic. They explore the importance of creating a context library to store domain-specific knowledge, enabling AI to provide accurate, efficient answers. Learn how consistent definitions, thoughtful prompt engineering, and regular updates to your AI context can improve team collaboration, reduce costs, and empower Scrum Masters to guide effective AI usage.

Lots of people are afraid of artificial intelligence and its potential for deception, fraud, harm and control. We also know that the bible's words will be fulfilled when the NWO system weaponizes this technology to shut dissidents out of society. But can such a thing glorify God? Today I want to share with you some thoughts after spending many hours working on a big project involving AI, and what I learned about technology and the glory of God. * 00:00 - Introduction* 25:35 - Lesson #1: Challenges & Good Works* 33:24 - Lesson #2: Computers & The Gospel* 45:42 - Lesson #3: Creation* 59:27 - Lesson #4: Prompt Engineering * 1:12:18 - Lesson #5: God's Sovereignty* 1:27:47 - Final Thoughts This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.danceoflife.com/subscribe

Send a textAI automation is changing how businesses handle sales calls, website builds, internal systems, and admin tasks using AI agents, prompt engineering, and real business data. This episode breaks down real world AI use cases including sales call analysis, website automation, email prioritization, and building internal AI software to replace manual workflows. Learn how companies can use AI integration, AI coding tools, and process documentation to improve efficiency, reduce overhead, and prepare for the AI shift already happening.If AI is already costing you time and money, get on a strategy call and build a custom AI system before your competitors figure it out: https://bit.ly/4jMZtxu#AIautomation #BusinessAutomation #ArtificialIntelligence #AIagents #entrepreneurship --------------------------------------------------------------------------Want free resources? Dowload our Free Amazon guides here:2026 Q1 Repeat Buyer Formula: https://bit.ly/47KJmOdGrowth Email Marketing Strategies: https://hubs.ly/Q04457QF0Amazon Proft Margin Defense 2026: https://hubs.ly/Q042trRH0Amazon SEO Toolkit 2026: https://bit.ly/4oC2ClTAmazon Seller Strategy Report 2026: https://bit.ly/3YN1RME2026 Ecommerce Website & SEO Readiness Checklist: https://hubs.ly/Q040Jg0M0Amazon Crisis Kit: https://bit.ly/4maWHn0TIMESTAMPS00:00 – AI Is Finally Ready for Business02:00 – Using AI to Analyze Sales Calls and Customer Pain Points04:00 – Extracting Amazon Seller Pain Points With AI Tools05:20 – Why Businesses Are Pivoting to AI Services09:56 – The AI Singularity and What It Means for Companies14:30 – Cutting Costs With AI Instead of Cutting Teams17:00 – Replacing Admin Work With AI Agents18:58 – Building an AI Website in One Afternoon21:35 – Live Demo: Updating a Website With AI25:42 – Building Internal AI Software With Company Data28:00 – Prompt Engineering and Iteration at Scale30:40 – Automating Email With AI for Daily Efficiency32:28 – Packaging AI Services and Selling in Public34:56 – Why AI Content Can Reach a Bigger Audience36:04 – Fixing Websites Fast With AI38:46 – AI FOMO and Moving Before It's Too Late________________________________Follow us:LinkedIn: https://www.linkedin.com/company/28605816/Instagram: https://www.instagram.com/stevenpopemag/Pinterest: https://www.pinterest.com/myamazonguys/Twitter: https://twitter.com/myamazonguySubscribe to the My Amazon Guy podcast:My Amazon Guy podcast: https://podcast.myamazonguy.comApple Podcast: https://podcasts.apple.com/us/podcast/my-amazon-guy/id1501974229Spotify: https://open.spotify.com/show/4A5ASHGGfr6s4wWNQIqyVwSupport the show

This conversation was recorded at GOTO Copenhagen 2025.https://gotocph.comRod Johnson - Building the future of agent frameworks at EmbabelArjen Poutsma - Practical Insights from a Spring Framework VeteranTrisha Gee - Award-winning Engineer, Author and PC MemberRESOURCESRodhttps://twitter.com/springrodhttps://github.com/johnsonrhttps://www.linkedin.com/in/johnsonrodahttps://the-composition.com/@springrodArjenhttps://bsky.app/profile/poutsma.bsky.socialhttps://fosstodon.org/@poutsmahttps://github.com/poutsmahttps://www.linkedin.com/in/arjen-poutsma-288ba6Trishahttps://bsky.app/profile/trishagee.bsky.socialhttps://twitter.com/trisha_geehttps://github.com/trishageehttps://www.linkedin.com/in/trishageehttps://trishagee.comABSTRACTAsk me anything.Read the full abstract here:https://gotocph.com/2025/sessions/3927RECOMMENDED BOOKSRod Johnson • Expert One-On-One J2Ee Design and Development • https://amzn.to/48oCxAJJohnson, Höller, Arendsen, Risbert & Sampaleanu • Professional Java Development with the Spring Framework • https://amzn.to/44J4SRbTrisha Gee & Helen Scott • Getting to Know IntelliJ IDEA • https://amzn.to/3ZBgnGcKevlin Henney & Trisha Gee • 97 Things Every Java Programmer Should Know • https://amzn.to/3kiTwJJTrisha Gee, Kathy Sierra & Bert Bates • Head First Java • https://amzn.to/3k59BJ6BlueskyTwitterInstagramLinkedInFacebookCHANNEL MEMBERSHIP BONUSJoin this channel to get early access to videos & other perks:https://www.youtube.com/channel/UCs_tLP3AiwYKwdUHpltJPuA/joinLooking for a unique learning experience?Attend the next GOTO conference near you! Get your ticket: gotopia.techSUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

Seit den frühen Tagen des "Prompt Engineering" hat sich viel getan. Wie kommt man im Jahr 2026 zu den besten Ergebnissen?

In this episode of Hands-On IT, host Landon Miles is joined by Automox Security Engineer Henry Smith for a deep dive into prompt engineering and how it's transforming the way IT and security teams work with AI.From crafting high-quality prompts to auditing and hardening code using large language models like Claude and ChatGPT, Landon and Henry share real-world insights, practical strategies, and lessons learned from implementing AI in secure development workflows.They also explore:Why context is king when prompting AISecurity implications of AI-generated codeTips for optimizing token usage and context windowsHow Automox engineers are experimenting safely with AIWhether you're a developer, security professional, or IT leader, this episode offers actionable advice and forward-thinking perspectives on integrating AI into your workflow.This episode originally aired July 29, 2025. 

The marketing teams winning with AI today are not the ones chasing every new model release. They are the ones who found the boring, repetitive tasks their teams hate and automated those first.Nir Pochter, Co-Founder and CMO at Lightricks, joins Stephanie Postles on Marketing Trends to break down what AI actually means for creative workflows and why most teams are still using it wrong.You'll learn:- The "algebra problem" of AI adoption- How to save your design team 80% of their time- Why the gap between marketers who use AI well and those who don't is widening fast.- How to use an LLM scoring system to pre-review documents for you- The dangerous trend of "AI Marketer" job titles- What's really in store for the future of video+AI Key Moments:00:00 — Why AI Hasn't Improved Creative Output Yet02:06 — The Algebra Problem: Tools vs. Knowing How to Use Them07:27 — Nir's Background: AI PhD to Lightricks and FaceTune09:46 — What Used to Take Weeks Now Takes Minutes13:35 — Why Automating Everything Failed Miserably16:38 — Start with What People Hate Doing20:08 — The LLM Scoring System: Nothing Gets Reviewed Without an 8521:43 — Train Your LLM to Be Mean, Not Nice23:32 — Building Custom GPTs with Company Guidelines26:30 — The Pitfall: Using AI to Please Leadership28:47 — From Toys to Tools: Why Text-to-Video Isn't Enough31:05 — Coca-Cola's 70,000 Prompts (Was It Worth It?)34:41 — AI Won't Replace Creatives, But This Will37:04 — The Two Critical Skills: Prompting and Curation37:55 — How AI Multiplies the Skills Gap (7 vs 10 Example)42:47 — What CMOs Should Be Asking Their Teams46:20 — Why "AI Marketer" Is LinkedIn Fluff This episode is brought to you by Lightricks. LTX is the all-in-one creative suite for AI-driven video production; built by Lightricks to take you from idea to final 4K render in one streamlined workspace.Powered by LTX-2, our next-generation creative engine, LTX lets you move faster, collaborate seamlessly, and deliver studio-quality results without compromise. Try it today at ltx.studio Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

IBF On Demand sponsored by Arkieva, your one-plan S&OP software. Learn more about Arkieva's innovative approach to forecasting here httpbit.lybusiness-forecasting In this bold episode, I deliver a powerful warning that every planner, forecaster, and supply chain professional needs to hear. This isn't anti-AI. But there are things we are doing wrong and the ugly side of AI misuse every day. We've glamorized LLMs, prompt engineering, and automated insights, yet many are unknowingly trading clarity for convenience, and intelligence for illusion. What you think is making you faster and sound smarter is exposing you and maybe making things worse.Support the showTo sign up for regular updates and the latest research, events, articles, podcasts and more from the Institute of Business Forecasting & Training, visit www.ibf.org

در این اپیزود تحلیلی و آموزنده از مدرسه زندگی فارسی، با استفاده از بهانه‌ای به‌نام هوش مصنوعی، به یکی از مهم‌ترین مهارت‌های فراموش‌شده‌ی زندگی می‌پردازیم: توانایی دقیق خواستن و بیان جزئیات خواسته‌ها. مهارتی که در قالب "پرامپت نویسی" در دنیای امروز، هم در کار با هوش مصنوعی و هم در ارتباطات انسانی نقش حیاتی دارد.در این ویدیو می‌آموزیم:چرا ذهن ما اغلب توانایی تجسم جزئیات خواسته‌ها را ندارد؟چگونه کودکی، تجربه‌های عاطفی و فرهنگ ما، زبان خواستن را شکل می‌دهد؟چرا اغلب در بیان اهداف و خواسته‌هایمان دچار تعارف و لکنت می‌شویم؟چگونه با تمرین و شناخت دقیق‌تر واژه‌ها، ایده‌هایمان را به واقعیت تبدیل کنیم؟چیستی و اهمیت «مهندسی دستور» یا Prompt Engineering در هوش مصنوعی و زندگی واقعیچرا خجالت یا پرتوقع بودن، مانع تحقق اهداف ما می‌شود؟چگونه بازخورد (فیدبک) از هوش مصنوعی و دیگران، می‌تواند ما را به بازنویسی مسیر هدایت کند؟این ویدیو تلاشی‌ست برای ایجاد یک نگاه جدید به هنر خواستن، هنر توصیف، و مهارت ساختن ایده در دنیایی که دیگر ابزارها آماده‌اند، ولی واژه‌ها و نیت‌ها هنوز شکل نگرفته‌اند.لینک ویدیوی انگلیسی:https://youtu.be/7Z1XanIyUEA#پرامپت_نویسی #هوش_مصنوعی #توسعه_فردی #مهارتهای_زندگی #مدرسه_زندگی_فارسی #PromptEngineering #AIcommunication #خودسازی #کلمات_دقیق #فلسفه_هوش_مصنوعی #زندگی_آگاهانه #گفتگو_موثر #مهارت_خواستن #AIthinking #درک_عمیق #پادکست #مرور_کتاب#کتاب_صوتی #ایمان_فانی #مدرسه_زندگی_فارسی #تحلیل #مطالعات_میان_رشته‌ای #podcast #interdisciplinary_Studies #iman_fani #persian_school_of_life لینک حمایت مالی:https://hamibash.com/schoolخرید دوره‌های آموزشی در خارج از کشور:https://imanfani.thinkific.comخرید دوره‌های آموزشی در ایران:https://b2n.ir/a19688https://imanfani.comhttps://instagram.com/dr_iman_fanihttps://telegram.me/dr_iman_faniلینک ویدیوی انگلیسی و کانال یوتیوب ورد ولکانhttp://www.youtube.com/@WordVulcanPress Hosted on Acast. See acast.com/privacy for more information.

What happens when every major AI model gets jailbroken within days? This week, the world's most prolific AI red teamer lifts the curtain on how and why "safe" AI might be an impossible promise. Pliny the Liberator | pliny.gg - discord.gg/basi ChatGPT Nears 900 Million Weekly Active Users But Gemini is Catching Up From Llamas to Avocados: Meta's shifting AI strategy is causing internal confusion Google Tells Advertisers It'll Bring Ads to Gemini in 2026 Meta Acquires Limiteless, an A.I. Pendant Company Backed by Sam Altman Here's how Google is laying the foundation for our mixed reality future OpenAI, Anthropic, and Block Are Teaming Up to Make AI Agents Play Nice Svedka's First Super Bowl Ad Will Be Made Primarily With AI AI Slop Is Ruining Reddit for Everyone TESCREALers paying journalists at major outlets to cover AI The Resonant Computing Manifesto (from Masnick) Techdirt fundraiser From Sam Lessin: Tech bros head to etiquette camp as Silicon Valley levels up its style Bare Metal Email Jeff in Austria Golden Globes enter the world of podcasts and tread carefully, avoiding controversy Who says AI isn't useful? Real-time Cricket Sorting By Sex Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Pliny the Liberator Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: auraframes.com/ink ventionteams.com/twit agntcy.org outsystems.com/twit

What happens when every major AI model gets jailbroken within days? This week, the world's most prolific AI red teamer lifts the curtain on how and why "safe" AI might be an impossible promise. Pliny the Liberator | pliny.gg - discord.gg/basi ChatGPT Nears 900 Million Weekly Active Users But Gemini is Catching Up From Llamas to Avocados: Meta's shifting AI strategy is causing internal confusion Google Tells Advertisers It'll Bring Ads to Gemini in 2026 Meta Acquires Limiteless, an A.I. Pendant Company Backed by Sam Altman Here's how Google is laying the foundation for our mixed reality future OpenAI, Anthropic, and Block Are Teaming Up to Make AI Agents Play Nice Svedka's First Super Bowl Ad Will Be Made Primarily With AI AI Slop Is Ruining Reddit for Everyone TESCREALers paying journalists at major outlets to cover AI The Resonant Computing Manifesto (from Masnick) Techdirt fundraiser From Sam Lessin: Tech bros head to etiquette camp as Silicon Valley levels up its style Bare Metal Email Jeff in Austria Golden Globes enter the world of podcasts and tread carefully, avoiding controversy Who says AI isn't useful? Real-time Cricket Sorting By Sex Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Pliny the Liberator Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: auraframes.com/ink ventionteams.com/twit agntcy.org outsystems.com/twit

What happens when every major AI model gets jailbroken within days? This week, the world's most prolific AI red teamer lifts the curtain on how and why "safe" AI might be an impossible promise. Pliny the Liberator | pliny.gg - discord.gg/basi ChatGPT Nears 900 Million Weekly Active Users But Gemini is Catching Up From Llamas to Avocados: Meta's shifting AI strategy is causing internal confusion Google Tells Advertisers It'll Bring Ads to Gemini in 2026 Meta Acquires Limiteless, an A.I. Pendant Company Backed by Sam Altman Here's how Google is laying the foundation for our mixed reality future OpenAI, Anthropic, and Block Are Teaming Up to Make AI Agents Play Nice Svedka's First Super Bowl Ad Will Be Made Primarily With AI AI Slop Is Ruining Reddit for Everyone TESCREALers paying journalists at major outlets to cover AI The Resonant Computing Manifesto (from Masnick) Techdirt fundraiser From Sam Lessin: Tech bros head to etiquette camp as Silicon Valley levels up its style Bare Metal Email Jeff in Austria Golden Globes enter the world of podcasts and tread carefully, avoiding controversy Who says AI isn't useful? Real-time Cricket Sorting By Sex Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Pliny the Liberator Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: auraframes.com/ink ventionteams.com/twit agntcy.org outsystems.com/twit

What happens when every major AI model gets jailbroken within days? This week, the world's most prolific AI red teamer lifts the curtain on how and why "safe" AI might be an impossible promise. Pliny the Liberator | pliny.gg - discord.gg/basi ChatGPT Nears 900 Million Weekly Active Users But Gemini is Catching Up From Llamas to Avocados: Meta's shifting AI strategy is causing internal confusion Google Tells Advertisers It'll Bring Ads to Gemini in 2026 Meta Acquires Limiteless, an A.I. Pendant Company Backed by Sam Altman Here's how Google is laying the foundation for our mixed reality future OpenAI, Anthropic, and Block Are Teaming Up to Make AI Agents Play Nice Svedka's First Super Bowl Ad Will Be Made Primarily With AI AI Slop Is Ruining Reddit for Everyone TESCREALers paying journalists at major outlets to cover AI The Resonant Computing Manifesto (from Masnick) Techdirt fundraiser From Sam Lessin: Tech bros head to etiquette camp as Silicon Valley levels up its style Bare Metal Email Jeff in Austria Golden Globes enter the world of podcasts and tread carefully, avoiding controversy Who says AI isn't useful? Real-time Cricket Sorting By Sex Hosts: Leo Laporte, Jeff Jarvis, and Mike Elgan Guest: Pliny the Liberator Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: auraframes.com/ink ventionteams.com/twit agntcy.org outsystems.com/twit

Too many business owners are trying to use AI as a shortcut to fire people instead of using it to multiply the output of their best people. And that mindset is killing their growth. Matt Leitz has been building automation systems for 7- and 8-figure companies long before AI went mainstream. He's seen inside the machines powering 9-figure brands… and the truth is simple: automation isn't optional anymore. If you want to scale, you need a business that compounds output without requiring more of your time. Matt breaks down how to use AI as leverage — not as a crutch. He shares where founders get stuck, which systems create the highest ROI, how to turn funnels profitable even when ads lose money on day one, and how to build automations that drive revenue for years. If you've been trying to figure out how to integrate AI without breaking your business, this conversation will completely reset your framework.     Key Takeaways 00:00 Intro 01:36 You're Thinking About AI All Wrong 02:54 AI Agents and Chatbots 05:24 Start With Strategy, Not Technology 08:09 Why You Shouldn't Automate Reporting 11:22 Prompt Engineering is Easier Than You Think 16:04 How To Build & Leverage Custom GPTs 20:41 Collaborating With AI For Better Results 27:10 AI Tool that Boosts Sales Rep Performance 30:06 Why Tool-Hopping Slows Your Growth 31:50 Why Automation Is Required To Scale Big 35:35 Are Traditional Marketing Funnels Dead? 41:03 When to Focus ON or IN the Business 45:42 The Real Path To Scaling Ad Spend 54:03 Lead Offers vs. Maximizer Offers 01:02:06 Protecting Your Time Above Everything Else     Watch on YouTube: https://youtu.be/F96ncjHK8jI    Let's Connect: Website | Instagram | YouTube | TikTok | Twitter | Facebook

- Simulation Theory, AI, and Robots for Survival (0:11) - Global Political Tensions and Predictions (1:33) - Economic and Social Implications of Global Conflict (6:49) - The Era of Easy Money and Affordable Goods Ending (7:55) - Preparing for a Collapsing Economy (20:50) - Using AI and Robots for Survival and Decentralization (30:50) - The Role of Drones and Ground-Based Robots (43:32) - The Future of AI and Robotics in Society (56:02) - The Importance of Financial Preparedness (1:01:21) - The Role of AI in Defining Wealth and Success (1:13:48) - Mike Adams' Background and Skills (1:23:20) - The Importance of Clear Instructions for AI (1:25:50) - AI Agents and Their Applications (1:28:42) - Prompt Engineering and AI Skills (1:33:02) - Philosophical and Ethical Considerations of AI (1:34:33) - AI and Human Depopulation Vectors (1:43:05) - The Role of AI in Government and Society (1:47:35) - The Future of Human-AI Relationships (2:00:04) - The Ethical Implications of AI Development (2:02:59) - The Potential for AI to Replace Human Labor (2:04:41) For more updates, visit: http://www.brighteon.com/channel/hrreport  NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

- Endorsement of Pete Chambers for Texas Governor (0:10) - Chambers' Commitment to Decentralized Medicine and Humanitarian Efforts (1:41) - Importance of Prompt Engineering in AI (4:26) - AI's Role in Software Development and Prompt Engineering Techniques (5:53) - Prediction of a Major Robotics Hoax (19:27) - Comparison of Mainstream Deodorants and Health Ranger Store Deodorant (28:54) - Health Benefits of Purple Okra and Anthocyanins (40:02) - RFK Jr's Investigation into Psychiatric Medications and School Shootings (42:53) - Texas' Role in the Future of the United States (51:09) - Nutritional Tips for Enjoying Barbecue (55:42) - Energy Consumption and Water Usage by Data Centers (1:08:35) - Impact of Data Centers on Texas' Power Grid (1:19:53) - Economic and Environmental Concerns (1:20:58) - Water and Land Use Conflicts (1:23:37) - Governor's Role and Citizen-Led Governance (1:26:36) - Border Security and Governor Abbott's Performance (1:27:34) - Health and Human Services Expenditures (1:34:46) - Education and Food Security Initiatives (1:49:40) - Challenges of Political Corruption and Centralization (1:51:09) - Vision for Texas' Future (2:08:42) For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com

- Announcement of Enoch AI Engine Upgrade (0:03) - Accessing Enoch AI Engine (2:29) - Prompt Engineering and Use Cases (4:59) - Challenges and Successes in Training Enoch (9:25) - Applications and Benefits of Enoch AI Engine (12:21) - Demonstration and Comparison with Other AI Engines (18:10) - Support and Future Plans (1:06:27) - Enoch's Impact on Independent Media (1:17:07) - Conclusion and Call to Action (1:17:27) For more updates, visit: http://www.brighteon.com/channel/hrreport NaturalNews videos would not be possible without you, as always we remain passionately dedicated to our mission of educating people all over the world on the subject of natural healing remedies and personal liberty (food freedom, medical freedom, the freedom of speech, etc.). Together, we're helping create a better world, with more honest food labeling, reduced chemical contamination, the avoidance of toxic heavy metals and vastly increased scientific transparency. ▶️ Every dollar you spend at the Health Ranger Store goes toward helping us achieve important science and content goals for humanity: https://www.healthrangerstore.com/ ▶️ Sign Up For Our Newsletter: https://www.naturalnews.com/Readerregistration.html ▶️ Brighteon: https://www.brighteon.com/channels/hrreport ▶️ Join Our Social Network: https://brighteon.social/@HealthRanger ▶️ Check In Stock Products at: https://PrepWithMike.com