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-At some point in the last couple days, Grok began to offer extremely over the top opinions about Musk. The bot claimed that Musk is the "undisputed pinnacle of holistic fitness" and that he is more fitter than LeBron James, smarter than Albert Einstein, better fighter than Mike Tyson, morally superior to Jesus, and a better communist than Joseph Stalin. -FoloToy, a company selling AI-enabled toys, suspended sales of its products after a consumer safety report showed there were few restrictions around what its toys would talk about. -After what was apparently a successful testing period, OpenAI has announced that it is rolling out group chats in ChatGPT to "all logged-in users on ChatGPT Free, Go, Plus and Pro plans globally over the coming days." Learn more about your ad choices. Visit podcastchoices.com/adchoices
On today's episode, Johnnette Williams gives us practical steps in discerning Gods Will! She shares how to determine if its the prompting of the Holy Spirit and the virtues that can come forth from it.
El video que comento en el podcast es este. https://youtu.be/pmsTzFLM8rI?si=9JwensxldqHa32pm Video del curso de Prompting es este https://youtu.be/otqHo7G3OzYDarle cariño... www.discosduros.net
In unserer neuen Podcastfolge wird's technisch, nostalgisch und ein bisschen juristisch. Tobi erzählt, wie smarte Glühbirnen plötzlich zu Präsenzsensoren werden, warum eine Diskettenbox für Flashbacks sorgt und wie Sponsoren-Logos KI-seitig eigentlich automatisiert werden könnten. Dazu sprechen wir über den GEMA-Rechtsstreit gegen OpenAI und warum Kim Kardashian ihre Jura-Prüfung wegen ChatGPT vermasselt hat. Reinhören lohnt sich! -- Links zur Folge immer auf https://podcast.ichglaubeeshackt.de/ Wenn Euch unser Podcast gefallen hat, freuen wir uns über eine Bewertung! Feedback wie z.B. Themenwünsche könnt Ihr uns über sämtliche Kanäle zukommen lassen: Email: podcast@ichglaubeeshackt.de Web: podcast.ichglaubeeshackt.de Instagram: http://instagram.com/igehpodcast
Kontakt & EventsWillst du dabei sein? Schreib uns unter support@systemischer-club.de.Alle kostenfreien Online-Events findest du unter https://kalifornische-terrassen.de/events.
Marketing-Erfolg steigern durch klare Positionierung und kreatives Branding
In Folge #60 von The Walk of Brand – MARKE. MACHT. UMSATZ. geht es um eine unbequeme Wahrheit: Das klassische Agenturmodell hat ausgedient. Automatisierung, KI und datengetriebene Tools übernehmen die Aufgaben, für die früher ganze Teams bezahlt wurden, und das verändert alles. Denn die Agentur der Zukunft ist kein Dienstleister mehr. Sie ist ein strategischer Sparringspartner auf C-Level, der Marketing mit der Unternehmensstrategie verknüpft und echte Umsatzhebel bewegt. In dieser Episode erfährst du: • Warum klassische Agenturen im KI-Zeitalter keine Zukunft haben • Wie die „Agentur der Zukunft“ als ausgelagerter CMO agiert • Warum Marketing ins Board gehört – nicht ins Backoffice • Wie KI und Prompting zum neuen Wettbewerbsvorteil werden • Was Unternehmer heute tun müssen, um Marketing intelligent zu steuern Diese Folge ist für Unternehmer, Entscheider und Markenstrategen, die verstanden haben: Marketing ist kein Kostenblock, es ist ein Machtinstrument.
"The future won't belong to humans or machines, but to those who master the hybrid skill set combining AI literacy and human literacy."The future of work is not about humans versus machines. Instead, it belongs to those who master a unique hybrid skill set. This blend combines AI literacy with essential human capabilities. Literacy in today's world lies in the ability to learn, unlearn and relearn - this has never been more true as it is in today's partnership with Agentic AI. Andréa and I delve into the what these combined forces could look like, and how to build the framework for operational implementation. Digital transformation requires a hybrid skill set that fulfils the three different facets of transformation (cognitive, behavioural and emotional), which in turn align with the aspects of workplace culture (how we think, act and interact). We discuss how to build a culture of trust in AI, essential for successful collaboration and highlight a critical distinction : humans interpret data semantically, giving it meaning and purpose, while AI processes it syntactically, based on patterns and probabilities. This difference impacts decision-making and ethical considerations. Leaders of the future must be honest about and clearly see what tasks should be augmented using AI and how the time saved should be spent, i.e. what does AI do best now and, consequently, what should humans do better?How are you ensuring that you, your teams & your organisation are developing the skills necessary to complement AI's analytical power and drive results together. The main insights you'll get from this episode are : - Democratising access to a hybrid skill set means defining how to navigate the ‘fear vs. opportunity' narrative of human potential in a world of AI, harking back to ‘man vs. machine' as opposed to embracing a ‘man with machine' approach.- Digital transformation requires a hybrid skill set that fulfils the three different facets of transformation (cognitive, behavioural and emotional), which in turn align with the aspects of workplace culture (how we think, act and interact).- The cognitive transformation element, i.e. decision-making, is the most problematic for leaders as humans still believe in the old way of making decisions; leaders are most exposed to this risk due to their past successes.- In the words of Rasmus Hougaard, “ego is the worst enemy of leadership” and hampers effective decision-making - AI makes new things possible and humans are taken aback by the exponential rate at which we must learn and unlearn.- Prompting, data sense-making and re-perception mean that we need to craft better input for AI but also ask humans better questions - unexpected questions open our minds to novelty and creativity.- Our inherited educational model rewards good answers, not good questions, yet this stifles creativity and re-perception; the latter goes against the human (and educational) grain, but AI tools represent a good sparring partner.- Rather than a product-centric approach, we are now called upon to make sense of data, but AI and humans interpret data differently: humans interpret it semantically (adding their own perspective); AI interprets it syntactically (as tokens without understanding meaning).- The problem inherent to AI is that it does not understand or give meaning to its decisions and has no conscience about the action taken - humans must have responsibility for giving data meaning and not outsource this to AI.- AI learns on a binary basis without context; tasks that are too demanding...
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Rory and Drew return from Halloween with coffee, chaos, and a nerdfest on node-based creation. They speed-run Midjourney office hours, gripe about missing “make him smile” buttons, then crack open the new wave: nodes in Krea, Freepik Spaces, and Weavy...batching, branching, and wiring prompts like a patch bay. Drew admits he's been using v6 personalization inside v7 like a goblin. Rory shows how to spin one image into 20+ shots and auto-write video prompts, then turns pencil sketches into cinematic frames with structure-reference wizardry. It's equal parts workshop and roast of their past selves.--⏱️ Midjourney Fast Hour0:01 – "Tell your dog walker to subscribe” 1:08 – 55 episodes in: what Midjourney Fast Hours is really about3:25 – Midjourney Office Hours recap: dev updates, bugs, and feature requests5:02 – Multiple feature drops teased for next week6:39 – v7 release timing + hopes for a true creative studio UI9:02 – Wishlist: multi-character control, angles, expressions, and seed editing12:29 – Prompting real facial expressions (test simple → build complexity)15:13 – Pro tip: community rating = free Fast Hours learning16:02 – Hack: using v6 personalization codes inside v717:12 – The Node Revolution begins — why nodes fix creative workflow pain22:12 – Krea Nodes deep dive: blueprints, drag-to-wire, product-swap demo31:39 – Image-to-video inside Krea: turning stills into motion35:04 – Batch-generation magic: LLM → 10 prompts → parallel image runs43:07 – Weavy “app view” — simplified node interface for creators45:58 – Freepik Spaces walkthrough: collaborative canvas + node workflows48:25 – Quick win: “4 on demand” + unlimited Nano runs in Freepik49:18 – Rumor mill: Nano Banana 2 incoming50:25 – Seedream vs Nano: angle agility vs object consistency55:27 – Merch detour: Fast Hours T-shirt mockups built with nodes59:26 – Sketch-to-cinema using Mystic (Magnific) for structure-reference1:05:38 – Wrap-up: what's next for nodes and upcoming Midjourney updates1:07:08 – Tease: live AMA event coming in November
In this episode, Aydin chats with Allan Isfan, Senior Director of Global Video Platform at Warner Bros Discovery, about how AI is reshaping creativity, software development, and large-scale enterprise culture. Allan explains how he drives AI literacy for 1,500+ employees, the power of internal demos and sandboxes, and gives a hands-on walkthrough of generative video tools like Gemini V3, Flow, and Sora. He also dives into AI video analysis, the Wizard of Oz project at The Sphere, and the future of creative storytelling powered by AI.
Wie setzt du KI heute so ein, dass dein Immobilien-Alltag messbar leichter wird? In dieser Folge zeigen Martin, Torben und immo.memo (Mehmet), wie du aus Prompts produktive Workflows baust – von der Unterlagenprüfung (Grundbuch, Teilungserklärung, Energieausweis) über Marktanalysen bis hin zur Finanzierungs-Präsentation für Banken. Du erfährst, wie du dein Immobiliennetzwerk mit KI schneller aktivierst, Akquisestrukturierst und in Minuten prüfbare Ergebnisse lieferst. Weniger Fehler, mehr Fokus, mehr Deals. Darum geht's konkret· Warum Künstliche Intelligenz (KI) heute der größte Hebelin der Immobilienbranche ist – für Bestandshalter, Fix & Flip, Hausverwaltung und Ankauf.· Modelle im Vergleich: Stärken/Schwächen bei PDF-Erkennung& Reasoning; warum saubere Dokumenten-Analysen im Immobilienprozess entscheidend sind.· Prompting ohne Frust: Vom einfachen Prompt zum robusten System-Prompt – so wird aus „Antwort-Text“ einwiederverwendbarer Workflow.· Marktanalyse mit KI: öffentlich verfügbare Daten bündeln,Nachfrage/Angebot bewerten, Standortrisiken erkennen – und das format- &teamfähig.· Unterlagenprüfung inMinuten: Risikenerkennen (z. B. Effizienzklasse, Heizung), Sanierungsfahrplan samt förderfähigen Gewerkenvorbereiten, Rückfragen an Makler automatisch generieren.· Bank-Pitch aus KI-Daten: Von der Analyse zum Finanzierungs-Deck (inkl. Bauablauf, Rentabilität,Exit-Szenarien) – professionell auftreten, Vertrauen schaffen.· Immobiliennetzwerk mitKI aktivieren:Kontakte priorisieren (Makler, Verwalter, Handwerker, Steuerberater,Finanzierer), Outreach strukturieren, Follow-ups automatisieren.· Automatisierung: Warum kleine, spezialisierte Agenten/Workflows (statt „ein Mega-Bot für alles“) inder Praxis die besten Ergebnisse liefern. Partner dieser FolgeOhne-Makler.net – Immobilien ganz ohne Makler verkaufen oder vermieten.Mit dem Code DERIC25 erhältst du 25 € Startguthaben: ohne-makler.net/gutschein Du feierst den Podcast?Dann hinterlass uns eine Bewertung auf der Plattform deiner Wahl. Danke! Dein Feedback hilft uns, besser zu werden und Themen reinzuholen, die dich wirklich weiterbringen. Alle Links & Infos zur Folge und zur DERIC Mitgliedschaft https://links.insights.immo Echte Deals, echte Menschen, echter Mehrwert - den gibt's in unserer Immobiliencommunity deric.insights.immo Unser Gast: Mehmet: Instagram Deine HostsTorben – wonderl.ink/@torbenschulthoffMartin – linktr.ee/martincronacher
Prompting is out, context is in. Host Daniel Serfaty and Prof. Joseph Fuller of the Harvard Business School explore why “context engineering”—combining domain knowledge and judgment—is the next essential skill for human-AI teaming. They also discuss how organizational design, retention, and learning must evolve as technology advances faster than traditional upskilling can keep pace.
AI chat bots have streamlined the information gathering process, but as with any model, their output is only as good as their input, so when it comes to personal finance questions, the wrong prompts can lead to costly mistakes. Donna walks us through the process of prompt engineering AI chat bots to assist with financial decision making, and what types of questions should be left to a professional. Also on MoneyTalk, managing retiree healthcare costs. Host: Donna Sowa Allard, CFP®, AIF®; Air Date: 10/27/2025. Have a question for the hosts? Leave a message on the MoneyTalk Hotline at (401) 587-SOWA and have your voice heard live on the air!See omnystudio.com/listener for privacy information.
In this episode, Joseph sits down with Donovan Rittenbach — a serial entrepreneur, copywriting virtuoso, and AI marketing specialist — to explore the intersection of storytelling, technology, and transformation. As the founder of My AI Web Guy, Donovan has helped countless small businesses scale through his proprietary copywriting frameworks fused with cutting-edge AI strategies. He's also the author of Prompt Virtuoso, a new book that redefines how creators and marketers harness the power of prompts to shape digital narratives.Together, Joseph and Donovan dive into:
On this episode of FDE+, Kortney Harmon and Mike Wolford, CEO of LexDuo, explore how AI is redefining what it means to be a recruiter—and why the future belongs to those who build with it, not just use it.They discuss how recruiters are moving beyond basic prompting into programming and workflow design—creating custom GPTs, connecting APIs, and automating tasks that once drained hours from their day. Mike also explains how imagination has become a recruiter's new competitive advantage and outlines the ethical and legal considerations that come with building AI-driven systems.Key Takeaways • The three levels of AI adoption and how each elevates recruiter performance • Why creativity, not coding, defines success in the AI-driven era • How API connections can integrate your ATS, CRM, and communication tools • The coming divide between corporate TA and staffing—and where opportunity grows • How to “automate and elevate” recruiting by combining AI precision with human judgmentDiscover how forward-thinking recruiters are using AI to amplify—not replace—the human side of hiring.___________Follow Mike Wolford on LinkedIn: LinkedIn | Mike Check out his website: lexduo.net Follow Crelate on LinkedIn: Crelate Want to learn more about Crelate? Book a demo here Subscribe to our newsletter: The Full Desk Experience
People are increasingly asking AI, not Google, to help them discover products. A recent shopping report says Americans, this holiday season, will likely turn to large language models this season to find gifts, deals, and sales instead of traditional search. Also, Snabbit has raised its third funding round in nine months. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Europe's military buildup, presidential use of the National Guard, and a “gospel-first” approach to sidewalk counseling. Plus, Janie B. Cheaney on the cost of scoffing, bringing site to the blind, and the Tuesday morning newsSupport The World and Everything in It today at wng.org/donateAdditional support comes from Cedarville University—a Christ-centered, academically rigorous university located in southwest Ohio, equipping students for Gospel impact across every career and calling. Cedarville integrates a biblical worldview into every course in the more than 175 undergraduate and graduate programs students choose from. New online undergraduate degrees through Cedarville Online offer flexible and affordable education grounded in a strong Christian community that fosters both faith and learning. Learn more at cedarville.edu, and explore online programs at cedarville.edu/onlineFrom The Issues, et cetera podcast. Expert guests, Expansive topics, Extolling Christ. More at issuesetc.orgAnd from Asbury University — where students are known, supported, and prepared to lead. Customized visits available. asbury.edu/visit
Mark Murphy, Senior Policy Manager with the Irish Heart Foundation; Dr Garrett McGovern, Medical Director and Addiction Specialist at the Priority Medical Clinic.
Tucker's remarks at a Turning Point event highlight the divisions within the Republican party over foreign policy. Plus: more evidence of Israel's crimes against Palestinians are revealed during the fragile ceasefire. Finally: Tommy Robinson goes to Israel, where he is exposed to even more pro-Israel propaganda. --------------------------- Watch full episodes on Rumble, streamed LIVE 7pm ET. Become part of our Locals community Follow System Update: Twitter Instagram TikTok Facebook
Gaza Ceasefire Interrupted by Violence; Hamas Reasserts Dominance. David Daoud and Bill Roggio discuss how the Gaza ceasefire was violated when Hamas killed Israeli soldiers, prompting Israeli retaliation to reinforce red lines without restarting the conflict entirely. Hamas is deliberately slowing the return of dead hostages to stabilize the ceasefire internationally. In Gaza, Hamas immediately began cracking down on rivals to reassert its dominance and prevent others from filling the power vacuum left by IDF withdrawals, signaling it remains the top power. 1902 CARACAS
Gaza Ceasefire Interrupted by Violence; Hamas Reasserts Dominance. David Daoud and Bill Roggio discuss how the Gaza ceasefire was violated when Hamas killed Israeli soldiers, prompting Israeli retaliation to reinforce red lines without restarting the conflict entirely. Hamas is deliberately slowing the return of dead hostages to stabilize the ceasefire internationally. In Gaza, Hamas immediately began cracking down on rivals to reassert its dominance and prevent others from filling the power vacuum left by IDF withdrawals, signaling it remains the top power. 1930 CARACAS
Pastor Jesus Arriaga urges us to live intentionally under God's will, saying yes to His promptings today rather than postponing obedience. He highlights simple, immediate acts like encouragement, praying with someone now, and meeting practical needs.
The AI Breakdown: Daily Artificial Intelligence News and Discussions
AI is trained on the sum total of human output—which means it often produces the average of averages. That's fine for passable results, but not for unique, high-quality work. In this weekend big think episode, NLW explores what he calls AI's tyranny of the average and shares five techniques to break through it: using negative style guides, forcing divergence and choice, burning down clichés, prompting self-critique, and leveraging examples that defy consensus. Based on an essay by Alex Kantrowitz, this is a practical guide for anyone who wants their AI outputs to stand out rather than blend in.AI Sameness Essay: https://www.bigtechnology.com/p/ais-sameness-problemBrought to you by:Is your enterprise ready for the future of agentic AI?Visit AGNTCY.orgVisit Outshift Internet of AgentsGoogle Gemini - Try NotebookLM today https://notebooklm.google.com/KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. https://www.kpmg.us/AIpodcastsBlitzy.com - Go to https://blitzy.com/ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? nlw@aidailybrief.ai
10-17-25 - Holmberg Keeps Trying Coffee But Still Doesn't Like It Prompting His Shared Food Rant Again - Reactions/Emails To Cory's Angry No Kings March Email About John's Money - Dirty Dining's Jason Barry Took Aim Again At Pacino's As John Finds Out About Live Clams vs Dead OnesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
10-17-25 - Holmberg Keeps Trying Coffee But Still Doesn't Like It Prompting His Shared Food Rant Again - Reactions/Emails To Cory's Angry No Kings March Email About John's Money - Dirty Dining's Jason Barry Took Aim Again At Pacino's As John Finds Out About Live Clams vs Dead OnesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Prompting feels like one of the #1 skills marketers are mastering in 2025. In this episode, Anna Carina Berkman, founder of Markitect, reveals how to turn simple text into powerful marketing results using AI tools like ChatGPT, Gemini, and more.Whether you're struggling to get quality AI output or you're just starting out, this deep dive covers the principles, examples, and frameworks that drive real marketing outcomes with AI.00:00 - Intro: Why Prompting Matters in 202501:22 - Meet Anna Carina Berkman, Founder at Markitect03:10 - What Is Prompting, Really?04:40 - Why Prompting Is the New Copywriting06:25 - The Coco Framework Explained (Clear, Outcome, Context, Options)09:15 - Examples of High-Converting AI Prompts12:50 - Lazy Prompting: Automating Great Results14:30 - Prompting Across Tools (ChatGPT, Claude, Gemini)16:05 - Common Prompting Mistakes to Avoid17:45 - Building a Prompt Library for Your Team19:00 - Final Advice************Please take the time to check out our partners, all of whom we work with because we think they're useful companies for lovely marketers.Frontify - all your brand assets in one place: Frontify combines DAM, brand guidelines, and templates into a collaborative source of brand truth.Cambridge Marketing College - the best place to get your marketing qualifications and apprenticeships.Planable - the content collaboration platform that helps marketing teams create, plan, review, and approve all their awesome marketing content.NOAN - your superhuman business partner. Easily build your strategy & control your business knowledge with AI, then use it to manage your tasks, create content & supercharge your marketing.Wistia - a complete video marketing platform that helps teams create, host, market, and measure their videos and webinars—all in one place.
Matt Bowers — SEO and LLM consultant, formerly of Zapier and Zillow — joins Ross Hudgens for a deep dive into how AI is transforming programmatic SEO. They explore what's working and what's not for large-scale, AI-assisted content strategies — from full-AI “use-case” pages to hybrid human workflows. Matt breaks down examples of successful AI programmatic sites, the pitfalls of duplicate content, and the emerging “information gain” paradigm shaping rankings post-2024. They also discuss the limits of AI in UX-driven verticals, personalization opportunities, long-tail visibility in LLMs like ChatGPT, and how data-driven scaling can still give human SEOs a competitive edge. Plus: the rise and fall of Greg.app, the future of personalization, Zillow's “Project Boggle,” and practical tools like Builder.io, Strapi, and AirOps that power modern programmatic builds. Show Notes 0:08 – Matt returns for round two: programmatic SEO meets AI 1:00 – Are “pure AI” sites actually winning? What's working and what's not 2:06 – Inside a million-visit-per-month AI programmatic play 3:15 – Structuring AI content around real use cases, not blog posts 4:22 – Why old GPT-3.5 copy can still rank — and the “don't mess with success” mantra 5:03 – Dwell time as a differentiator: the “product as content” advantage 6:13 – How AI copy helps with indexing and duplicate-content differentiation 7:17 – Why Google probably isn't detecting AI directly and what it does instead 8:11 – The “high-DR arbitrage” era of AI content — and why it's fading 10:11 – Why most public AI case studies stay anonymous 11:16 – Case study: Greg.app — AI-generated plant care pages done right 12:03 – How prompt engineering + UX elevate AI content 13:13 – Prompting each paragraph individually vs. one giant prompt 15:21 – Two winning models: product-driven and UX-driven AI programmatic 16:15 – Why blog-style AI content still struggles and the “pizza” metaphor 20:05 – Greg.app's traffic drop: lessons from a 75% decline 22:21 – AI's scalability advantage — and its ROI trade-offs 25:24 – Zillow's data advantage: proprietary enrichment and GIS precision 26:16 – When AI enables pages that “shouldn't exist” by human economics 27:21 – Scaling what can't be scaled: the real AI unlock 28:16 – Competing in local long-tail SERPs with AI vs. humans 28:31 – Traits of losing players: low information gain, weak differentiation 29:20 – Why “information gain” may be the new ranking factor 30:06 – Proprietary data as the ultimate SEO differentiator 31:00 – How real estate UX converged — and why speed and personalization win 33:00 – When non-AI programmatic still wins: data-only, high-usability pages 35:07 – Where AI doesn't belong: when usability is more important than copy 35:37 – Personalization and the future of AI-driven recommendations 37:07 – The Perplexity vision: a world run by AI agents and voice search 39:06 – What AI agents mean for SEO and monetization 40:38 – Long-tail demand from LLMs and how Zapier used programmatic pages 42:29 – How LLMs discover your use cases and why it matters 43:20 – Using internal data to fuel new programmatic ideas Project Boggle 46:09 – Generating new landing pages from user search inputs 47:52 – Internal search data as a goldmine for programmatic expansion 48:30 – Tools of the trade: AirOps, Builder.io, Strapi, and hybrid stacks 49:43 – Why programmatic SEO still needs human PMs and engineers 50:08 – Where to find Matt online Show Links Matt Bowers on LinkedIn: https://www.linkedin.com/in/mpbow/ Matt's Website: https://mattb.rs/ Greg.app AI plant care example: https://greg.app/plant-care/monstera Strapi CMS: https://strapi.io/ AirOps: https://www.airops.com/ Builder.io: https://www.builder.io/ Subscribe today for weekly tips: https://bit.ly/3dBM61f Listen on iTunes: https://podcasts.apple.com/us/podcast/content-and-conversation-seo-tips-from-siege-media/id1289467174 Listen on Spotify: https://open.spotify.com/show/1kiaFGXO5UcT2qXVRuXjsM Listen on Google: https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5zaW1wbGVjYXN0LmNvbS9jT3NjUkdLeA Follow Siege on Twitter: http://twitter.com/siegemedia Follow Ross on Twitter: http://twitter.com/rosshudgens Directed by Cara Brown: https://twitter.com/cararbrown Email Ross: ross@siegemedia.com #seo | #contentmarketing
AP correspondent Haya Panjwani reports on protests in Peru.
The Democrat Party in deep blue areas keep reaching new depths of despair. What will the response be? Jesse Kelly breaks it all down. Best of I'm Right with Jesse Kelly on The First TV Vandy Crisps: Get 25% off your first order | Use code JESSE at https://vandycrisps.com/JESSE Cowboy Colostrum: Get 25% Off Cowboy Colostrum with code JESSETV at https://www.cowboycolostrum.com/JESSETV Pure Talk: Go to https://www.puretalk.com/JESSETV and save 50% off your first month.Follow The Jesse Kelly Show on YouTube: https://www.youtube.com/@TheJesseKellyShowSee omnystudio.com/listener for privacy information.
The AI Breakdown: Daily Artificial Intelligence News and Discussions
NLW breaks down five ways businesses are already using OpenAI's Sora 2 model — from product design and e-commerce video automation to creative marketing campaigns and new content platform opportunities. He also shares a practical guide to prompting for the best Sora results, explaining how to balance creativity with control and why “style and structure” matter most for high-quality output. Plus, in the headlines: Nvidia says 100% of its engineers now use AI coding tools like Cursor, Google launches Gemini 2.5 for computer use, Anthropic partners with IBM and Deloitte, and xAI releases a major upgrade to its Imagine video model.Brought to you by:Is your enterprise ready for the future of agentic AI?Visit AGNTCY.orgVisit Outshift Internet of AgentsTry Notion AI today with Notion 3.0 https://ntn.so/nlwKPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. https://www.kpmg.us/AIpodcastsBlitzy.com - Go to https://blitzy.com/ to build enterprise software in days, not months Insightwise - AI for the entire consulting lifecycle https://www.insightwise.ai/Robots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/Vanta - Simplify compliance - https://vanta.com/nlwThe Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? nlw@aidailybrief.ai
In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss scaling Generative AI past basic prompting and achieving real business value. You will learn the strategic framework necessary to move beyond simple, one-off interactions with large language models. You will discover why focusing on your data quality, or “ingredients,” is more critical than finding the ultimate prompt formula. You will understand how connecting AI to your core business systems using agent technology will unlock massive time savings and efficiencies. You will gain insight into defining clear, measurable goals for AI projects using effective user stories and the 5P methodology. Stop treating AI like a chatbot intern and start building automated value—watch now to find out how! Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-getting-real-value-from-generative-ai.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn – 00:00 In this week’s *In-Ear Insights*. Another week, another gazillion posts on LinkedIn and various social networks about the ultimate ChatGPT prompt. OpenAI, of course, published its Prompt Blocks library of hundreds of mediocre prompts that are particularly unhelpful. And what we’re seeing in the AI industry is this: A lot of people are stuck and focused on how do I prompt ChatGPT to do this, that, or the other thing, when in reality that’s not where the value is. Today, let’s talk about where the value of generative AI actually is, because a lot of people still seem very stuck on the 101 basics. And there’s nothing wrong with that—that is totally great—but what comes after it? Christopher S. Penn – 00:47 So, Katie, from your perspective as someone who is not the propeller head in this company and is very representative of the business user who wants real results from this stuff and not just shiny objects, what do you see in the Generative AI space right now? And more important, what do you see it’s missing? Katie Robbert – 01:14 I see it’s missing any kind of strategy, to be quite honest. The way that people are using generative AI—and this is a broad stroke, it’s a generalization—is still very one-off. Let me go to ChatGPT to summarize these meeting notes. Let me go to Gemini to outline a blog post. There is nothing wrong with that, but it’s not a strategy; it’s one more tool in your stack. And so the big thing that I see missing is, what are we doing with this long term? Katie Robbert – 01:53 Where does it fit into the overall workflow and how is it actually becoming part of the team? How is it becoming integrated into the organization? So, people who are saying, “Well, we’re sitting down for our 2026 planning, we need to figure out where AI fits in,” I think you’re already setting yourself up for failure because you’re leading with AI needs to fit in somewhere versus you need to lead with what do we need to do in 2026, period? Chris has brought up the 5P Framework, which is 100% where I’m going to recommend you start. Start with the purpose. So, what are your goals? What are the questions you’re trying to answer? How are you trying to grow and scale? And what are the KPIs that you want to be thinking about in 2026? Katie Robbert – 02:46 Notice I didn’t say with AI. Leave AI out of it for now. For now, we’ll get to it. So what are the things that you’re trying to do? What is the purpose of having a business in 2026? What are the things you’re trying to achieve? Then you move on to people. Well, who’s involved? It’s the team, it’s the executives, it’s the customers. Don’t forget about the customers because they’re kind of the reason you have a business in the first place. And figure out what all of those individuals bring to the table. How are they going to help you with your purpose and then the process? How are we going to do these things? So, in order to scale the business by 10x, we need to bring in 20x revenue. Katie Robbert – 03:33 In order to bring in 20x revenue, we need to bring in 30x visits to the website. And you start to go down that road. That’s sort of your process. And guess what? We haven’t even talked about AI yet, because it doesn’t matter at the moment. You need to get those pieces figured out first. If we need to bring in 30x the visits to the website that we were getting in the previous year, how do we do that? What are we doing today? What do we need to do tomorrow? Okay, we need to create content, we need to disseminate it, we need to measure it, we need to do this. Oh, maybe now we can think about platforms. That’s where you can start to figure out where in this does AI fit? Katie Robbert – 04:12 And I think that’s the piece that’s missing: people are jumping to AI first and not why the heck are we doing this. So that is my long-winded rant. Chris, I would love to hear your perspective. Christopher S. Penn – 04:23 Perspective specific to AI. Where people are getting tripped up is in a couple different areas. The biggest at the basic level is a misunderstanding of prompting. And we’re going to be talking about this. You’ll hear a lot about this fall as we are on the conference circuit. Prompting is like a recipe. So you have a recipe for baking beef Wellington, what have you. The recipe is not the most important part of the process. It’s important. Winging it, particularly for complex dishes, is not a good idea unless you’ve done it a million times before. The most important part is things like the ingredients. You can have the best recipe in the world; if you have no ingredients, you ain’t eating. That’s pretty obvious. Christopher S. Penn – 05:15 And yet so many people are so focused on, “Oh, I’ve got to have the perfect prompt”—no, you don’t. You need to have good ingredients to get value. So, let’s say you’re doing 2026 strategic planning and you go to the AI to say, “I need to work on my strategic plan for 2026.” They will understand generally what that means because most models are reasoning models now. But if you provide no data about who you are, what you do, how you’ve done it, your results before, who your competitors are, who your customers are, all the 10 things that you need to do strategic planning like your budget, who’s involved, the Five Ps—basically AI won’t be able to help you any better than you will or that your team will. It’s a waste of time. Christopher S. Penn – 06:00 For immediate value unlocks for AI, it starts with the right ingredients, with the right recipe, and your skills. So that should sound an awful lot like people, process, and platform. I call it Generative AI 102. If 101 is, “How do I prompt?” 102 is, “What ingredients need to go with my prompt to get value out of them?” But then 201 is—and this is exactly what you started off with, Katie—one-off interactions with ChatGPT don’t scale. They don’t deliver value because you, the human, are still typing away like a little monkey at the keyboard. If you want value from AI, part of its value comes from saving time, saving money, and making money. Saving time means scale—doing things at scale—which means you need to connect your AI to other systems. Christopher S. Penn – 06:59 You need to plug it into your email, into your CRM, into your DSP. Name the technology platform of your choice. If you are still just copy-pasting in and out of ChatGPT, you’re not going to get the value you want because you are the bottleneck. Katie Robbert – 07:16 I think that this extends to the conversations around agentic AI. Again, are you thinking about it as a one-off or are you thinking about it as a true integration into your workflow? Okay, so I don’t want to have to summarize meeting notes anymore. So let me spend a week building an agent that’s going to do that for me. Okay, great. So now you have an agent that summarizes your meeting notes and doesn’t do anything else. So now you have to, okay, what else do I want it to do? And you start frankensteining together all of these one-off tasks until you have 100 agents to do 100 things versus maybe one really solid workflow that could have done a lot of things and have less failure points. Katie Robbert – 08:00 That’s really what we’re talking about. When you’re short-sighted in thinking about where generative AI fits in, you introduce even more failure points in your business—your operations, your process, your marketing, whatever it is. Because you’re just saying, “Okay, I’m going to use ChatGPT for this, and I’m going to use Gemini for this, and I’m going to use Claude for this, and I’m use Google Colab for this.” Then it’s just kind of all over the place. Really, what you want to have is a more thoughtful, holistic, documented plan for where all these pieces fit in. Don’t put AI first. Think about your goals first. And if the goal is, “We want to use AI,” it’s the wrong goal. Start over. Christopher S. Penn – 08:56 Unless that’s literally your job. Katie Robbert – 09:00 But that would theoretically tie to a larger business goal. Christopher S. Penn – 09:05 It should. Katie Robbert – 09:07 So what is the larger business goal that you’ve then determined? This is where AI fits in. Then you can introduce AI. A great way to figure that out is a user story. A user story is a simple three-part sentence: As a [Persona], I want [X], so that [Y]. So, as the lead AI engineer, I want to build an AI agent. And you don’t stop there. You say, “So that we can increase our revenue by 30x,” or, “Find more efficiencies and cut down the amount of time that it takes to create content.” Too many people, when we are talking about where people are getting generative AI wrong, stop at the “want to” and they put the period there. They forget about the “so that.” Katie Robbert – 09:58 And the “so that” arguably is the most important part of the user story because it gives you a purpose, it gives you a performance metric. So the Persona is the people, the “want to” is the process and the platform. The “so that” is the purpose and the performance. Christopher S. Penn – 10:18 When you do that, when you start thinking about the purpose, it will hint at the platforms that have to be involved. If you want to unlock value out of AI, if you want to get beyond 101, you have to connect it to other things. A real simple example: Say you’re in sales. Where does all the data that you’d want AI to use live? It doesn’t live in ChatGPT; it lives in your CRM. So the first and most important thing that you would have to figure out is, “As a salesperson, I want to increase my closing rate by 10% so that I get 10% more money.” That’s a pretty solid user story. Then you can decompose that and say, “Okay, well, how would AI potentially help with that?” Well, it could identify maybe next best actions on my… Christopher S. Penn – 11:12 …on the deals that are in my pipeline. Maybe I’ve forgotten something. Maybe something fell through the cracks. How do I do that? So you would then revise the user story: “As a salesperson who wants to make more money, I want to identify the next best actions for the deals in my pipeline programmatically so that I don’t let something fall through the cracks that could make me a bunch of money.” Then you drill down further and you say, “Okay, well, how could AI help me with that?” Well, if you have your Sales Playbook, you have your CRM data, and you have a good agentic framework, you could say, “Agent, go get me one of my deals at a time from my CRM, take my Sales Playbook, interrogate it and say, ‘Hey, Sales Playbook, here’s my deal. What should my next best action be?'” Christopher S. Penn – 11:59 If you’ve done a good job with your Sales Playbook and you’ve got battle cards and all that stuff in there, the AI will pretty easily figure out, “Oh, this deal is in this state. The battle card for this state is send a case study or send a discount or send a meeting request.” Then the AI has to go back to its agent and say, “CRM, record a task for me. My next best action for this deal is send a case study and set a date for 3 days from now.” Now, you’ve taken the user story, drilled down. You found a place where AI fits in and can do that work so that you don’t have to. Because a human could do that work. And a human should know what’s in your Sales Playbook. Christopher S. Penn – 12:48 But let’s be honest, if you do a really good job with the Sales Playbook, it might be 300 pages long. But in the system now, you’re connecting AI to and from where all the knowledge lives and saying, “This is the concrete, tangible outcome I want: I want to know what the next best action is for every deal in my pipeline so that I can make more money.” Katie Robbert – 13:10 I would argue that even if your sales book is 200 pages long, you should still kind of know how you’re selling things. Christopher S. Penn – 13:19 Should. Katie Robbert – 13:21 But that’s the thing: to get more value out of generative AI, you have to know the thing first. So, yeah, generative AI can give you suggestions and help you brainstorm. But really, it comes down to what you know. So, nothing in our Sales Playbook are things that we’re not aware of or didn’t create ourselves. Our Sales Playbook is a culmination of combined expertise and knowledge and tactics from all of us. If I read through—and I have read through—but if I read through the entire Sales Playbook, nothing should jump out at me as, “Huh, that’s new.” Katie Robbert – 13:58 I wasn’t aware of that. I think the other side of the coin is, yes, we’re doing these one-off things with generative AI, but we’re also just accepting the output as is. We’re, “Okay, so that must be it.” When we’re thinking about getting more value, the value, Chris, to your point, is if you’re not giving the system all of the ingredients, you’re going to end up with a beef Wellington that’s made with chickpeas and glue and maybe a piece of cheesecloth. I’m waiting for you to try to wrap your head around that. Christopher S. Penn – 14:45 Yeah, no, that sounds horrible. Katie Robbert – 14:48 Exactly. That’s exactly the point: the value you get out of generative AI. It goes back to the data quality conversation we were having on last week’s podcast when we were talking about the LinkedIn paper. It’s not enough just to accept the output and clean it from there. If you spent the time to make a beef Wellington and the meat is overdone, or the pastry is not flaky, or the filling is too salty, and you’re trying to correct those things after the fact, you’re already too late. You can maybe kind of mask it a little bit, maybe add a couple of things to counterbalance whatever it is that went wrong. But it really starts at the beginning of what you’re putting into it. Katie Robbert – 15:39 So maybe don’t be so heavy-handed with the salt, maybe don’t overwork the dough so that it is actually more flaky and more like a pastry dough than a pizza dough. Christopher S. Penn – 15:52 I’m really hungry now. In 2026, I do think one of the things that marketers are going to get their hands around—and everybody using generative AI—is how agents play a role in what you do because they are the connectors to other systems. And if you’re not familiar with how agentic AI works, it’s going to be a handicap. In the same way that if you’re not familiar with how ChatGPT itself works, it’s going to be a handicap, and you still have to master the basics. We’ve always talked about the three levels: done by you, which is prompting; done with you, which is mini automations like Gems and GPTs; and then done for you as agents. I think people have kind of at least figured out done by you, give or take. Christopher S. Penn – 16:41 Yes, there’s still a lot of crappy prompts out there, but for the most part people don’t need to be told what a prompt is anymore. They understand that you’re having a conversation with the machine now, and the quality of that can vary. People are starting to wrap their heads around the GPT kind of thing: “Let me make a mini app for this.” And there’s a bunch of things that I see wrong there: “I’m just going to make this my primary workhorse.” No, it doesn’t have the context, doesn’t have the ingredients to do that. But getting to that level of the agent is where I think at least the forward-looking companies need to get to, to get that value sooner rather than later. Christopher S. Penn – 17:20 This past year in 2025, we have built probably two dozen agentic systems, which is nothing more than an AI wrapped around a whole bunch of code connecting to data sources. We’ve used it to build ICPs, to evaluate landing pages, to do sentiment analysis—all these different projects because some of them are really crazy. But the key for the value was connecting to those systems. Christopher S. Penn – 17:49 That’s the really difficult part because—and we have a whole thing about this if you want to chat about it—we have a data quality audit. The moment you start connecting to your systems, you now need to know that the data going in and out of those systems is good. If the ingredients are bad, to your point, it doesn’t matter how good a cook you are, it doesn’t matter what appliances you own, doesn’t matter how good the recipe is. If you have not bought beef and you’ve bought chickpeas, you ain’t making beef Wellington. Katie Robbert – 18:27 Side note: I have made a vegetarian beef Wellington with chickpeas, and it actually came out pretty good. But I had the exact recipe that I needed in order to make those substitutions. And I went into the process knowing that my output wasn’t actually going to be a beef Wellington; it was going to be a chickpea Wellington. I think that’s also part of it—the expectation setting. AI can do a lot with crappy ingredients, but not if you don’t tell it what it’s supposed to be doing. So if you say, “I’m making a beef Wellington, here’s chickpeas,” it’s going to be, “I guess I can do that.” Katie Robbert – 19:13 But if you’re saying, “I’m making a chickpea loaf covered in puff pastry and a mushroom filling,” it’s, “Oh, I can totally do that,” because there was no mention of beef, and now I don’t have the context that I’m supposed to be doing anything with beef. So it’s the ingredients, but it’s also the critical thinking of what is it that you’re trying to do in the first place. Katie Robbert – 19:34 That goes back to this is where people aren’t getting the right value out of generative AI because they’re just doing these one-off things and they’re not giving it the context that it needs to actually do something. And then it’s not integrated into the business as a whole. It’s just, Chris is over there using generative AI to make songs. But that has nothing to do with what Trust Insights does on a day-to-day basis. So that’s never going to make us any money. He’s spending the time and the resources. This is all fictional. He doesn’t actually spend company time doing this. Christopher S. Penn – 20:09 I spent a lot of time personally. Katie Robbert – 20:10 Doing this, and that’s fine. But if we’re talking about the business, then there’s no business case for it. You haven’t gone through the Five Ps. Katie Robbert – 20:20 To say this is where this particular thing fits into the business overall. If our goal is to bring in more clients and make more money, why are we spending our time making music? Christopher S. Penn – 20:32 Exactly. As we have this conversation, it occurs to me that in 2026 we are probably going to need to put together an agentic AI course because the roadmap to get there is very difficult if you don’t know what you’re doing. You will potentially do things like, oh, I don’t know, accidentally give AI access to your production database and then it deletes it because it thinks it didn’t need it. Which happened to someone on the Replit repository not too long ago. Katie Robbert – 21:04 Whoops. Christopher S. Penn – 21:08 This is why we do git commits and rollbacks and we use sandbox AI. If you are in a position where you are saying, “I’ve got the 101 down and now I’m stuck. I don’t know where to go next,” the three things that you should be looking at: Number one is the Five Ps to figure out what you should be doing, period. Number two is a data quality audit to make sure that the data you’re feeding into AI is going to be any good. Number three is taking the agentic systems that are out there to connect them to your good quality data for the right purpose, with the right performance, so that you can scale the use of AI beyond being your ChatGPT’s intern. That’s what you are. Katie Robbert – 21:58 Chris, I don’t know if you know this, but we have a course that actually walks you through a lot of those things. You can go to Trust Insights AI strategy course. To be clear, this specific course doesn’t teach you how to use AI. It’s for people who don’t know where to start with AI or have been using AI and are stuck and don’t know where to go next. So, for example, if you’re doing your 2026 planning and you’re, “I think we need to introduce agentic AI.” Christopher S. Penn – 22:33 Cool. Katie Robbert – 22:34 I would highly recommend using the tools that you learn in this course to figure out, “Do I need to do that? Where does it fit? Who needs to do it? How are we going to maintain it? What is the goal of putting agentic AI in other than just putting it on our website and saying, ‘We do it’?” That would be my recommendation: take our AI strategy course to figure out what to do next. Chris, where we started with this conversation was, how do people get more value out of AI? So, Chris, congratulations. Chris is an AI ready strategist. Katie Robbert – 23:14 We’re very proud of him. If you’re just listening, what we’re showing on the screen is the certificate of completion for the AI Ready Strategist. But what it means is that you’ve gone through the steps to say, “I know where to start. If I’m stuck, I know how to get unstuck.” Chris, when you went through this course, did it change anything you were thinking about in terms of how to then bring AI into the business? Christopher S. Penn – 23:42 Yes. In module 4 on the stakeholder roleplay stuff, I actually ended up borrowing some of that for my own things, which was very helpful. Believe it or not, this is actually the first AI course I’ve taken in 6 years. Katie Robbert – 23:58 I’m going to take that as a very high compliment. Christopher S. Penn – 24:01 Exactly. Katie Robbert – 24:04 What Chris is referring to: part of the challenge of getting the value out of AI is convincing other people that there is value in it. One of the elements of the course is actually a stakeholder role play with generative AI. Basically, you can say, “This is what I want to do.” And it will simulate talking to your stakeholder. If your stakeholder is saying, “Okay, I need to know this, this, and this.” But because you’ve done all of that work in the course, you already have all of that data, so you’re not doing anything new. You’re saying, “Oh, here’s that information. Here, let me serve it up to you.” Katie Robbert – 24:41 So it’s an easy yes. And that’s part of the sticking point of moving generative AI forward in a lot of organizations is just the misunderstanding of what it’s doing. Christopher S. Penn – 24:52 Exactly. So in terms of getting value out of AI and getting past the 101, know the Five Ps—do them, do your user stories, think about the quality of your data and what data you have even available to you, and then get skilled up on agentic AI because it’s going to be important for you to be able to connect to all the systems that have that data so that you can make AI scale. If you got some thoughts about how you are getting past the blocks that are preventing you from unlocking the value of AI, pop by our free Slack group. Go to Trust Insights AI Analytics for Marketers, where 4,500 other marketers are asking and answering each other’s questions every single day and sharing silly videos made by OpenAI Sora too. Christopher S. Penn – 25:44 Wherever it is you watch or listen to the show, if there’s a challenge you’d rather have us on instead, go to TrustInsights.ai/TIpodcast. You can find us in all the places that fine podcasts are served. Thanks for tuning in. We’ll talk to you on the next one. Speaker 3 – 26:02 Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep-dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology and MarTech selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, Dall-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or data scientists to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the *In-Ear Insights* Podcast, the *Inbox Insights* newsletter, the *So What* Livestream webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models. Yet, they excel at exploring and explaining complex concepts clearly through compelling narratives and visualizations—Data Storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data-driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.
At OpenAI DevDay, we sit down with Sherwin Wu and Christina Cai from the OpenAI Platform Team to discuss the launch of AgentKit - a comprehensive suite of tools for building, deploying, and optimizing AI agents. Christina walks us through the live demo she performed on stage, building a customer support agent in just 8 minutes using the visual Agent Builder, while Sherwin shares insights on how OpenAI is inverting the traditional website-chatbot paradigm by embedding apps directly within ChatGPT through the new Apps SDK. The conversation explores how OpenAI is tackling the challenges developers face when taking agents to production - from writing and optimizing prompts to building evaluation pipelines. They discuss the decision to adopt Anthropic's MCP protocol for tool connectivity, the importance of visual workflows for complex agent systems, and how features like human-in-the-loop approvals and automated prompt optimization are making agent development more accessible to a broader range of developers. Sherwin and Christina also reveal how OpenAI is dogfooding these tools internally, with their own customer support at openai.com already powered by AgentKit, and share candid insights about the evolution from plugins to GPTs to this new agent platform. They discuss the surprising persistence of prompting as a critical skill (contrary to predictions from two years ago), the challenges of serving custom fine-tuned models at scale, and why they believe visual agent builders are essential as workflows grow to span dozens of nodes. Guests: Sherwin Wu: Head of Engineering, OpenAI Platform https://www.linkedin.com/in/sherwinwu1/ https://x.com/sherwinwu?lang=en Christina Huang: Platform Experience, OpenAI https://x.com/christinaahuang https://www.linkedin.com/in/christinaahuang/ Thanks very much to Lindsay and Shaokyi for helping us set up this great deepdive into the new DevDay launches! Key Topics: • AgentKit launch: Agent SDK, Builder, Evals, and deployment tools • Apps SDK and the inversion of the app-chatbot paradigm • Adopting MCP protocol for universal tool connectivity • Visual agent building vs code-first approaches • Human-in-the-loop workflows and approval systems • Automated prompt optimization and "zero-gradient fine-tuning" • Service Health Dashboard and achieving five nines reliability • ChatKit as an embeddable, evergreen chat interface • The evolution from plugins to GPTs to agent platforms • Internal dogfooding with Codex and agent-powered support
10-06-25 - Flying Taxis Coming Within 2 Years And Testing In NY Now - Woman Smears Cybertruck w/Dog Poop Prompting Our Fastback And The Longboobs Discussion - Researchers Gave Shutdown And Ethics Prompts To AI And It Acted Like A Scorned WomanSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
In this episode of Crazy Wisdom, host Stewart Alsop talks with Jared Zoneraich, CEO and co-founder of PromptLayer, about how AI is reshaping the craft of software building. The conversation covers PromptLayer's role as an AI engineering workbench, the evolving art of prompting and evals, the tension between implicit and explicit knowledge, and how probabilistic systems are changing what it means to “code.” Stewart and Jared also explore vibe coding, AI reasoning, the black-box nature of large models, and what accelerationism means in today's fast-moving AI culture. You can find Jared on X @imjaredz and learn more or sign up for PromptLayer at PromptLayer.com.Check out this GPT we trained on the conversationTimestamps00:00 – Stewart Alsop opens with Jared Zoneraich, who explains PromptLayer as an AI engineering workbench and discusses reasoning, prompting, and Codex.05:00 – They explore implicit vs. explicit knowledge, how subject matter experts shape prompts, and why evals matter for scaling AI workflows.10:00 – Jared explains eval methodologies, backtesting, hallucination checks, and the difference between rigorous testing and iterative sprint-based prompting.15:00 – Discussion turns to observability, debugging, and the shift from deterministic to probabilistic systems, highlighting skill issues in prompting.20:00 – Jared introduces “LM idioms,” vibe coding, and context versus content—how syntax, tone, and vibe shape AI reasoning.25:00 – They dive into vibe coding as a company practice, cloud code automation, and prompt versioning for building scalable AI infrastructure.30:00 – Stewart reflects on coding through meditation, architecture planning, and how tools like Cursor and Claude Code are shaping AGI development.35:00 – Conversation expands into AI's cultural effects, optimism versus doom, and critical thinking in the age of AI companions.40:00 – They discuss philosophy, history, social fragmentation, and the possible decline of social media and liberal democracy.45:00 – Jared predicts a fragmented but resilient future shaped by agents and decentralized media.50:00 – Closing thoughts on AI-driven markets, polytheistic model ecosystems, and where innovation will thrive next.Key InsightsPromptLayer as AI Infrastructure – Jared Zoneraich presents PromptLayer as an AI engineering workbench—a platform designed for builders, not researchers. It provides tools for prompt versioning, evaluation, and observability so that teams can treat AI workflows with the same rigor as traditional software engineering while keeping flexibility for creative, probabilistic systems.Implicit vs. Explicit Knowledge – The conversation highlights a critical divide between what AI can learn (explicit knowledge) and what remains uniquely human (implicit understanding or “taste”). Jared explains that subject matter experts act as the bridge, embedding human nuance into prompts and workflows that LLMs alone can't replicate.Evals and Backtesting – Rigorous evaluation is essential for maintaining AI product quality. Jared explains that evals serve as sanity checks and regression tests, ensuring that new prompts don't degrade performance. He describes two modes of testing: formal, repeatable evals and more experimental sprint-based iterations used to solve specific production issues.Deterministic vs. Probabilistic Thinking – Jared contrasts the old, deterministic world of coding—predictable input-output logic—with the new probabilistic world of LLMs, where results vary and control lies in testing inputs rather than debugging outputs. This shift demands a new mindset: builders must embrace uncertainty instead of trying to eliminate it.The Rise of Vibe Coding – Stewart and Jared explore vibe coding as a cultural and practical movement. It emphasizes creativity, intuition, and context-awareness over strict syntax. Tools like Claude Code, Codex, and Cursor let engineers and non-engineers alike “feel” their way through building, merging programming with design thinking.AI Culture and Human Adaptation – Jared predicts that AI will both empower and endanger human cognition. He warns of overreliance on LLMs for decision-making and the coming wave of “AI psychosis,” yet remains optimistic that humans will adapt, using AI to amplify rather than atrophy critical thinking.A Fragmented but Resilient Future – The episode closes with reflections on the social and political consequences of AI. Jared foresees the decline of centralized social media and the rise of fragmented digital cultures mediated by agents. Despite risks of isolation, he remains confident that optimism, adaptability, and pluralism will define the next AI era.
10-06-25 - Flying Taxis Coming Within 2 Years And Testing In NY Now - Woman Smears Cybertruck w/Dog Poop Prompting Our Fastback And The Longboobs Discussion - Researchers Gave Shutdown And Ethics Prompts To AI And It Acted Like A Scorned WomanSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
AP correspondent Julie Walker reports the FDA approves another generic abortion pill, prompting outrage from conservatives.
Judy Dempsey notes that Russian drone activities are prompting several European nations to seek a collective "drone wall" and coordinate defense efforts independent of US leadership, signaling a shift in the transatlantic relationship. She highlights positive pro-European election results in Moldova and a temporary halt to the far-right AfD's momentum in German local elections. Europe remains hesitant about the Gaza plan but expects to contribute to reconstruction.
Judy Dempsey notes that Russian drone activities are prompting several European nations to seek a collective "drone wall" and coordinate defense efforts independent of US leadership, signaling a shift in the transatlantic relationship. She highlights positive pro-European election results in Moldova and a temporary halt to the far-right AfD's momentum in German local elections. Europe remains hesitant about the Gaza plan but expects to contribute to reconstruction. 1940 DANUBE
10-01-25 - Entertainment Drill - WED - Charlie Hunnam Plays Ed Gein In Netflix Movie And Visited His Grave Prompting Serial Killer DiscussionSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Don and Tom tackle the creeping role of AI in financial advice—highlighting Vanguard's new “nudges” on its platform—before pivoting into lively listener calls. The show explores the balance between saving and living (including an $800K earner debating a bigger house), the risks of high-yield gimmick ETFs like QQQI, the simplicity of age-based 529 plans, and the murky rules around paying kids into Roth IRAs. Humor, skepticism, and practical guidance keep the conversation grounded, with a side of leaf blowers, Italian villas, and Tom's inevitable puns. 0:10 Don's dramatic AI apocalypse intro and Vanguard “nudges” 1:20 Squarespace rant: how customer service died 4:13 Vanguard limiting fund lists—bias toward active funds? 6:22 AI is coming for investing advice 6:35 Listener call: $800K household, cheap mortgage, “living life” vs upgrading home 10:22 House affordability rules: 25–30% PITI, low-rate lock-in dilemma 12:19 Call from Jim in Bellevue: QQQI high-yield ETF 13:44 Why covered call income funds are risky, volatile, and gimmicky 17:41 Tech focus, March 2000 parallels, why diversification beats chasing yield 19:29 Covered call strategies—why they lose upside and add complexity 22:50 Listener email from Shauna: which Utah 529 portfolio to pick 24:36 Best choice = age-based glide path, simplicity and cost advantages 26:13 Follow-up caller: Roth IRAs for kids, risk of inflated wages and IRS scrutiny 29:24 Who checks wages? IRS shutdown jokes, K-1 confusions, AI tax analysis fail Learn more about your ad choices. Visit megaphone.fm/adchoices
10-01-25 - Entertainment Drill - WED - Charlie Hunnam Plays Ed Gein In Netflix Movie And Visited His Grave Prompting Serial Killer DiscussionSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Eddie Yoon, Sr Director, Paid Media at NP Digital, shows how CMOs can spin up a full creative campaign in ~30 minutes using AI. He breaks down a rapid “three-tab” workflow—Meta Ad Library for competitive research, GPT for strategy and prompts, and an image generator (Reeve) for instant mood boards—then extends it into testing (Trial Reels, TikTok hooks), product R&D, and agentic pipelines. We also riff on why the next decade could normalize solo billionaire founders, how Netflix foreshadowed AI-driven content, and what real-time, stylized, monetizable media will look like.Timestamps1:07 Meet Eddie Yoon—NP Digital, paid social × creative × AI background.1:49 “AI is redefining growth”: blistering company speed and scale.2:16 The solo-founder era & agentic executive teams.4:39 Enterprise example: HubSpot's leadership going all-in on AI.5:29 Founder example: Tyler at Beehive—shipping fast by listening + acting.6:30 Design & media: Netflix's early AI play; House of Cards data story.11:29 The 30-minute campaign challenge—Eddie's live plan.12:53 The three tabs: Meta Ad Library → GPT prompts → Reeve mockups.14:37 Copy/paste every active ad into GPT; ask for strategy synthesis.16:06 Five “board-level” ideas; forcing a single high-acceptance pitch.17:56 Image prompt for “Comfort 2.0” (eco-luxury, performance lifestyle).20:27 Prompting hack: “200+ IQ” to push for originality (avoid clichés).21:06 Locking on Comfort 2.0—“performance tech meets everyday life.”23:06 Iterating the mood board; feeding outputs back into GPT.23:30 If the client has the shoe already: do it all in AI (no photoshoot).24:39 Rapid tests: ethnicity, angle, color; Instagram Trial Reels.26:03 Beyond ads: full-funnel → product design & R&D with agents.27:24 100-page competitor deep dives from public signals.28:26 Scoring system (cutoff 85; 95+ are “winners”) to prioritize assets.30:13 Spinning GPT outputs into 10 TikTok hooks for creators/founders.31:32 Domain-tuned agents that deliver 90%-ready work.33:13 What's next: automatic video analysis and creative fixes.34:13 Next 12 months: IP-driven brands, real-time stylized video, avatars.35:43 Meta: capturing AI audio; partner via your agent in the future.36:12 Why solo $1B is realistic (and $100M solos even more so).Tools & Technologies Mentioned (with quick notes)Meta Ad Library — Public index of active FB/IG ads; great for competitive creative research.GPT — Used to analyze competitor ads, generate board-level strategies, image prompts, TikTok hooks, and run scoring frameworks.Reeve — Static image generator (Midjourney-like) for fast mood boards and spec creative.Midjourney — Alternative image generation tool for photorealistic concepts.VO3 — Motion/video generation tool referenced for animated concepts.Instagram Trial Reels — Organic test surface to gauge hooks/creatives with cold audiences before spend.TikTok — Distribution + hook testing via short scripts for creators/founders.Semrush — Search/keyword intel to complement social competitive analysis.SocialPeta — Creative/spend intelligence (legacy use; less relied upon now).AI Avatars & Agentic Flows — Persona-based creators and multi-agent pipelines to speed research, ideation, testing, and post-mortems.Subscribe at thisnewway.com to get the step-by-step playbooks, tools, and workflows.
Vanester Scott shared her journey of following God's prompting and direction for her life. In this episode she shared the story of how she met her husband, started her prayer ministry and upcoming community event for unity. Enjoy!
Top TakeawaysAI's real win in sales right now: offload repetitive tasks (triaging inboxes, drafting replies/follow-ups, note-taking, CRM updates) so sellers can focus on discovery, demos, and closing. Time to value is the new battleground. ChatGPT has reset expectations; buyers want activation on day one, not week 12. Meta-prompting → compounding quality. Prompts and personas should self-improve as your style and outcomes evolve. Context engineering increases quality. Simple details (who/where/when) measurably boost LLM output quality. Adoption reality check. Biggest blocker isn't tech—it's org inertia and middle-management friction. Start with a tiger-team pilot.Be great at your craft first. AI massively amplifies already-excellent practitioners. The AI for Sales Podcast is brought to you by BDR.ai, Nooks.ai, and ZoomInfo—the go-to-market intelligence platform that accelerates revenue growth.Skip the forms and website hunting—Chad will connect you directly with the right person at any of these companies.
#OZWATCH: JEREMY ZAKIS, NEW SOUTH WALES. #FRIENDSOFHISTORYDEBATINGSOCIETY. SUMMARY: Brisbane faces an unprecedented snake "siege" with two to three times the normal population, prompting public warnings regarding watering holes. In Katherine, NT, a 41-year-old woman died within an hour from a suspected King Brown neurotoxin bite. The venom caused respiratory failure and collapse within 20 minutes. 1890
More countries recognizing a Palestinian state has drawn angry response from Israel. AP correspondent Donna Warder reports.
In this episode, Alexandra Sunderland (VP of Engineering at Fellow) pulls back the curtain on how she runs engineering with agentic workflows that actually move the needle: background coding agents in Cursor that fix bugs while she's in meetings, Claude + MCPs to query Linear and auto-generate reports in seconds, and Zapier pipelines that turn meeting transcripts into daily briefs, real-time project risk pings, sales insights, and even 1:1 growth trackers. The theme: make conversations computable, specialize agents narrowly, and wire every tool together so ops happen while you sleep.Timestamps1:11 — Background: 13+ yrs with Aydin; author of Remote Engineering Management.2:13 — What is an “agent”? Alexandra's practical definition (automation + LLM).3:39 — Why specialized agents beat general ones (Sept 2025 reality check).5:25 — Cursor background agents via Slack VIP notifications—coding while she's away.8:00 — Hackathon: hand-built dev productivity dashboard vs. Claude + Linear MCP.10:38 — Why use Claude here instead of Cursor: downloadable PDFs & exploratory insights.13:03 — Interface shift: logging into Linear/GitHub less; notify via Slack instead.14:21 — Plan: live workflows that leaders can copy.15:31 — Workflow #1: Daily Brief in Zapier (9:00 a.m. trigger → transcripts → CoS-style digest).18:00 — Slack example of the generated daily brief.20:22 — Workflow #2: Project Meeting Insights—real-time blockers & cross-team risks.22:00 — Prompting style (“best VP of Eng in the world”) and why it helps.26:40 — Idea: an “Alexandra agent” that drafts her responses.27:59 — Workflow #3: Sales call mining → bug/feature requests for Eng.29:14 — Next step: Cursor agents created via API—fixes ready for human review minutes after calls.30:23 — Rolling Cursor to product & success; non-engineers leverage code context.31:16 — Auto-drafting help center docs with Cursor that can browse.32:34 — Future: docs auto-update—or vanish into on-demand LLM answers.34:52 — Workflow #4 (WIP): 1:1 growth tracker—extract coaching, strengths, feedback into a living doc.37:41 — Sales coaching automation: enforce key phrases/objection handling.38:10 — Playbook: start with simple “yesterday's conversations → insights,” then stack.39:24 — Next 12 months: tools connecting to each other, patterns across datasets.Tools & Technologies Mentioned (with quick notes)Cursor — AI-powered code editor with background agents (cloud-run) and Slack integration for async coding and fixes.Cursor Background Agents API — Programmatically spin up agents to implement bug fixes/features for later human review.Slack (VIP Notifications) — Marking the Cursor app as VIP ensures agent updates punch through Do Not Disturb.Claude — LLM used with MCPs to query data sources (e.g., Linear), generate PDFs, surface trends, and build ad-hoc reports.MCP (Model Context Protocol) — Standard to connect LLMs to tools/data (e.g., Linear) for live, permissioned operations.Linear — Issue/project tracker; source for ticket analytics (resolution rates, triage time, stage durations).Zapier — No-code automations; schedules, filters, formats, makes API calls, and runs AI by Zapier LLM steps.Fellow.ai — AI meeting assistant capturing summaries, actions, decisions; acts as an “AI chief of staff” across meetings.GitHub — Code hosting referenced as a UI Alexandra now visits less thanks to agentic workflows.Google Docs / Notion / Wiki — Destinations for auto-appending 1:1 growth notes and team principles.APIs (custom + vendor) — Zapier “Webhooks by Zapier”/custom API calls used to fetch transcripts and trigger agents.Subscribe at thisnewway.com to get the step-by-step playbooks, tools, and workflows.
Can AI save your sanity when therapy isn't enough? In this episode, Rajeev Kapur shares how ChatGPT became a lifeline for a suicidal business exec, repairing his marriage, reconnecting him with his daughter, and even saving his company. We cover AI therapy prompts, data privacy hacks, deepfake nightmares, and how to use AI responsibly without losing your soul. Topics Discussed: AI has been integrated into our lives for a long time. Mental health support can be augmented by AI tools. Therapists should embrace AI to enhance their practice. Prompting techniques can make AI more effective for users. Data privacy is crucial when using AI applications. Deepfakes pose significant risks to individuals and organizations. AI can help improve personal relationships and communication. The future of work may involve universal basic income due to AI advancements. Ethics in AI development is a pressing concern. AI is still in its early stages, with much potential ahead. Resources: Books: AI Made Simple (3rd Edition), Prompting Made Simple by Rajeev Kapur ---- GUEST WEBSITE: https://rajeev.ai/ ---- MORE FROM BROBOTS: Connect with us on Threads, Twitter, Instagram, Facebook, and Tiktok Subscribe to BROBOTS on Youtube Join our community in the BROBOTS Facebook group ---- LINKS TO OUR PARTNERS: Take control of how you'd like to feel with Apollo Neuro Explore the many benefits of cold therapy for your body with Nurecover Muse's Brain Sensing Headbands Improve Your Meditation Practice. Get started as a Certified Professional Life Coach! Get a Free One Year Supply of AG1 Vitamin D3+K2, 5 Travel Packs Revamp your life with Bulletproof Coffee You Need a Budget helps you quickly get out of debt, and save money faster! Start your own podcast!
09-09-25 - New Disease Fear Is Screw Worms Infecting Us As We Wonder How Many Chickens There Are - Rant Against Man Who Plays His Pan Flute On Top Of Piestewa Peak - US School Test Scores Are Low Prompting John To Call Again For Teachers To QuitSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
California Republican lawmakers are suing to block Governor Gavin Newsom's redistricting plan from the November ballot, as President Trump vows his own lawsuit against the state's effort to redraw its congressional maps to favor Democrats. That's despite Trump encouraging a similar effort in Texas that favors Republicans. Meanwhile, Newsom is trolling the President on social media, co-opting his taunting style. We'll talk with KQED's politics team about Newsom's tactics and get the latest redistricting news. What do you think of the Governor's methods? Guests: Marisa Lagos, politics correspondent, KQED - co-host of KQED's Political Breakdown Guy Marzorati, correspondent, KQED's California Politics and Government Desk Learn more about your ad choices. Visit megaphone.fm/adchoices
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