Podcasts about prompting

In the final episode of the Podcast-to-Book series, host Susan Diaz sits down with change leader and AI education lead Melissa Penton (Sun Life) for a human-first conversation about what actually makes AI adoption work. They talk productivity vs room-for-life, why one-prompt culture is snake oil, the shift from prompt engineering to context engineering, and the simplest enterprise question that changes everything: "What would make Monday easier for employees?" Episode summary Susan closes out the Podcast-to-Book sprint with a conversation that feels like the point of the whole series: AI isn't a tool problem. It's a people problem disguised as a tool problem. Melissa Penton shares her lens as a long-time change manager working in AI readiness and education inside a large organisation. Her focus isn't faster work. It's making room for what matters - and designing adoption in a way that's safe, honest, and grounded in real human tension points. Together, Susan and Melissa unpack why generic prompting courses aren't enough, why people get hives when they hear words like "workflow" and "agentic," and how leaders can create real change by starting with everyday pain. They also go deep on psychological safety, the fear of "training your robot replacement," and what it looks like to lead with humility in the biggest transformation most of us will live through.   Key takeaways Productivity is the doorway. Room-for-life is the goal. Saving time is nice. The real win is using that time to live in your "zone of genius" and have space for the things you care about. One-prompt culture is snake oil. Useful AI work is iterative, messy, and conversational. The magic isn't the prompt. It's the human steering, correcting, and refining. Prompt engineering is evolving into context engineering. The skill isn't "write a clever prompt." It's learning to give the right context, ask better questions, and build on responses. Enterprise adoption should start with one simple question: "What would make Monday easier for my employees?" That question forces leaders to solve real friction instead of buying shiny tools. The biggest people problem masquerading as an AI problem is readiness. AI is being thrown at people who don't know where to start, how it fits their real lives, or how it changes their work without threatening them. Training should be experiential, not theoretical. Courses can help. But capability sticks when people learn by doing, inside real workflows, with real tasks, and real feedback loops. Psychological safety is non-negotiable. People won't share pain points if they fear automation will erase their job. Leaders shouldn't make promises they can't keep. They should make learning safe and transferable. Workflows don't have to be scary. A workflow is just the steps you already take. "Ask a question → make notes → read notes → act." That's a workflow. Low-risk experiments lead to higher-risk breakthroughs. The "AI coffee warmer" might feel silly. But it's part of the lab. Small experiments teach the muscles needed for bigger transformations. Leadership in the AI era requires humility. Admit you're learning. Model curiosity. Use AI to explore recurring organisational stuck points, mediate perspectives, and surface patterns in conversations.   Timestamps  00:03 — Susan sets the scene: the final stretch of the 30-day podcast-to-book sprint 01:12 — Meet Melissa: change management, training, and leading AI education/readiness 02:31 — Productivity vs "making room for what matters" (crochet, hikes, real life) 03:29 — Time saved is table stakes… what are we doing with the time? 03:58 — Zone of Genius living and why AI should move you toward it 06:44 — Snake-oil prompts, "one prompt fixes your life," and why it makes Susan grumpy 08:02 — "I am the prompt": AI as an iterative, human conversation 09:21 — Prompting → context engineering (asking better questions is the skill) 09:50 — The enterprise question: "What will make Monday easier for employees?" 11:02 — Voice mode and why it changes tone, cadence, and output quality 14:27 — The biggest "AI problem" is actually a people/readiness problem 16:20 — Start with real tension points, not an abstract AI adoption plan 18:23 — Why "prompting courses" can repel people (language matters) 20:39 — Courses aren't bad… they're just not sufficient 21:49 — Cleaning workflows as the gateway drug to agentic thinking 22:44 — Agentic AI explained simply: consecutive steps without you in the middle 23:20 — "Workflow" definition for normal humans (no hives required) 24:12 — First 3 moves in 30 days: Monday, conversations, embedded learning 26:00 — Psychological safety: fear of replacement and why honesty matters 31:03 — Skill recognition: you're learning transferable capability, not training your replacement 33:35 — Whole-human value: you are not your job title 34:22 — The spiritual lens: AI should expand what humans can become 35:34 — Why "small silly tools" still matter (science lab thinking) 37:29 — Low-risk testing as the path to bigger breakthroughs 38:00 — Leadership advice: be humble, be curious, use AI to explore stuck patterns 40:58 — Where to find Melissa: LinkedIn + Substack 41:30 — "Purple person": bridging tech and business communication   Connect with Melissa Penton on LinkedIn Substack: Confessions of an AI User   If you're leading AI adoption, steal this question and use it today:  "What would make Monday easier for our people?" Then pick one friction point. Make it safer. Make it simpler. Let the learning compound. Connect with Susan Diaz on LinkedIn to get a conversation started. Agile teams move fast. Grab our 10 AI Deep Research Prompts to see how proven frameworks can unlock clarity in hours, not months. Find the prompt pack here.

Saya sedang melihat film dokumenter tentang DeepMind. Ini cerita Demis Hassabi ingin memecahkan masalah AGI. Mereka mencoba memecahkan protein folding problem.#AI https://www.youtube.com/watch?v=d95J8yzvjbQ

You're using AI for content. That's good. But if you're still writing prompts, manually editing outputs, and piecing everything together—you're doing the hardest part yourself.In this episode, Kristen explains why prompting is just the starting line, not the finish. She shares how she runs a two-person, multi-six-figure business and hasn't written or repurposed content from scratch in months. The shift? She stopped thinking of AI as a tool and started building it like a trainable team.Kristen breaks down what a background content team really looks like: agents that take one voice note and turn it into a week of formatted, platform-specific content that runs in the background without you touching it. This isn't about working faster on a hamster wheel—it's about building a system that gives you your life back.If you're still thinking in prompts, this episode will show you how to train AI to work for you instead.

Host Susan Diaz sits down with Jennifer Hufnagel (Hufnagel Consulting), an AI educator and AI readiness consultant who's trained 4K+ people. They break down what "AI readiness" actually means (spoiler: it's not buying Copilot), why AI doesn't fix broken processes or dirty data, and how leaders can build real capability through training programs, communities of practice, and properly resourced AI champions. Episode summary Susan Diaz and Jennifer Hufnagel met in "the most elite way possible": both were quoted in The Globe and Mail about women and AI. Jennifer shares her background as a business analyst and digital adoption / L&D consultant, and how she pivoted when clients began asking for AI workshops right after ChatGPT's release. Together, they map a simple but powerful framework: AI awareness (practice + play, foundational learning, early change management) AI readiness (software stack, data quality, workflows, current state, and - quietly - the "people audit") AI adoption (implementation, strategy, and ongoing integration) Jennifer explains why "audit" language scares people, but the work is essential - especially talking to humans about what's frustrating, what takes time, and where fear is showing up. She shares what she's seeing after training thousands: AI fluency is still low, people obsess over tools, and many assume AI will solve problems that are actually process or data issues. The second half gets practical: what "workflows" really mean (step-by-step checklists), how AI now makes documenting processes easier than ever (voice → SOPs), why prompt engineering isn't dead but "100 prompts for your bookkeeping business" is mostly snake oil, and why one-off training sessions don't create real fluency. They close with how to build sustainable AI capability: proper training programs, leadership-led culture, communities of practice, and protecting champions from becoming unpaid help desks. Key takeaways AI readiness is the middle of the journey. Jennifer frames AI maturity as: awareness → readiness → adoption. Most organisations skip readiness and wonder why adoption stalls. Readiness includes software, data, process… and people. You can call it a software/data/process audit, but you still have to talk to humans about their day-to-day work, pain points, and fears. That's where the truth lives. AI fluency is still lower than the headlines suggest. Jennifer questions rosy "90% adoption" stats because many rooms she's in still show low real-world usage beyond basic experimentation. Stop obsessing over tools. Companies are writing AI policy around tools and forcing everyone into a single platform. Jennifer argues the real goal is discernment, critical thinking, and clarity - not "pick one tool and pray". AI doesn't fix broken processes or dirty data. If your workflows aren't documented, AI will scale the chaos. If your data is messy, the analysis will be messy too. Readiness comes first. A workflow is just a checklist. Jennifer demystifies "workflow" as step-by-step instructions and ownership: who does what, when. Sticky notes on a wall is a valid start. Process documentation is easier than ever. You can dictate steps into a model (without passwords) and ask it to produce an SOP/checklist - getting knowledge out of people's heads and into a shareable format. Prompting isn't dead, but promise-all prompt packs are mostly hype. Prompting differs by model, and the best move is often to ask the model how to prompt it - and how to troubleshoot when output is wrong. One-off AI workshops don't create fluency. AI changes too fast. Real capability requires programs, practice, communities of practice, office hours, and change management - plus leadership modelling and culture. Don't burn out your AI champions. Champions need dedicated time, resources, and leadership sponsorship. Otherwise they become unpaid AI help desks and the entire initiative becomes fragile. Community of practice is the unlock. Jennifer shares her in-person "AI Chats & Bites" group and encourages finding online + in-person + internal communities to keep learning alive. Episode highlights 00:01 — The 30-day podcast-to-book sprint and why people are saying yes in December 00:40 — Susan + Jennifer meet via The Globe and Mail "women and AI" feature 01:21 — Jennifer's origin story: business analyst → digital adoption/L&D → AI readiness 04:09 — The three-part framework: awareness → readiness → adoption 05:03 — Readiness: software stack, data quality ("dirty data"), and mapping current state 06:13 — "People audit" without calling it that: interview humans about pain + fear 08:02 — What Jennifer sees after ~4,000 trainees: fluency still low + stats don't match reality 09:38 — AI doesn't fix broken processes; it scales whatever is there 10:55 — Workflows explained as checklists; "won the lottery" handoff test 12:18 — Dictate your process into AI → generate SOPs/checklists 14:24 — Prompting isn't dead; ask the model to help you prompt + troubleshoot 17:50 — Why one-off training doesn't work; AI fluency requires a program + practice 22:15 — Burning out champions and why AI culture must be top-down 27:49 — Communities of practice: online + local + internal 31:00 — Common mistakes: vending-machine mindset, believing output, not defining the problem 35:31 — Women and AI: opportunity, fear, resilience, and "be in the grey" 39:51 — Where to find Jennifer: hufnagelconsulting.ca + LinkedIn Guest info Jennifer Hufnagel Website: hufnagelconsulting.ca Email: hello@hufnagelconsulting.ca Best place to connect: LinkedIn - Jennifer Hufnagel If AI adoption feels stuck in your organization, don't buy another tool first. Start with readiness: Map one workflow end-to-end. Talk to the humans doing it daily. Clean up the process and data enough that AI can actually help. Then build fluency through a program - not a one-off workshop - and protect your champions with real time and resources.   Connect with Susan Diaz on LinkedIn to get a conversation started. Agile teams move fast. Grab our 10 AI Deep Research Prompts to see how proven frameworks can unlock clarity in hours, not months. Find the prompt pack here.

These profound demographic changes are significantly influencing white identity and societal dynamics. The prospect of becoming a numerical minority challenges the long-held perception of white Americans as the "prototypical ethnic group" or what it means to be "All-American."  This shift is seen by some as eroding material advantages historically associated with being white, prompting a deep re-evaluation of white identity itself.Become a supporter of this podcast: https://www.spreaker.com/podcast/racism-white-privilege-in-america--4473713/support.

Drew and Rory stumble back from the holiday chaos—one fresh off vacation, the other barely resurrected from a mystery NYC illness.Between fever dreams and booger fingers, they somehow manage to tear into ChatGPT's Image 1.5 disappointment, expose why Nano Banana Pro is quietly dominating their workflows, and reveal the Weavy automation setup that's actually working (while FreePik continues its reign of mediocre terror). The duo gets brutally honest about why OpenAI feels like it's slipping, why negative prompting might be more important than what you actually want to create, and how to build your own custom AI tools in Google AI Studio without selling your soul to another subscription. Plus: vintage Kodak rally cars, the art of perfect thumbnails, coconut water in cocktails, and why their illness prevention protocols involve more vitamin C than common sense. If you survived their holiday absence and made it through the mandatory 20-minute ramble tax, you'll be rewarded with legitimate workflow gold that actually ships.---⏱️ Midjourney Fast Hour00:01 A Mr. Sniffles cold open05:18 Prompting while sick, then getting cooked on X07:35 An “Am I an AI artist?” reality check15:08 Moodboards, unsettling styles, and “what counts as art”27:39 Blade, Pluribus, and movie still inspiration sites31:42 Midjourney V8 quiet, Style Creator alpha changes37:45 The pace of releases and tool fatigue40:37 World models, Veo 3, and the next leap43:28 ChatGPT Image 1.5 talk and why it's still behind46:12 Nano Banana Pro flex, Freepik waits, and why it matters49:17 Weavy workflow walkthrough: from ref to shot list55:26 Contact sheets, “mini LoRA” vibes, and system rules59:14 Kling o1 keyframes: why 3–10 seconds is a cheat code01:03:32 Real text and brand risks in outputs01:06:52 Build your own Nano tool in Google AI Studio01:08:01 Writing models: ChatGPT vs Gemini vs Claude01:09:23 Negative prompting becomes the main event01:11:25 Wrap, thumbnails, and holiday chaos

Better defaults reduce trial and error. Users get results faster. We explore usability.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

12-15-25 - TMZ Reporting Billy Crystal And Larry David Seen At Rob Reiner Home Prompting Frank's Idea Of Detective Duo Jewman And ThriftySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

12-15-25 - TMZ Reporting Billy Crystal And Larry David Seen At Rob Reiner Home Prompting Frank's Idea Of Detective Duo Jewman And ThriftySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this GoodKind Podcast episode, Clayton, Amy, and Chris explore how artificial intelligence is quietly reshaping everyday life — from school and creativity to productivity and parenting. What begins as a practical conversation about using AI for efficiency quickly turns into a deeper discussion about discernment, formation, and what should (and should not) be offloaded to technology.The team unpacks what AI does well — summarizing information, organizing ideas, brainstorming, and speeding up tasks — while also naming its limitations, including its tendency to sound confident even when it's wrong. They discuss why better prompts matter, how AI can short-circuit learning if used too early, and why struggle and effort still play a critical role in creativity, wisdom, and growth.They also reflect on how parents are already navigating AI in schools, writing assignments, music, and communication — often faster than expected — and why modeling intentional use matters more than setting rigid rules. Throughout the conversation, they return to a central question: Which human is this replacing? — and how that question can guide healthier decisions around technology.If you've ever wondered whether using AI is making things easier at the cost of meaning… or how to integrate helpful tools without letting them become formative forces… this episode offers a thoughtful, grounded framework for using AI with clarity, boundaries, and purpose — especially in family life.You learn how AI works best as a support tool for information and efficiency, not a replacement for creativity or wisdom.Clear prompting leads to better results, while vague questions often produce shallow or incorrect output.AI excels at summarizing, brainstorming, and organizing information — but still requires discernment.Not everything should be offloaded; relationships, creativity, and formation matter too much.Overusing AI can weaken creative and learning muscles, especially for kids.Asking “Which human is this replacing?” helps clarify whether AI use is appropriate.Modeling intentional AI use shapes how children understand effort, learning, and meaning.00:00 Introduction to AI and Everyday Life02:41 What AI Is Good At (and What It's Not)05:28 Prompting, Accuracy, and Discernment08:47 AI, Creativity, and the Cost of Ease12:11 Parenting, School, and Early AI Exposure15:36 Which Human Is This Replacing?18:42 Modeling Healthy Technology Habits21:10 Final Thoughts and Key TakeawaysKeywords:artificial intelligence and families, Christian parenting and technology, AI and creativity, using AI responsibly, parenting in the age of AI, technology and formation, discernment with AI, raising kids with technology, meaningful learning vs convenienceTakeawaysChapters

Get my free 1 hour AI Playbook: https://fos.now/yt-gd-discover-1-hour-ai-playbookWant my help scaling your business using systems? Book a free Systems Audit call here: https://fos.now/yt-apply-557AI just made one of its biggest jumps forward, and if you're not building the right skills right now, you're already starting behind the curve. Over the past year, I've been running my entire company through Claude, ChatGPT, Whisperflow, and a full AI-powered workflow, and in this video I'm breaking down the six core AI skills every founder needs to scale faster, work less, and build real leverage.You'll learn how to turn your voice into clean, polished writing instantly, how to build a complete content engine using Claude projects, how to create a world-class YouTube scriptwriting system, how to turn sales calls into copywriting gold, how to build a second brain that drives smarter decisions, and how to map your entire business into AI systems that save you hours every day.By the end of this video, you'll understand how to use AI as a true strategic partner instead of just another tool, so you can grow faster without adding more chaos to your business.Already doing $30K+/month? Come to my next free workshop and I'll show you how to systemize your business and get your time back → https://fos.now/yt-workshop-557Want to LEARN proven systems to grow your personal brand? Go here: https://fos.now/yt-newsletter-557Connect with me:Website: https://fos.now/yt-founder-os-557Twitter: https://twitter.com/matt_gray_LinkedIn: https://www.linkedin.com/in/mattgray1TikTok: https://www.tiktok.com/@realmattgrayInstagram: https://instagram.com/matthgray00:00 - Intro00:18 - Voice-to-Text Mastery02:20 - AI-Assisted Content Creation08:30 - Building SOPs with Loom AI09:50 - Sales Analysis11:30 - Data-Driven Decision Making15:45 - Prompting and Workflow Design#onepersonbusiness #creatoreconomy #entrepreneurshipDisclaimer: Information shared here is for educational purposes only. Individuals and business owners should evaluate their own business strategies and identify any potential risks. The information shared here is not a guarantee of success. Your results may vary. This video shares my personal experience and growth building businesses over 15+ years of consistent effort. Your results will vary depending on your own actions, strategies, and circumstances.

TLDR: It was Claude :-)When I set out to compare ChatGPT, Claude, Gemini, Grok, and ChatPRD for writing Product Requirement Documents, I figured they'd all be roughly equivalent. Maybe some subtle variations in tone or structure, but nothing earth-shattering. They're all built on similar transformer architectures, trained on massive datasets, and marketed as capable of handling complex business writing.What I discovered over 45 minutes of hands-on testing revealed not just which tools are better for PRD creation, but why they're better, and more importantly, how you should actually be using AI to accelerate your product work without sacrificing quality or strategic thinking.If you're an early or mid-career PM in Silicon Valley, this matters to you. Because here's the uncomfortable truth: your peers are already using AI to write PRDs, analyze features, and generate documentation. The question isn't whether to use these tools. The question is whether you're using the right ones most effectively.So let me walk you through exactly what I did, what I learned, and what you should do differently.The Setup: A Real-World Test CaseHere's how I structured the experiment. As I said at the beginning of my recording, “We are back in the Fireside PM podcast and I did that review of the ChatGPT browser and people seemed to like it and then I asked, uh, in a poll, I think it was a LinkedIn poll maybe, what should my next PM product review be? And, people asked for ChatPRD.”So I had my marching orders from the audience. But I wanted to make this more comprehensive than just testing ChatPRD in isolation. I opened up five tabs: ChatGPT, Claude, Gemini, Grok, and ChatPRD.For the test case, I chose something realistic and relevant: an AI-powered tutor for high school students. Think KhanAmigo or similar edtech platforms. This gave me a concrete product scenario that's complex enough to stress-test these tools but straightforward enough that I could iterate quickly.But here's the critical part that too many PMs get wrong when they start using AI for product work: I didn't just throw a single sentence at these tools and expect magic.The “Back of the Napkin” Approach: Why You Still Need to Think“I presume everybody agrees that you should have some formulated thinking before you dump it into the chatbot for your PRD,” I noted early in my experiment. “I suppose in the future maybe you could just do, like, a one-sentence prompt and come out with the perfect PRD because it would just know everything about you and your company in the context, but for now we're gonna do this more, a little old-school AI approach where we're gonna do some original human thinking.”This is crucial. I see so many PMs, especially those newer to the field, treat AI like a magic oracle. They type in “Write me a PRD for a social feature” and then wonder why the output is generic, unfocused, and useless.Your job as a PM isn't to become obsolete. It's to become more effective. And that means doing the strategic thinking work that AI cannot do for you.So I started in Google Docs with what I call a “back of the napkin” PRD structure. Here's what I included:Why: The strategic rationale. In this case: “Want to complement our existing edtech business with a personalized AI tutor, uh, want to maintain position industry, and grow through innovation. on mission for learners.”Target User: Who are we building for? “High school students interested in improving their grades and fundamentals. Fundamental knowledge topics. Specifically science and math. Students who are not in the top ten percent, nor in the bottom ten percent.”This is key—I got specific. Not just “students,” but students in the middle 80%. Not just “any subject,” but science and math. This specificity is what separates useful AI output from garbage.Problem to Solve: What's broken? “Students want better grades. Students are impatient. Students currently use AI just for finding the answers and less to, uh, understand concepts and practice using them.”Key Elements: The feature set and approach.Success Metrics: How we'd measure success.Now, was this a perfectly polished PRD outline? Hell no. As you can see from my transcript, I was literally thinking out loud, making typos, restructuring on the fly. But that's exactly the point. I put in maybe 10-15 minutes of human strategic thinking. That's all it took to create a foundation that would dramatically improve what came out of the AI tools.Round One: Generating the Full PRDWith my back-of-the-napkin outline ready, I copied it into each tool with a simple prompt asking them to expand it into a more complete PRD.ChatGPT: The Reliable GeneralistChatGPT gave me something that was... fine. Competent. Professional. But also deeply uninspiring.The document it produced checked all the boxes. It had the sections you'd expect. The writing was clear. But when I read it, I couldn't shake the feeling that I was reading something that could have been written for literally any product in any company. It felt like “an average of everything out there,” as I noted in my evaluation.Here's what ChatGPT did well: It understood the basic structure of a PRD. It generated appropriate sections. The grammar and formatting were clean. If you needed to hand something in by EOD and had literally no time for refinement, ChatGPT would save you from complete embarrassment.But here's what it lacked: Depth. Nuance. Strategic thinking that felt connected to real product decisions. When it described the target user, it used phrases that could apply to any edtech product. When it outlined success metrics, they were the obvious ones (engagement, retention, test scores) without any interesting thinking about leading indicators or proxy metrics.The problem with generic output isn't that it's wrong, it's that it's invisible. When you're trying to get buy-in from leadership or alignment from engineering, you need your PRD to feel specific, considered, and connected to your company's actual strategy. ChatGPT's output felt like it was written by someone who'd read a lot of PRDs but never actually shipped a product.One specific example: When I asked for success metrics, ChatGPT gave me “Student engagement rate, Time spent on platform, Test score improvement.” These aren't wrong, but they're lazy. They don't show any thinking about what specifically matters for an AI tutor versus any other educational product. Compare that to Claude's output, which got more specific about things like “concept mastery rate” and “question-to-understanding ratio.”Actionable Insight: Use ChatGPT when you need fast, serviceable documentation that doesn't need to be exceptional. Think: internal updates, status reports, routine communications. Don't rely on it for strategic documents where differentiation matters. If you do use ChatGPT for important documents, treat its output as a starting point that needs significant human refinement to add strategic depth and company-specific context.Gemini: Better Than ExpectedGoogle's Gemini actually impressed me more than I anticipated. The structure was solid, and it had a nice balance of detail without being overwhelming.What Gemini got right: The writing had a nice flow to it. The document felt organized and logical. It did a better job than ChatGPT at providing specific examples and thinking through edge cases. For instance, when describing the target user, it went beyond demographics to consider behavioral characteristics and motivations.Gemini also showed some interesting strategic thinking. It considered competitive positioning more thoughtfully than ChatGPT and proposed some differentiation angles that weren't in my original outline. Good AI tools should add insight, not just regurgitate your input with better formatting.But here's where it fell short: the visual elements. When I asked for mockups, Gemini produced images that looked more like stock photos than actual product designs. They weren't terrible, but they weren't compelling either. They had that AI-generated sheen that makes it obvious they came from an image model rather than a designer's brain.For a PRD that you're going to use internally with a team that already understands the context, Gemini's output would work well. The text quality is strong enough, and if you're in the Google ecosystem (Docs, Sheets, Meet, etc.), the integration is seamless. You can paste Gemini's output directly into Google Docs and continue iterating there.But if you need to create something compelling enough to win over skeptics or secure budget, Gemini falls just short. It's good, but not great. It's the solid B+ student: reliably competent but rarely exceptional.Actionable Insight: Gemini is a strong choice if you're working in the Google ecosystem and need good integration with Docs, Sheets, and other Google Workspace tools. The quality is sufficient for most internal documentation needs. It's particularly good if you're working with cross-functional partners who are already in Google Workspace. You can share and collaborate on AI-generated drafts without friction. But don't expect visual mockups that will wow anyone, and plan to add your own strategic polish for high-stakes documents.Grok: Not Ready for Prime TimeLet's just say my expectations were low, and Grok still managed to underdeliver. The PRD felt thin, generic, and lacked the depth you need for real product work.“I don't have high expectations for grok, unfortunately,” I said before testing it. Spoiler alert: my low expectations were validated.Actionable Insight: Skip Grok for product documentation work right now. Maybe it'll improve, but as of my testing, it's simply not competitive with the other options. It felt like 1-2 years behind the others.ChatPRD: The Specialized ToolNow this was interesting. ChatPRD is purpose-built for PRDs, using foundational models underneath but with specific tuning and structure for product documentation.The result? The structure was logical, the depth was appropriate, and it included elements that showed understanding of what actually matters in a PRD. As I reflected: “Cause this one feels like, A human wrote this PRD.”The interface guides you through the process more deliberately than just dumping text into a general chat interface. It asks clarifying questions. It structures the output more thoughtfully.Actionable Insight: If you're a technical lead without a dedicated PM, or you're a PM who wants a more structured approach to using AI for PRDs, ChatPRD is worth the specialized focus. It's particularly good when you need something that feels authentic enough to share with stakeholders without heavy editing.Claude: The Clear WinnerBut the standout performer, and I'm ranking these, was Claude.“I think we know that for now, I'm gonna say Claude did the best job,” I concluded after all the testing. Claude produced the most comprehensive, thoughtful, and strategically sound PRD. But what really set it apart were the concept mocks.When I asked each tool to generate visual mockups of the product, Claude produced HTML prototypes that, while not fully functional, looked genuinely compelling. They had thoughtful UI design, clear information architecture, and felt like something that could actually guide development.“They were, like, closer to, like, what a Lovable would produce or something like that,” I noted, referring to the quality of low-fidelity prototypes that good designers create.The text quality was also superior: more nuanced, better structured, and with more strategic depth. It felt like Claude understood not just what a PRD should contain, but why it should contain those elements.Actionable Insight: For any PRD that matters, meaning anything you'll share with leadership, use to get buy-in, or guide actual product development, you might as well start with Claude. The quality difference is significant enough that it's worth using Claude even if you primarily use another tool for other tasks.Final Rankings: The Definitive HierarchyAfter testing all five tools on multiple dimensions: initial PRD generation, visual mockups, and even crafting a pitch paragraph for a skeptical VP of Engineering, here's my final ranking:* Claude - Best overall quality, most compelling mockups, strongest strategic thinking* ChatPRD - Best for structured PRD creation, feels most “human”* Gemini - Solid all-around performance, good Google integration* ChatGPT - Reliable but generic, lacks differentiation* Grok - Not competitive for this use case“I'd probably say Claude, then chat PRD, then Gemini, then chat GPT, and then Grock,” I concluded.The Deeper Lesson: Garbage In, Garbage Out (Still Applies)But here's what matters more than which tool wins: the realization that hit me partway through this experiment.“I think it really does come down to, like, you know, the quality of the prompt,” I observed. “So if our prompt were a little more detailed, all that were more thought-through, then I'm sure the output would have been better. But as you can see we didn't really put in brain trust prompting here. Just a little bit of, kind of hand-wavy prompting, but a little better than just one or two sentences.”And we still got pretty good results.This is the meta-insight that should change how you approach AI tools in your product work: The quality of your input determines the quality of your output, but the baseline quality of the tool determines the ceiling of what's possible.No amount of great prompting will make Grok produce Claude-level output. But even mediocre prompting with Claude will beat great prompting with lesser tools.So the dual strategy is:* Use the best tool available (currently Claude for PRDs)* Invest in improving your prompting skills ideally with as much original and insightful human, company aware, and context aware thinking as possible.Real-World Workflows: How to Actually Use This in Your Day-to-Day PM WorkTheory is great. Here's how to incorporate these insights into your actual product management workflows.The Weekly Sprint Planning WorkflowEvery PM I know spends hours each week preparing for sprint planning. You need to refine user stories, clarify acceptance criteria, anticipate engineering questions, and align with design and data science. AI can compress this work significantly.Here's an example workflow:Monday morning (30 minutes):* Review upcoming priorities and open your rough notes/outline in Google Docs* Open Claude and paste your outline with this prompt:“I'm preparing for sprint planning. Based on these priorities [paste notes], generate detailed user stories with acceptance criteria. Format each as: User story, Business context, Technical considerations, Acceptance criteria, Dependencies, Open questions.”Monday afternoon (20 minutes):* Review Claude's output critically* Identify gaps, unclear requirements, or missing context* Follow up with targeted prompts:“The user story about authentication is too vague. Break it down into separate stories for: social login, email/password, session management, and password reset. For each, specify security requirements and edge cases.”Tuesday morning (15 minutes):* Generate mockups for any UI-heavy stories:“Create an HTML mockup for the login flow showing: landing page, social login options, email/password form, error states, and success redirect.”* Even if the HTML doesn't work perfectly, it gives your designers a starting pointBefore sprint planning (10 minutes):* Ask Claude to anticipate engineering questions:“Review these user stories as if you're a senior engineer. What questions would you ask? What concerns would you raise about technical feasibility, dependencies, or edge cases?”* This preparation makes you look thoughtful and helps the meeting run smoothlyTotal time investment: ~75 minutes. Typical time saved: 3-4 hours compared to doing this manually.The Stakeholder Alignment WorkflowGetting alignment from multiple stakeholders (product leadership, engineering, design, data science, legal, marketing) is one of the hardest parts of PM work. AI can help you think through different stakeholder perspectives and craft compelling communications for each.Here's how:Step 1: Map your stakeholders (10 minutes)Create a quick table in a doc:Stakeholder | Primary Concern | Decision Criteria | Likely Objections VP Product | Strategic fit, ROI | Company OKRs, market opportunity | Resource allocation vs other priorities VP Eng | Technical risk, capacity | Engineering capacity, tech debt | Complexity, unclear requirements Design Lead | User experience | User research, design principles | Timeline doesn't allow proper design process Legal | Compliance, risk | Regulatory requirements | Data privacy, user consent flowsStep 2: Generate stakeholder-specific communications (20 minutes)For each key stakeholder, ask Claude:“I need to pitch this product idea to [Stakeholder]. Based on this PRD, create a 1-page brief addressing their primary concern of [concern from your table]. Open with the specific value for them, address their likely objection of [objection], and close with a clear ask. Tone should be [professional/technical/strategic] based on their role.”Then you'll have customized one-pagers for your pre-meetings with each stakeholder, dramatically increasing your alignment rate.Step 3: Synthesize feedback (15 minutes)After gathering stakeholder input, ask Claude to help you synthesize:“I got the following feedback from stakeholders: [paste feedback]. Identify: (1) Common themes, (2) Conflicting requirements, (3) Legitimate concerns vs organizational politics, (4) Recommended compromises that might satisfy multiple parties.”This pattern-matching across stakeholder feedback is something AI does really well and saves you hours of mental processing.The Quarterly Planning WorkflowQuarterly or annual planning is where product strategy gets real. You need to synthesize market trends, customer feedback, technical capabilities, and business objectives into a coherent roadmap. AI can accelerate this dramatically.Six weeks before planning:* Start collecting input (customer interviews, market research, competitive analysis, engineering feedback)* Don't wait until the last minuteFour weeks before planning:Dump everything into Claude with this structure:“I'm creating our Q2 roadmap. Context:* Business objectives: [paste from leadership]* Customer feedback themes: [paste synthesis]* Technical capabilities/constraints: [paste from engineering]* Competitive landscape: [paste analysis]* Current product gaps: [paste from your analysis]Generate 5 strategic themes that could anchor our Q2 roadmap. For each theme:* Strategic rationale (how it connects to business objectives)* Key initiatives (2-3 major features/projects)* Success metrics* Resource requirements (rough estimate)* Risks and mitigations* Customer segments addressed”This gives you a strategic framework to react to rather than starting from a blank page.Three weeks before planning:Iterate on the most promising themes:“Deep dive on Theme 3. Generate:* Detailed initiative breakdown* Dependencies on platform/infrastructure* Phasing options (MVP vs full build)* Go-to-market considerations* Data requirements* Open questions requiring research”Two weeks before planning:Pressure-test your thinking:“Play devil's advocate on this roadmap. What are the strongest arguments against each initiative? What am I likely missing? What failure modes should I plan for?”This adversarial prompting forces you to strengthen weak points before your leadership reviews it.One week before planning:Generate your presentation:“Create an executive presentation for this roadmap. Structure: (1) Market context and strategic imperative, (2) Q2 themes and initiatives, (3) Expected outcomes and metrics, (4) Resource requirements, (5) Key risks and mitigations, (6) Success criteria for decision. Make it compelling but data-driven. Tone: confident but not overselling.”Then add your company-specific context, visual brand, and personal voice.The Customer Research WorkflowAI can't replace talking to customers, but it can help you prepare better questions, analyze feedback more systematically, and identify patterns faster.Before customer interviews:“I'm interviewing customers about [topic]. Generate:* 10 open-ended questions that avoid leading the witness* 5 follow-up questions for each main question* Common cognitive biases I should watch for* A framework for categorizing responses”This prep work helps you conduct better interviews.After interviews:“I conducted 15 customer interviews. Here are the key quotes: [paste anonymized quotes]. Identify:* Recurring themes and patterns* Surprising insights that contradict our assumptions* Segments with different needs* Implied needs customers didn't articulate directly* Recommended next steps for validation”AI is excellent at pattern-matching across qualitative data at scale.The Crisis Management WorkflowSomething broke. The site is down. Data was lost. A feature shipped with a critical bug. You need to move fast.Immediate response (5 minutes):“Critical incident. Details: [brief description]. Generate:* Incident classification (Sev 1-4)* Immediate stakeholders to notify* Draft customer communication (honest, apologetic, specific about what happened and what we're doing)* Draft internal communication for leadership* Key questions to ask engineering during investigation”Having these drafted in 5 minutes lets you focus on coordination and decision-making rather than wordsmithing.Post-incident (30 minutes):“Write a post-mortem based on this incident timeline: [paste timeline]. Include:* What happened (technical details)* Root cause analysis* Impact quantification (users affected, revenue impact, time to resolution)* What went well in our response* What could have been better* Specific action items with owners and deadlines* Process changes to prevent recurrence Tone: Blameless, focused on learning and improvement.”This gives you a strong first draft to refine with your team.Common Pitfalls: What Not to Do with AI in Product ManagementNow let's talk about the mistakes I see PMs making with AI tools. Pitfall #1: Treating AI Output as FinalThe biggest mistake is copy-pasting AI output directly into your PRD, roadmap presentation, or stakeholder email without critical review.The result? Documents that are grammatically perfect but strategically shallow. Presentations that sound impressive but don't hold up under questioning. Emails that are professionally worded but miss the subtext of organizational politics.The fix: Always ask yourself:* Does this reflect my actual strategic thinking, or generic best practices?* Would my CEO/engineering lead/biggest customer find this compelling and specific?* Are there company-specific details, customer insights, or technical constraints that only I know?* Does this sound like me, or like a robot?Add those elements. That's where your value as a PM comes through.Pitfall #2: Using AI as a Crutch Instead of a ToolSome PMs use AI because they don't want to think deeply about the product. They're looking for AI to do the hard work of strategy, prioritization, and trade-off analysis.This never works. AI can help you think more systematically, but it can't replace thinking.If you find yourself using AI to avoid wrestling with hard questions (”Should we build X or Y?” “What's our actual competitive advantage?” “Why would customers switch from the incumbent?”), you're using it wrong.The fix: Use AI to explore options, not to make decisions. Generate three alternatives, pressure-test each one, then use your judgment to decide. The AI can help you think through implications, but you're still the one choosing.Pitfall #3: Not IteratingGetting mediocre AI output and just accepting it is a waste of the technology's potential.The PMs who get exceptional results from AI are the ones who iterate. They generate an initial response, identify what's weak or missing, and ask follow-up questions. They might go through 5-10 iterations on a key section of a PRD.Each iteration is quick (30 seconds to type a follow-up prompt, 30 seconds to read the response), but the cumulative effect is dramatically better output.The fix: Budget time for iteration. Don't try to generate a complete, polished PRD in one prompt. Instead, generate a rough draft, then spend 30 minutes iterating on specific sections that matter most.Pitfall #4: Ignoring the Political and Human ContextAI tools have no understanding of organizational politics, interpersonal relationships, or the specific humans you're working with.They don't know that your VP of Engineering is burned out and skeptical of any new initiatives. They don't know that your CEO has a personal obsession with a specific competitor. They don't know that your lead designer is sensitive about not being included early enough in the process.If you use AI-generated communications without layering in this human context, you'll create perfectly worded documents that land badly because they miss the subtext.The fix: After generating AI content, explicitly ask yourself: “What human context am I missing? What relationships do I need to consider? What political dynamics are in play?” Then modify the AI output accordingly.Pitfall #5: Over-Relying on a Single ToolDifferent AI tools have different strengths. Claude is great for strategic depth, ChatPRD is great for structure, Gemini integrates well with Google Workspace.If you only ever use one tool, you're missing opportunities to leverage different strengths for different tasks.The fix: Keep 2-3 tools in your toolkit. Use Claude for important PRDs and strategic documents. Use Gemini for quick internal documentation that needs to integrate with Google Docs. Use ChatPRD when you want more guided structure. Match the tool to the task.Pitfall #6: Not Fact-Checking AI OutputAI tools hallucinate. They make up statistics, misrepresent competitors, and confidently state things that aren't true. If you include those hallucinations in a PRD that goes to leadership, you look incompetent.The fix: Fact-check everything, especially:* Statistics and market data* Competitive feature claims* Technical capabilities and limitations* Regulatory and compliance requirementsIf the AI cites a number or makes a factual claim, verify it independently before including it in your document.The Meta-Skill: Prompt Engineering for PMsLet's zoom out and talk about the underlying skill that makes all of this work: prompt engineering.This is a real skill. The difference between a mediocre prompt and a great prompt can be 10x difference in output quality. And unlike coding or design, where there's a steep learning curve, prompt engineering is something you can get good at quickly.Principle 1: Provide Context Before InstructionsBad prompt:“Write a PRD for an AI tutor”Good prompt:“I'm a PM at an edtech company with 2M users, primarily high school students. We're exploring an AI tutor feature to complement our existing video content library and practice problems. Our main competitors are Khan Academy and Course Hero. Our differentiation is personalized learning paths based on student performance data.Write a PRD for an AI tutor feature targeting students in the middle 80% academically who struggle with science and math.”The second prompt gives Claude the context it needs to generate something specific and strategic rather than generic.Principle 2: Specify Format and ConstraintsBad prompt:“Generate success metrics”Good prompt:“Generate 5-7 success metrics for this feature. Include a mix of:* Leading indicators (early signals of success)* Lagging indicators (definitive success measures)* User behavior metrics* Business impact metricsFor each metric, specify: name, definition, target value, measurement method, and why it matters.”The structure you provide shapes the structure you get back.Principle 3: Ask for Multiple OptionsBad prompt:“What should our Q2 priorities be?”Good prompt:“Generate 3 different strategic approaches for Q2:* Option A: Focus on user acquisition* Option B: Focus on engagement and retention* Option C: Focus on monetizationFor each option, detail: key initiatives, expected outcomes, resource requirements, risks, and recommendation for or against.”Asking for multiple options forces the AI (and forces you) to think through trade-offs systematically.Principle 4: Specify Audience and ToneBad prompt:“Summarize this PRD”Good prompt:“Create a 1-paragraph summary of this PRD for our skeptical VP of Engineering. Tone: Technical, concise, addresses engineering concerns upfront. Focus on: technical architecture, resource requirements, risks, and expected engineering effort. Avoid marketing language.”The audience and tone specification ensures the output will actually work for your intended use.Principle 5: Use Iterative RefinementDon't try to get perfect output in one prompt. Instead:First prompt: Generate rough draft Second prompt: “This is too generic. Add specific examples from [our company context].” Third prompt: “The technical section is weak. Expand with architecture details and dependencies.” Fourth prompt: “Good. Now make it 30% more concise while keeping the key details.”Each iteration improves the output incrementally.Let me break down the prompting approach that worked in this experiment, because this is immediately actionable for your work tomorrow.Strategy 1: The Structured Outline ApproachDon't go from zero to full PRD in one prompt. Instead:* Start with strategic thinking - Spend 10-15 minutes outlining why you're building this, who it's for, and what problem it solves* Get specific - Don't say “users,” say “high school students in the middle 80% of academic performance”* Include constraints - Budget, timeline, technical limitations, competitive landscape* Dump your outline into the AI - Now ask it to expand into a full PRD* Iterate section by section - Don't try to perfect everything at onceThis is exactly what I did in my experiment, and even with my somewhat sloppy outline, the results were dramatically better than they would have been with a single-sentence prompt.Strategy 2: The Comparative Analysis PatternOne technique I used that worked particularly well: asking each tool to do the same specific task and comparing results.For example, I asked all five tools: “Please compose a one paragraph exact summary I can share over DM with a highly influential VP of engineering who is generally a skeptic but super smart.”This forced each tool to synthesize the entire PRD into a compelling pitch while accounting for a specific, challenging audience. The variation in quality was revealing—and it gave me multiple options to choose from or blend together.Actionable tip: When you need something critical (a pitch, an executive summary, a key decision framework), generate it with 2-3 different AI tools and take the best elements from each. This “ensemble approach” often produces better results than any single tool.Strategy 3: The Iterative Refinement LoopDon't treat the AI output as final. Use it as a first draft that you then refine through conversation with the AI.After getting the initial PRD, I could have asked follow-up questions like:* “What's missing from this PRD?”* “How would you strengthen the success metrics section?”* “Generate 3 alternative approaches to the core feature set”Each iteration improves the output and, more importantly, forces me to think more deeply about the product.What This Means for Your CareerIf you're an early or mid-career PM reading this, you might be thinking: “Great, so AI can write PRDs now. Am I becoming obsolete?”Absolutely not. But your role is evolving, and understanding that evolution is critical.The PMs who will thrive in the AI era are those who:* Excel at strategic thinking - AI can generate options, but you need to know which options align with company strategy, customer needs, and technical feasibility* Master the art of prompting - This is a genuine skill that separates mediocre AI users from exceptional ones* Know when to use AI and when not to - Some aspects of product work benefit enormously from AI. Others (user interviews, stakeholder negotiation, cross-functional relationship building) require human judgment and empathy* Can evaluate AI output critically - You need to spot the hallucinations, the generic fluff, and the strategic misalignments that AI inevitably producesThink of AI tools as incredibly capable interns. They can produce impressive work quickly, but they need direction, oversight, and strategic guidance. Your job is to provide that guidance while leveraging their speed and breadth.The Real-World Application: What to Do Monday MorningLet's get tactical. Here's exactly how to apply these insights to your actual product work:For Your Next PRD:* Block 30 minutes for strategic thinking - Write your back-of-the-napkin outline in Google Docs or your tool of choice* Open Claude (or ChatPRD if you want more structure)* Copy your outline with this prompt:“I'm a product manager at [company] working on [product area]. I need to create a comprehensive PRD based on this outline. Please expand this into a complete PRD with the following sections: [list your preferred sections]. Make it detailed enough for engineering to start breaking down into user stories, but concise enough for leadership to read in 15 minutes. [Paste your outline]”* Review the output critically - Look for generic statements, missing details, or strategic misalignments* Iterate on specific sections:“The success metrics section is too vague. Please provide 3-5 specific, measurable KPIs with target values and explanation of why these metrics matter.”* Generate supporting materials:“Create a visual mockup of the core user flow showing the key interaction points.”* Synthesize the best elements - Don't just copy-paste the AI output. Use it as raw material that you shape into your final documentFor Stakeholder Communication:When you need to pitch something to leadership or engineering:* Generate 3 versions of your pitch using different tools (Claude, ChatPRD, and one other)* Compare them for:* Clarity and conciseness* Strategic framing* Compelling value proposition* Addressing likely objections* Blend the best elements into your final version* Add your personal voice - This is crucial. AI output often lacks personality and specific company context. Add that yourself.For Feature Prioritization:AI tools can help you think through trade-offs more systematically:“I'm deciding between three features for our next release: [Feature A], [Feature B], and [Feature C]. For each feature, analyze: (1) Estimated engineering effort, (2) Expected user impact, (3) Strategic alignment with making our platform the go-to solution for [your market], (4) Risk factors. Then recommend a prioritization with rationale.”This doesn't replace your judgment, but it forces you to think through each dimension systematically and often surfaces considerations you hadn't thought of.The Uncomfortable Truth About AI and Product ManagementLet me be direct about something that makes many PMs uncomfortable: AI will make some PM skills less valuable while making others more valuable.Less valuable:* Writing boilerplate documentation* Creating standard frameworks and templates* Generating routine status updates* Synthesizing information from existing sourcesMore valuable:* Strategic product vision and roadmapping* Deep customer empathy and insight generation* Cross-functional leadership and influence* Critical evaluation of options and trade-offs* Creative problem-solving for novel situationsIf your PM role primarily involves the first category of tasks, you should be concerned. But if you're focused on the second category while leveraging AI for the first, you're going to be exponentially more effective than your peers who resist these tools.The PMs I see succeeding aren't those who can write the best PRD manually. They're those who can write the best PRD with AI assistance in one-tenth the time, then use the saved time to talk to more customers, think more deeply about strategy, and build stronger cross-functional relationships.Advanced Techniques: Beyond Basic PRD GenerationOnce you've mastered the basics, here are some advanced applications I've found valuable:Competitive Analysis at Scale“Research our top 5 competitors in [market]. For each one, analyze: their core value proposition, key features, pricing strategy, target customer, and likely product roadmap based on recent releases and job postings. Create a comparison matrix showing where we have advantages and gaps.”Then use web search tools in Claude or Perplexity to fact-check and expand the analysis.Scenario Planning“We're considering three strategic directions for our product: [Direction A], [Direction B], [Direction C]. For each direction, map out: likely customer adoption curve, required technical investments, competitive positioning in 12 months, and potential pivots if the hypothesis proves wrong. Then identify the highest-risk assumptions we should test first for each direction.”This kind of structured scenario thinking is exactly what AI excels at—generating multiple well-reasoned perspectives quickly.User Story GenerationAfter your PRD is solid:“Based on this PRD, generate a complete set of user stories following the format ‘As a [user type], I want to [action] so that [benefit].' Include acceptance criteria for each story. Organize them into epics by functional area.”This can save your engineering team hours of grooming meetings.The Tools Will Keep Evolving. Your Process Shouldn'tHere's something important to remember: by the time you read this, the specific rankings might have shifted. Maybe ChatGPT-5 has leapfrogged Claude. Maybe a new specialized tool has emerged.But the core principles won't change:* Do strategic thinking before touching AI* Use the best tool available for your specific task* Iterate and refine rather than accepting first outputs* Blend AI capabilities with human judgment* Focus your time on the uniquely human aspects of product managementThe specific tools matter less than your process for using them effectively.A Final Experiment: The Skeptical VP TestI want to share one more insight from my testing that I think is particularly relevant for early and mid-career PMs.Toward the end of my experiment, I gave each tool this prompt: “Please compose a one paragraph exact summary I can share over DM with a highly influential VP of engineering who is generally a skeptic but super smart.”This is such a realistic scenario. How many times have you needed to pitch an idea to a skeptical technical leader via Slack or email? Someone who's brilliant, who's seen a thousand product ideas fail, and who can spot b******t from a mile away?The quality variation in the responses was fascinating. ChatGPT gave me something that felt generic and safe. Gemini was better but still a bit too enthusiastic. Grok was... well, Grok.But Claude and ChatPRD both produced messages that felt authentic, technically credible, and appropriately confident without being overselling. They acknowledged the engineering challenges while framing the opportunity compellingly.The lesson: When the stakes are high and the audience is sophisticated, the quality of your AI tool matters even more. That skeptical VP can tell the difference between a carefully crafted message and AI-generated fluff. So can your CEO. So can your biggest customers.Use the best tools available, but more importantly, always add your own strategic thinking and authentic voice on top.Questions to Consider: A Framework for Your Own ExperimentsAs I wrapped up my Loom, I posed some questions to the audience that I'll pose to you:“Let me know in the comments, if you do your PRDs using AI differently, do you start with back of the envelope? Do you say, oh no, I just start with one sentence, and then I let the chatbot refine it with me? Or do you go way more detailed and then use the chatbot to kind of pressure test it?”These aren't rhetorical questions. Your answer reveals your approach to AI-augmented product work, and different approaches work for different people and contexts.For early-career PMs: I'd recommend starting with more detailed outlines. The discipline of thinking through your product strategy before touching AI will make you a stronger PM. You can always compress that process later as you get more experienced.For mid-career PMs: Experiment with different approaches for different types of documents. Maybe you do detailed outlines for major feature PRDs but use more iterative AI-assisted refinement for smaller features or updates. Find what optimizes your personal productivity while maintaining quality.For senior PMs and product leaders: Consider how AI changes what you should expect from your PM team. Should you be reviewing more AI-generated first drafts and spending more time on strategic guidance? Should you be training your team on effective AI usage? These are leadership questions worth grappling with.The Path Forward: Continuous ExperimentationMy experiment with these five AI tools took 45 minutes. But I'm not done experimenting.The field of AI-assisted product management is evolving rapidly. New tools launch monthly. Existing tools get smarter weekly. Prompting techniques that work today might be obsolete in three months.Your job, if you want to stay at the forefront of product management, is to continuously experiment. Try new tools. Share what works with your peers. Build a personal knowledge base of effective prompts and workflows. And be generous with what you learn. The PM community gets stronger when we share insights rather than hoarding them.That's why I created this Loom and why I'm writing this post. Not because I have all the answers, but because I'm figuring it out in real-time and want to share the journey.A Personal Note on Coaching and ConsultingIf this kind of practical advice resonates with you, I'm happy to work with you directly.Through my pm coaching practice, I offer 1:1 executive, career, and product coaching for PMs and product leaders. We can dig into your specific challenges: whether that's leveling up your AI workflows, navigating a career transition, or developing your strategic product thinking.I also work with companies (usually startups or incubation teams) on product strategy, helping teams figure out PMF for new explorations and improving their product management function.The format is flexible. Some clients want ongoing coaching, others prefer project-based consulting, and some just want a strategic sounding board for a specific decision. Whatever works for you.Reach out through tomleungcoaching.com if you're interested in working together.OK. Enough pontificating. Let's ship greatness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit firesidepm.substack.com

Pernahkah Anda membayangkan memiliki asisten super cerdas yang siap melakukan apa saja, namun hanya diam menunggu perintah yang tepat? Di episode kali ini, kita akan membongkar wawasan tentang prompting—sebuah seni baru dalam berkomunikasi dengan kecerdasan buatan. Prompting bukan sekadar mengetik kata kunci di kolom pencarian; ini adalah bahasa literasi baru abad ke-21, jembatan penghubung antara imajinasi manusia yang abstrak dan kemampuan eksekusi mesin yang luar biasa presisi. Lupakan cara lama Anda menggunakan internet. Di era AI generatif, kita tidak lagi sekadar mencari informasi yang sudah ada, kita sedang menciptakannya bersama mitra digital. Namun, ingat satu aturan emas: mesin tidak bisa membaca pikiran, ia hanya membaca instruksi. Kualitas jawaban yang Anda dapatkan berbanding lurus dengan kualitas promptyang Anda berikan. Kita akan membahas mengapa memberi konteks, menetapkan peran, dan menjadi spesifik adalah kunci untuk mengubah jawaban robot yang kaku menjadi solusi yang brilian dan penuh wawasan. Jadi, siapkan diri Anda untuk mengubah cara bekerja dan berkarya secara fundamental. Baik Anda seorang profesional, mahasiswa, atau sekadar penjelajah teknologi, menguasai prompting berarti memegang kendali penuh atas potensi teknologi di ujung jari Anda. Mari kita pelajari bagaimana caranya menjadi "konduktor" bagi orkestra digital ini dan membuat AI bekerja sesuai keinginan kita, selengkapnya hanya di INIKOPER!

Episode 73: Psst, content design is about to have a major momentIn 2025's final episode of Content Rookie, I introduce you to what I have coined the ”roguessance” of content design.I truly believe content design is about to have a major moment, thanks to developments like Google Disco redefining how we design and build experiences and interfaces as a whole. What are suddenly the most valuable skills on the market? Content strategy. Content systems. Clear comms. Prompting. Negotiating. Who does that best? Well, we content folks, of course!Why the latest developments in LLMs and AI are leveling the playing field for builders, writers, and designers, and how we can take ownership, are just some of the learning outcomes in this episode.Happy New Year, and thanks for listening to Content Rookie!Connect with the host, Nicole Michaelis:nicoletells.comhi@nicoletells.comhttps://www.linkedin.com/in/nicoletells/

2026 nutzen wir KI nicht mehr als Tool, sondern direkt im Alltag! In der neuen Folge geht es um eine Veränderung, die gerade still und leise passiert und dennoch vieles verändert. Denn KI wird nicht nur besser. Sie wird „unsichtbar", weil sie direkt dort eingebaut ist, wo Arbeit, Lernen und Zusammenarbeit stattfinden. Aber was bedeutet das für L&D, Trainings, Coaching und Organisationsentwicklung? Ich spreche über Agentic AI und darüber, warum Prompting allein 2026 nicht mehr reicht. Wenn KI eigenständig handeln kann, braucht es etwas anderes als gute Befehle. Ein Teil der Folge dreht sich außerdem um die aktuellen Entwicklungen bei Notebook LM und den Vergleich zu ChatGPT. Ich zeige, worin sich beide Systeme inzwischen deutlich unterscheiden, wofür Notebook LM im Lern und Wissenskontext besonders stark wird und wie sich mit ChatGPT 5.2 die Rolle von KI erneut verschiebt. Zum Schluss teile ich noch drei Red Flags, die L&D aktuell ausbremsen, statt es zukunftsfähig zu machen. Darum geht's im Überblick:

In this episode, host Peter Bauman (Le Random's editor in chief) speaks with transdisciplinary artist Stephanie Dinkins about AI as a container for preserving oral history, tradition, and the kinds of community knowledge that rarely make it onto the internet.Dinkins shares how a chance encounter with Bina48 in 2014 reshaped her practice. They discuss how this connects to her push for small, community-driven data that protects nuance and self-definition, especially for Black and Brown communities, against the homogenizing pull of large corporate models.They also cover Not the Only One as a “living archive” of family memory, the politics of access, privacy, and consent, and why Dinkins treats imagination (and hyperstition) as a practical method for building the AI futures we actually want.Monday's editorial (Beeple on Robot Dogs as Canvas): https://www.lerandom.art/editorial/beeple-on-robot-dogs-as-canvasChapters

Collab with Artlist and get 2 extra months for free here:https://artlist.io/artlist-70446?artlist_aid=the505podcast_2970&utm_source=affiliate_p&utm_medium=the505podcast_2970&utm_campaign=the505podcast_2970The 10 Minute Personal Brand Kickstart (FREE): https://the505podcast.courses/personalbrandkickstartWhat's up Rock Nation! Today we're joined by Jeff Su. He's an ex-Google employee, turned full-time creator and AI educator. Jeff helps solopreneurs and creators turn AI tools into real leverage, not just shortcuts.In this episode, Jeff shares why AI-native creators will outpace everyone in 2026, how to use AI to replace a 10-person content team, and why good prompts are built on systems, not templates. He also breaks down his repurposing workflow, the red team prompt strategy, and why AI won't replace you, but a smarter creator using AI will.Check out Jeff here:https://www.youtube.com/ ⁨@JeffSu⁩  https://www.instagram.com/j.sushie/SUSCRIBE TO OUR NEWSLETTER: https://the505podcast.ac-page.com/rock-reportKostas' Lightroom Presetshttps://www.kostasgarcia.com/store-1/p/kglightroompresetsgreeceCOP THE BFIGGY "ESSENTIALS" SFX PACK HERE: https://courses.the505podcast.com/BFIGGYSFXPACKTimestamps: 0:00 – Intro1:03 – How Creators Can Use AI as a Tool, Not a Threat2:53 – AI Isn't Replacing You—Bad Creators Are Replaceable4:16 – Why AI Content Won't Kill Human-Made Content5:12 – Using AI at Google vs. as a Creator6:49 – What Are Gemini Gems and How Do They Work?8:09 – ChatGPT vs Claude vs Gemini: Which AI for What Task?10:41 – Why Most People Should Start with ChatGPT12:03 – AI's Impact on Solo Creators and Business Scaling12:44 – The Smart Way to Create 50+ Podcast Clips a Month14:18 – Sponsored Segment: Artlist15:49 – The Biggest Trap Creators Fall Into with AI18:59 – A Hybrid Approach to AI Video Clipping20:32 – The 3 Levels of AI Fluency: Curious, Literate, Native22:19 – Why You Need to Use Text Expanders for Prompting23:18 – Text Expander Tools: Alfred, Raycast & More25:39 – Getting Better AI Results Starts with Better Prompts26:28 – Why Most People Never Advance with AI Tools28:57 – There's No AI Playbook (Yet)—And Why That Matters32:02 – Winning Skeptics Over to the Power of AI33:21 – Reverse Prompt Engineering Explained35:28 – Building a Prompt Database in Notion37:50 – Organizing Your AI Workflow Like a Pro39:21 – Jeff's Research Process Using ChatGPT & Notion41:25 – What is Red Teaming and How to Use It With AI43:12 – Behind Jeff's YouTube Workflow: From Idea to Upload46:02 – How AI Helps Explain Complex Concepts Clearly47:12 – What to Include in Your ChatGPT Custom Instructions50:02 – Evergreen vs. Limiting Custom Instructions50:58 – Why Custom Instructions Can Hurt More Than Help52:53 – Best Practices for Structuring Effective Prompts54:50 – How Prompting Is Like Excel Shortcuts for AI56:16 – Why You Need Battle-Tested Prompts for Your Workflow1:01:33 – Why Reverse Prompting Saves You Hours1:02:13 – Prompting with Hashtags & XML: Advanced Tips1:04:09 – Using AI to Improve Video Prompts for GenAI Tools1:07:05 – Notion Setup: Jeff's Full YouTube Content System1:10:05 – Using AI to Add Clarity Without Losing Personality1:11:33 – Avoid the “Curse of Knowledge” With AI Assistance1:13:40 – How Custom Instructions Shape AI Tone of Voice1:14:40 – Where Most People Go Wrong With Custom Instructions1:16:36 – How Overly Specific Instructions Pigeonhole AI1:17:46 – Bad vs. Good Examples of Custom Instructions1:19:19 – AI Bias: Why Tools May Overfit to Your Role1:20:06 – Best Custom Instructions for General Use1:26:06 – How AI Boosts Productivity Across Roles1:27:15 – Final Tips for Personalizing AI Assistants1:29:36 – Balancing Efficiency With Authenticity in Content1:32:19 – Post Pod DebriefIf you liked this episode please send it to a friend and take a screenshot for your story! And as always, we'd love to hear from you guys on what you'd like to hear us talk about or potential guests we should have on. DM US ON IG: (Our DM's are always open!) Bfiggy: https://www.instagram.com/bfiggy/ Kostas: https://www.instagram.com/kostasg95/ TikTok:Bfiggy: https://www.tiktok.com/bfiggy/ Kostas: https://www.tiktok.com/kostasgarcia/

Rising Tensions: Hezbollah's Rearmament and Hamas's Defiance: Colleague Jonathan Schanzer warns that Hezbollah has rebuilt its strength in Lebanon using Iranian weapons, prompting Israeli threats of a full-scale attack, noting that Hamas refuses to disarm in Gaza, supported by Turkey and Qatar, while the U.S. moves to designate Muslim Brotherhood branches as terrorist organizations. 1953

A new AI enhancement now lets Ring devices match faces to stored profiles. Privacy watchdogs warn the system could be exploited if safeguards fail. Ring responded by emphasizing encryption, user consent, and limited data retention.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Jeff Farnan, Representative for Missouri's 1st district, joins Chris and Brad Young and explains how he came to create legislation that would curb artificial intelligence scams. He says AI is, 'a great tool,' but there are always going to be people taking advantage of it. He says Missouri is one of only 3 states without any 'deepfake' laws.

Get the free NotebookLM guide: https://clickhubspot.com/wph Episode 87: Can AI know you well enough to create audio content tailored to your interests—without you ever prompting it? Nathan Lands (https://x.com/NathanLands) is joined by Raiza Martin (https://x.com/raizamrtn), one of the creators behind Google's NotebookLM and now co-founder of Huxe, a new startup carving the path toward truly personal AI. Raiza shares her unconventional journey from leading innovation at Google to building Huxe, an app that generates personalized audio (think “AI radio made just for you”) driven by your daily habits and interests—without you having to initiate the conversation. The episode dives into what it means to design AI for real human needs, the balancing act of privacy and helpfulness, and the vision for a future where your AI assistant proactively enhances your everyday life. They also discuss where AI products are succeeding, how creating trust is an overlooked challenge, and why the next breakthrough will be more about fitting seamlessly into our routines than about being “smarter.” Check out The Next Wave YouTube Channel if you want to see Matt and Nathan on screen: https://lnk.to/thenextwavepd — Show Notes: (00:00) From NotebookLM to Huxe (04:29) Finding AI's Killer Use Case (06:33) Users' Unique Huxe Usage Insights (12:24) Proactive AI: A New Approach (16:02) Daily Brief Insights (17:21) VCs Monitoring Funding Opportunities (21:33) ChatGPT's Role in Everyday AI (24:43) App Adoption and Design Insights (29:20) Uniquely Human Skills Matter (31:11) Modern Childhood and Connection (33:27) Understanding Tech Basics for Kids — Mentions: Raiza Martin: https://www.linkedin.com/in/whatsaraiza Huxe: https://www.huxe.com/ NotebookLM: https://notebooklm.google/ ChatGPT Pulse: https://openai.com/index/introducing-chatgpt-pulse/ Factory: https://factory.ai/ Get the guide to build your own Custom GPT: https://clickhubspot.com/tnw — Check Out Matt's Stuff: • Future Tools - https://futuretools.beehiiv.com/ • Blog - https://www.mattwolfe.com/ • YouTube- https://www.youtube.com/@mreflow — Check Out Nathan's Stuff: Newsletter: https://news.lore.com/ Blog - https://lore.com/ The Next Wave is a HubSpot Original Podcast // Brought to you by Hubspot Media // Production by Darren Clarke // Editing by Ezra Bakker Trupiano

Episode Summary In this episode, Cary talks with Keven Ellison, Vice President of Marketing at AIS, a technology company that evolved from selling office equipment to providing IT services, telecom, security solutions, and now AI tools. Keven shares how, even at age 63, he's fully embraced the potential of AI and has become the self-appointed "AI Ambassador" at his company. His excitement and curiosity shine through as he breaks down how businesses can better understand and use AI tools—especially ChatGPT—to solve real problems. He also introduces "Prompt Master," a tool he created to help people ask better questions and get more valuable results from AI tools. 3 Key Takeaways Prompting isn't just asking questions: Most users don't know how to prompt well, which leads to basic or misleading AI responses. Keven's Prompt Master helps users provide the right context to get better results. Different tools have different strengths: ChatGPT is the best all-around option, Claude is excellent for human-like writing, and Gemini is great for visuals and data visualization. Prompting styles need to be adjusted depending on the tool. The future of work is AI collaboration: Keven emphasizes that success with AI isn't about being an expert—it's about staying curious, experimenting, and building systems that help others understand and apply these tools more effectively. About Keven Ellison Keven Ellison is the VP of Marketing at AIS, a company that has transitioned from traditional office equipment to a full-stack technology provider. With over 30 years of marketing experience in both public and private sectors, Keven is passionate about using AI to improve business operations and decision-making. He's also the creator of Prompt Master—a tool designed to help teams write more effective AI prompts. You can find him actively sharing AI insights and tool updates on LinkedIn, where he posts multiple times per week. Connect WIth Keven: https://www.linkedin.com/in/kevenellison/ Keven's Prompting Tools PromptMaster XL 1.3: PromptMaster XL 1.3 is a tool that helps people get much better results from AI by teaching it exactly what they want. Instead of typing a random prompt and hoping the AI understands, PromptMaster XL shows you how to ask smarter, clearer questions so the AI gives you more accurate, useful answers. It's like having a "prompt coach" that helps you turn rough ideas into high-quality instructions the AI can easily follow. This makes AI faster, easier to use, and way more reliable for things like writing, schoolwork, marketing, business, or creative projects.   Image Prompt Architect 1.1: Image Architect 1.1 is a tool that helps you tell AI exactly how you want pictures to look — by guiding you to create clear, precise instructions (prompts) so the AI generates better images. Instead of guessing what the AI might draw, Image Architect 1.1 helps you describe color, style, layout, and details carefully so the AI "sees" your idea the way you do. It's like having a design assistant that turns your imagination into a picture. That makes it easier to get nice, useful images for art, presentations, social media, school projects or creative work.     Cary offers customized one-on-one ChatGPT training in 60 minute sessions. Find out more information on the sessions, answers to frequent questions, and how to register at www.ChatGPTExperiment.com +++++++++ CONNECT WITH CARY ChatGPT Podcast Website: www.ChatGPTExperiment.com Marketing Podcast: www.PracticalMarketingShow.com Cary's Agency Website: www.CMWeston.com LinkedIn: https://www.linkedin.com/in/caryweston LINKEDIN NEWSLETTER The Chat GPT Experiment is also a LinkedIn Newsletter and you can find it here: https://www.linkedin.com/newsletters/the-chat-gpt-experiment-7110348839919702016/ MUSIC CREDITS The instrumental music used in this podcast is called "Curious" by Podington Bear".

Send us a textWe unpack brand misreads around DEI, then shift into AI's new place in music as an AI artist hits the Billboard charts. The second half breaks down No Limit vs Cash Money, why showmanship beat scarcity, and who could credibly face Jay-Z in a Versus.• Target's inclusivity optics and how brands underestimate cultural risk• AI as tool vs replacement in music creation• Prompting as a communication skill and why it matters• The ethics and reality of relationships with AI• Service apps, convenience trade-offs, and hidden costs• No Limit vs Cash Money: attendance, presence, and MVPs• Snoop's loyalty, Master P's protection, and legacy moments• Mannie Fresh vs KLC and production identity• Who can match Jay-Z: Wayne, Nas, Drake, Kanye• Why Jay vs Nas makes the most musical senseYoutube to https://youtube.com/playlist?list=PLPIs6Ko7BCc9l5jlE5AbAUqZ0gAOhmuq- https://mixed-vibez-drip.printify.me/

Companies keep approaching AI the way they approached every other tech rollout: install it, train on it, expect immediate returns. But AI isn't software. It's imperfect by design, doesn't follow a predictable implementation curve, and the gap between what leadership promised the board and what's actually happening is becoming a serious problem. In this episode of The Trending Communicator, host Dan Nestle sits down with Chris Gee, founder of Chris Gee Consulting and strategic advisor to Ragan's Center for AI Strategy. Chris has survived four career reinventions driven by technological disruption—from watching his graphic design degree become obsolete the day he graduated to now helping organizations navigate the shift to agentic AI. His motto, "copilot, not autopilot," frames the entire conversation. Chris and Dan dig into why AI adoption is stalling—because companies are treating transformation like a switch to flip rather than a capability to build. They explore the parallel to 1993's Internet boom and why the adoption curve is right on schedule despite executive frustration. The conversation gets practical: Chris shares how he built an AI agent named "Alexa Irving" for client onboarding, and they tackle whether doom-and-gloom predictions from AI CEOs are helping or hurting the people who actually need to use these tools. Listen in and hear about... Why the adoption curve for AI mirrors the early Internet The $17 trillion argument against AI replacing all jobs (hint: someone has to buy things) How prompting skills aren't going away Building agentic AI with guardrails: Chris's "Alexa Irving" experiment Why "copilot, not autopilot" is more than a slogan—it's a survival strategy The skills gap nobody's addressing and why we need more brains who understand AI, not fewer Notable Quotes "My motto is copilot, not autopilot. I wholeheartedly believe that we are going to make the most progress using AI in tandem—where humans focus on the things that we do well and we use AI for the things it does better than we do." — Chris Gee [04:19] "17 is $17 trillion—that's what the American consumer spends per year. 70 is the percentage of US GDP that represents. And zero is the amount of money that AI chatbots, LLMs, and agents have to spend." — Chris Gee [23:57] "Your ability was never simply in your ability to string together words and phrases, but to translate experiences or emotions and create connection with other humans." — Chris Gee [36:44] "It's not thinking and it never will be thinking. So if we understand that, then we understand it won't be thinking like a human." — Chris Gee [1:07:00] Resources and Links Dan Nestle Inquisitive Communications | Website The Trending Communicator | Website Communications Trends from Trending Communicators | Dan Nestle's Substack Dan Nestle | LinkedIn Chris Gee Chris Gee Consulting | chrisgee.me Chris Gee | LinkedIn The Intelligent Communicator Newsletter | chrisgee.me (sign up on website) Timestamps 0:00:00 AI Transformation: Hype vs. Reality in Communications0:06:00 Human Touch vs. Automation in Service Jobs0:12:40 Early Career Transformation & Adapting to Technology0:18:00 AI Adoption Curve: Early Adopters and Laggards0:23:30 Tech Disruption, Job Fears, and Economic Impact0:29:10 Prompting and Obstacles to AI Adoption0:34:45 Redefining Skill Sets & Human Value with AI0:40:45 Efficiency, Productivity, and Creativity with AI Tools0:46:20 Rethinking Work: Flexible Schedules & Four-Day Weeks0:51:39 Practical AI Use Cases: Experiment and Upgrade0:55:11 Agentic AI: Autonomous Agents and Guardrails1:01:29 Autonomous Agents: Oversight, Guardrails, and Risks1:08:15 AI Is Imperfect: Why Human Judgment Remains Essential1:14:16 AI Quirks, Prompting Challenges, and Adoption Friction1:19:41 Wrap-Up: Finding Chris Gee & Newsletter/Prompt Suggestions1:21:18 Final Thoughts & Episode Closing (Notes co-created by Human Dan, Claude, and Castmagic) Learn more about your ad choices. Visit megaphone.fm/adchoices

Send us a textHow to use AI strategically to save time, increase productivity, and grow your business faster—without losing your unique voice.After over a year of using AI in my business (and teaching my clients to do the same), I'm sharing what I've learned about leveraging AI strategically to increase productivity, save time, and work smarter—not harder.In this episode, I break down:Why AI matters now – A Chief Economist at a Canadian business conference highlighted AI as a low-cost investment that increases business effectiveness, especially in a slower economyTypes of AI platforms – Generalist tools (ChatGPT, Sintra) vs. specialized tools (Descript for video/podcast editing, Perplexity for research, and more)The power of prompting – Why "garbage in, garbage out" applies to AI, and how giving proper context and clear instructions changes everythingTeaching your AI about your business – How paid subscriptions let you train AI agents on your frameworks, sales philosophy, and brand voice so you don't repeat yourselfUsing AI to amplify (not replace) your uniqueness – I never ask AI for content ideas; instead, I use it as my executive assistant and typewriter to process my ideas fasterReal examples from my business – How I use AI to turn one podcast episode into show notes, social captions, and email newsletters in under an hour (instead of days)AI for research – How I used ChatGPT to do months' worth of market research in one hour for a 2026 projectWhat to be careful about – Automations, integrations, confidentiality, intellectual property, and data limitsIf you've been curious about AI but not sure where to start—or if you're already using it but want to get better results—this episode will give you a clear, practical roadmap.Resources & LinksChatGPT – Generalist AI platform (great for beginners)Sintra – European AI platform designed for business owners (Maggie's choice) - check it out HEREDescript – AI tool for podcast and video editing - check it here Perplexity – AI research tool with sources and citationsGemini – Google's generalist AI platformFree Training: AI for Sales & Marketing Learn how to use AI for social media content that's unique to your brand and saves you time.  GET IT HEREConnect with Maggie:Website: https://www.stairwaytoleadership.com/Instagram: @maggieperotin.s2lLinkedIn: Maggie Perotin

Prompting each other for the weird phrases we always say to each other.

11-24-25 - Michael Bidwill Spotted At Ra Ra Room Before End Of Overtime Cardinals Loss Prompting John To Think He Must Be Meeting w/Someone To Sell The TeamSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

11-24-25 - Michael Bidwill Spotted At Ra Ra Room Before End Of Overtime Cardinals Loss Prompting John To Think He Must Be Meeting w/Someone To Sell The TeamSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

-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.

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.

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.

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

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

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.

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.

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.

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.

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.