Podcasts about use ai

Go to www.LearningLeader.com for full show notes This is brought to you by Insight Global. If you need to hire one person, hire a team of people, or transform your business through Talent or Technical Services, Insight Global's team of 30,000 people around the world has the hustle and grit to deliver. My Guest: Nick Gray is the author of The Two-Hour Cocktail Party and founder of Museum Hack. He's mastered the art of hosting events that strengthen networks and build genuine connections. In this conversation, he shares practical systems for hosting gatherings, why every leader needs a personal website, and lessons learned from his viral blind date trip to Tokyo. The Learning Leader Show Key Learnings Two Great Ice Breaker Questions:  What's a compliment that someone has given you that you've never forgotten about?  If you could teach any class about a topic that you're an expert on, what would it be? The power of a network is real: As a leader, you're probably hiring people regularly or looking for investors. By hosting simple, lightweight meetups or dinner parties, or happy hours once a quarter, you can strengthen your network, build it, and keep those loose connections or weak ties warm. Mix professional and personal contacts: For me, a really boring event would be all work people. Look for occupational diversity. If you're hosting a work event, invite some other random folks who you know are gonna be good conversationalists and add to the energy. Don't reach for the top shelf first. Most important advice for leaders: do not invite your most impressive contact to your very first happy hour or meetup. Your first party should be for your neighbors, the parents of kids at your school, those LinkedIn connections, high school buddies you haven't seen in a while. Your first party should be a comfortable meetup for 15 to 22 people that you host at your home with just cocktails, not a dinner party. Then slowly, once a quarter, you'll be adding more people to it and filtering your list. Collect RSVPs to ensure attendance. New hosts are absolutely terrified that nobody will arrive. As long as you get a minimum of 15 people to show up, your party will generally be a success. Use platforms like Partiful or Mixily (not Paperless Post or Evite) to get people to RSVP, let them know what to expect, and send reminder messages. Ten days before, send a reminder message hyping up the party. About a week before, send another reminder message with a little dossier of who the attendees are. Write something little: "Ryan Hawk hosts a podcast. He wrote a book. He lives in Ohio. Ask him about the ski trip he went on with his family." This serves to make anxious people or socially awkward feel like they're welcome and they have a conversational access point. Practical hosting tips on event day: Label your trash cans and your bathrooms. As people arrive, greet and welcome every single person, and make them a name tag. Write it out right in front of them, first name only. Do not pre-write your name tags. Force collisions through structured activities. Your job as a leader is to go through life collecting the interesting people that you meet and helping them meet each other.  Can you become a connector? One way to be a connector is to host these meetups and force the collisions. Lead two or three rounds of introductions at your meetup. Make a little announcement 30 minutes after it starts: "There are so many interesting people here. I want you all to meet each other. We're gonna split into small groups. It might seem silly, but I promise the purpose tonight is for you to talk to as many new people as possible. We're gonna split into small groups of three or four people, and you're gonna go around and tell your life story in two minutes." End on time, especially for weekday events: Host from 6:30 to 8:30 PM with a hard stop on Tuesday or Wednesday nights. People appreciate having an end time because they have responsibilities. Having that end time makes them more likely to RSVP yes and actually attend. "I get more compliments on my party ending on time, and they leave with a positive experience, so they want to return for another." Why every leader needs a personal website. If you have a blue check verified on Instagram, if you post at least once a month on LinkedIn, you probably need your own personal website. It's proactive reputation management. People are out there searching for you on Google and on ChatGPT. It may not happen every single day, but it probably happens every week. Whether it's parents of your kids at school, whether it's new employees, people are googling you. You want to have a personal website to put your best foot forward and make a good impression. Carrd.co to create a simple homepage or cloudflare to set up your domain name.  Keep it simple: You don't need a Gary Vee type page. Your page can look like a Google Doc. Feed these large language models your story and bio. My website is plain text, simple homepage. I used to have a fancy design site. Now I'm like, dude, it doesn't matter. 80% of my visitors are on their cell phone and just want to read some text and have some links. The tweet from 2024 that changed everything.  The viral Tokyo blind date trip taught me I was ready to share my life with someone. I ended up meeting my wife a couple of months after this experience because I realized I was ready. From a business perspective, one of the most interesting things while that was happening and for about a week afterwards: anyone would accept my phone call. My callbacks were instantaneous. My dial to answer fast. People were reaching out from everywhere. I was like, whoa, is this what it's like to be a celebrity? "I came back to Texas after the trip, ready to truly settle down and find a relationship and meet my now wife." Write like you talk: The best book about storytelling is Storyworthy by Matthew Dicks. Don't try to write a LinkedIn post that says "I'm happy to announce." Would you actually say that to someone? No, you wouldn't. Say it like you talk. Advice on Blind Introductions: Use a double opt-in intro. Reach out to one person first, "Hey, are you taking new clients before I connect you with a friend?" Get both parties' permission, separately - then send the email.  Give yourself a Free Day: Dan Sullivan suggests one free day a quarter from work. Make it a weekday, and even get a burner phone so you can't check your work text/emails, so you're completely disconnected from work.  The keys to being a great host/MC: Priya Parker does such a great job talking about the theory of being a good leader. The host that doesn't do a great job is the one who's too cool to care. Give explicit instructions to people. You are a ring leader for an event, and you're in charge of everyone's energy levels and keeping the show on the road.  Add value before taking value. Never send someone a message, "I'd love to pick your brain," or "I'm looking for a mentor." That is take, take, take. Think about how you can add value first. When you add value first to people, it's some sort of law of reciprocity. They're much more likely to want to help you out or do something in return. Advice for new grads in the AI era: AI and new tools are eating into the ability for companies to hire low-level employees that do grunt work. Learn how to use the tools themselves. Work with small businesses and entrepreneurs where you can make a difference. Develop a writing practice: Matthew Dicks has this activity called Homework for Life where every night you write down some note, some anecdote, something that stuck out for you. It gives you ideas about things to write about. Use AI as an editor, not a writer: Don't outsource your thinking to AI. Use the tools, understand how to use them, but don't outsource your thinking. It'll spit back something decent, but you don't want to outsource your thinking, especially as a leader. Reflection Questions Nick says your first party should be for neighbors, school parents, and LinkedIn connections you haven't seen in a while (not your most impressive contacts). Who are 15-20 people in your life that fall into this "comfortable but haven't connected recently" category that you could invite to a simple cocktail party?   He emphasizes "add value before you take value" and never says "I'd love to pick your brain." Think about someone you want to connect with. What's one specific way you could add value to them first before asking for anything in return?   Nick hosts events once a quarter to keep weak ties warm instead of trying to have individual coffee meetings with everyone. What's one relationship-building activity you're currently doing inefficiently that could be replaced with a group gathering? Additional Learning #663 - Priya Parker: The Art of Gathering #545: Will Guidara: Unreasonable Hospitality #430 - Matthew Dicks: Change Your Life Through The Power Of Storytelling Audio Timestamps 02:06 Icebreakers and Personal Stories 02:55 The Art of Hosting Events 08:27 Practical Tips for Successful Gatherings 20:16 Mastermind Events and Personal Websites 25:36 The Importance of a Personal Website 26:47 Crafting an Engaging Bio 29:27 The Viral Tokyo Trip 37:04 Living an Interesting Life 41:57 The Art of Hosting and MC'ing 44:50 Advice for New Graduates 46:35 The Power of Writing and Storytelling 49:07 EOPC

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Using AI and automation isn't just a trend—it's the secret to scaling your business without burning out. In this episode of Walk In Victory, host NaRon Tillman sits down with Dr. Bradford Carlton, business coach and automation expert, to reveal the blueprint for future-proofing your operations.Discover the critical difference between simple automation and true AI agents, and learn how to build an "Executive Assistant Suite" that runs your business for you. Whether you're a solopreneur or running a growing team, this conversation breaks down exactly how to reduce operational costs and reclaim your time. 

Get the Guide to AI Productivity here: https://fos.now/yt-gd-discover-guide-to-ai-productivityDo you want my help systematizing your business? Book a free call here: https://fos.now/yt-apply-558In this video, I break down the AI workflow that powers the core departments of my company. I show you how to unlock an extra 40% of productivity at each step so you can 10x the productivity of your team.You'll see how I use AI projects for Instagram carousels, viral tweets, YouTube scripts, lead magnets, email courses, operations, customer success, and more. This is how you build real leverage in 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-558Want to LEARN proven systems to grow your personal brand? Go here: https://fos.now/yt-newsletter-558Want to build the future with us? Apply to Founder OS here: www.founderos.com/careersConnect with me:Website: https://fos.now/yt-founder-os-558Twitter: https://twitter.com/matt_gray_LinkedIn: https://www.linkedin.com/in/mattgray1TikTok: https://www.tiktok.com/@realmattgrayInstagram: https://instagram.com/matthgray00:00 - Intro00:24 - The Prompts02:08 - Organize Your Systems05:28 - Building Your Project Knowledge09:34 - Projects Instructions + Memory Setup12:37 - Create Project For Every Format14:39 - Team Integration16:07 - Weekly Improvement#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.

“Use AI where it can make a difference to the organization and members.” - Shane ButcherThank you for tuning in to The CUInsight Network, with your host, Robbie Young, Vice President of Strategic Growth at CUInsight. In The CUInsight Network, we take a deeper dive with the thought leaders who support the credit union community. We discuss issues and challenges facing credit unions and identify best practices to learn and grow together.My guest on today's show is Shane Butcher, Chief Operating Officer / Chief Risk Officer at Optiri, a Trellance Company. Shane and I talk about how a teenage dream of becoming a fighter pilot turned into a career spanning the military, IT, operations, and ultimately the credit union space.In our conversation, Shane walks us through the evolution of Optiri and what it means to optimize, refresh, and innovate credit union technology without losing sight of the people whom it's supposed to serve. We talk about why credit unions have unique technology and security needs and how Opitiri focuses on doing the behind-the-scenes work so that credit unions can spend their energy on members.A big part of our conversation, though, is centered around AI as something already embedded in everyday tools. Shane breaks down what credit unions really should be thinking about right now—understanding where their data lives, tightening permissions, updating vendor policies, and choosing intentional use cases instead of chasing every new idea. We also break down how AI is reshaping cybersecurity on both sides, fueling more convincing attacks while also giving defenders faster, smarter ways to respond.As we wrap up the episode, Shane shares some lessons that he learned from a Navy mentor who led through calm problem-solving. He also talks about his love of good restaurants and unique experiences, why he loves Las Vegas, and has a book recommendation for us. Enjoy my conversation with Shane Butcher!

Melanie Smith, Head of Sales Development at Nooks, breaks down the exact systems, metrics, and coaching frameworks she uses to run one of the highest-performing SDR teams in outbound. In this episode, she shares KPI structures, call-block strategy, cold-call skill development, and how leaders can scale connect rates, conversation rates, and meeting production without burning out their reps.

You've probably heard it a thousand times: “Use AI or get left behind.” But if you're a course creator, that advice can feel like a trap, because the fastest way to “use AI” is also the fastest way to sound generic and lose your voice. In this episode, I sit down with Dan Cumberland, who helps founder-led brands scale with AI without losing their soul, and honestly, this conversation felt like a giant exhale. We dig into how to use AI in a way that keeps your content human, especially when it comes to marketing (the place most course creators get stuck). Dan shares a simple framework to help AI actually sound like you, plus practical examples of using AI inside your course experience to support students at a higher level, without turning your brand into “AI slop.” Watch the episode: https://youtu.be/inOBNS15RfQ Dan's Website: https://dancumberlandlabs.com/ Watch the Free Workshop: https://www.theonlinecourseguy.com/workshop Sign up for Jacques' Journal: https://www.theonlinecourseguy.com/Apply for Coaching: https://www.theonlinecourseguy.com/coachingFree Kajabi Course and 1 month Trial: http://everyclickkajabi.com/Free Skool Course and 14 day Trial: https://www.skool.com/refer?ref=c725cf8892fe42c8bb37dd7e5ffc2575Instagram: https://www.instagram.com/theonlinecourseguy/Threads: https://www.threads.net/@theonlinecourseguyX: https://twitter.com/onlinecourseguy

*This is a rerun of a previously released episode Geoff Woods is the #1 international bestselling author of The AI-Driven Leader: Harnessing AI to Make Faster Decisions and the founder of AI Leadership and the AI Driven Leadership Collective. As a former Chief Growth Officer of a global company, Geoff brings real-world expertise in using AI to transform how leaders think and make decisions. In this episode, he reveals how AI can serve as a powerful thought partner—enhancing strategic focus, overcoming operational overwhelm, and unlocking breakthrough solutions using his CRIT framework. Tune in to learn how the most effective leaders are leveraging AI to stay ahead in a rapidly evolving business landscape. Today we discussed: 00:00 Start 01:10 Introducing Geoff Woods 01:23 How AI Enhances Leaders Strategic Thinking 03:13 AI as a Thought Partner 04:50 How AI Can Help with Operation Tasks 06:20 Focusing on the 20% 07:56 The C.R.I.T. Framework 13:10 Addressing the AI Culture Shift 16:20 How is AI Changing Decision Making 17:39 What's AI's Role in Leadership 19:26 How to Start Integrating AI Into Your Leadership Practices This episode is brought to you by Duct Tape Marketing. Free Resource for Business Owners: If you're feeling overwhelmed by marketing, don't miss our CEO Sara Nay's new 30-minute workshop: The Clarity Engine. You'll learn a smarter, more strategic approach and get a worksheet to map out your next steps for 2026. Join the workshop & grab your free worksheet - https://dtm.world/clarity Give yourself the gift of clarity in 2026!  

In Episode 449 of the Immigration Lawyers Toolbox® Podcast, John Q. Khosravi, Esq. welcomes back Gianfranco De Girolamo, Esq. to discuss how AI, automation, and human-centered service are reshaping immigration law practice. They cover AI tools for admin and marketing, data centralization, prompt engineering, social media strategy, live video, and why human connection—not machines—will define successful firms in the years ahead. A must-listen for lawyers building future-ready practices. Spotify | iTunes | YouTube Music | YouTube Learn more about Gianfranco's marketing support service: https://nextlevellawyer.com/ Timestamps: 00:00 – Opening 00:33 – Introduction 02:00 – Will AI Replace Immigration Lawyers? 05:01 – The Right Way to Use AI 06:20 – AI for Managers & Leadership 07:36 – Understanding the Nature of AI 09:00 – Does AI Make You Less Intelligent? 10:44 – AI as a Single Source of Truth (Mistake to Avoid) 12:09 – Implementing AI Agents in Your Business 12:42 – The Master Prompt: How to Guide AI Effectively 13:53 – Mid-Episode Break 14:54 – Using AI for Social Media Scriptwriting 16:10 – How AI Multiplies Creativity 17:11 – How Social Media Algorithms Are Changing 18:34 – Why Going Live Still Matters 21:39 – The Impact & Advantages of Going Live 26:48 – AI's Global Impact: A World Wide Open 28:05 – Outro 28:18 – Final Closing Live Consular Processing training for lawyers Dec 18, 10:00–11:45 a.m. PT - NVC packets & DS-260 - Interview prep & follow-up - Timelines, fees, and real-world workflows Register here! Follow eimmigration by Cerenade: Facebook | Instagram | LinkedIn Start your Business Immigration Practice! (US LAWYERS ONLY - SCREENING REQUIRED): E-2 Course EB-1A Course Get the Toolbox Magazine!  Join our community (Lawyers Only) Get Started in Immigration Law! The Marriage/Family-Based Green Card course is for you Our Website: ImmigrationLawyersToolbox.com Not legal advice. Consult with an Attorney. Attorney Advertisement. #podcaster #Lawyer #ImmigrationLawyer #Interview #Immigration #ImmigrationAttorney #USImmigration #ImmigrationLaw #ImmigrationLawyersToolbox

Why Customer Success Can't Be Automated (And What AI Can Actually Do) In this special year-end episode of the FutureCraft GTM Podcast, hosts Ken Roden and Erin Mills sit down with Amanda Berger, Chief Customer Officer at Employ, to tackle the biggest question facing CS leaders in December 2026: What can AI actually do in customer success, and where do humans remain irreplaceable? Amanda brings 20+ years at the intersection of data and human decision-making—from AI-powered e-commerce personalization at Rich Relevance, to human-led security at HackerOne, to now implementing AI companions for recruiters. Her journey is a masterclass in understanding where the machine ends and the human begins. This conversation delivers hard truths about metrics, change management, and the future of CS roles—plus Amanda's controversial take that "if you don't use AI, AI will take your job." Unpacking the Human vs. Machine Balance in Customer Success Amanda returns with a reality check: AI doesn't understand business outcomes or motivation—humans do. She reveals how her career evolved from philosophy major studying "man versus machine" to implementing AI across radically different contexts (e-commerce, security, recruiting), giving her unique pattern recognition about what AI can genuinely do versus where it consistently fails. The Lagging Indicator Problem: Why NRR, churn, and NPS tell you what already happened (6 months ago) instead of what you can influence. Amanda makes the case for verified outcomes, leading indicators, and real-time CSAT at decision points. The 70% Rule for CS in Sales: Why most churn starts during implementation, not at renewal—and exactly when to bring CS into the deal to prevent it (technical win stage/vendor of choice). Segmentation ≠ Personalization: The jumpsuit story that proves AI is still just sophisticated bucketing, even with all the advances in 2026. True personalization requires understanding context, motivation, and individual goals. The Delegation Framework: Don't ask "what can AI do?" Ask "what parts of my job do I hate?" Delegate the tedious (formatting reports, repetitive emails, data analysis) so humans can focus on what makes them irreplaceable. Timestamps 00:00 - Introduction and AI Updates from Ken & Erin 01:28 - Welcoming Amanda Berger: From Philosophy to Customer Success 03:58 - The Man vs. Machine Question: Where AI Ends and Humans Begin 06:30 - The Jumpsuit Story: Why AI Personalization Is Still Segmentation 09:06 - Why NRR Is a Lagging Indicator (And What to Measure Instead) 12:20 - CSAT as the Most Underrated CS Metric 17:34 - The $4M Vulnerability: House Security Analogy for Attribution 21:15 - Bringing CS Into Sales at 70% Probability (The Non-Negotiable) 25:31 - Getting Customers to Actually Tell You Their Goals 28:21 - AI Companions at Employ: The Recruiting Reality Check 32:50 - The Delegation Mindset: What Parts of Your Job Do You Hate? 36:40 - Making the Case for Humans in an AI-First World 40:15 - The Framework: When to Use Digital vs. Human Touch 43:10 - The 8-Hour Workflow Reduced to 30 Minutes (Real ROI Examples) 45:30 - By 2027: The Hardest CX Role to Hire 47:49 - Lightning Round: Summarization, Implementation, Data Themes 51:09 - Wrap-Up and Key Takeaways Edited Transcript Introduction: Where Does the Machine End and Where Does the Human Begin? Erin Mills: Your career reads like a roadmap of enterprise AI evolution—from AI-powered e-commerce personalization at Rich Relevance, to human-powered collective intelligence at HackerOne, and now augmented recruiting at Employ. This doesn't feel random—it feels intentional. How has this journey shaped your philosophy on where AI belongs in customer experience? Amanda Berger: It goes back even further than that. I started my career in the late '90s in what was first called decision support, then business intelligence. All of this is really just data and how data helps humans make decisions. What's evolved through my career is how quickly we can access data and how spoon-fed those decisions are. Back then, you had to drill around looking for a needle in a haystack. Now, does that needle just pop out at you so you can make decisions based on it? I got bit by the data bug early on, realizing that information is abundant—and it becomes more abundant as the years go on. The way we access that information is the difference between making good business decisions and poor business decisions. In customer success, you realize it's really just about humans helping humans be successful. That convergence of "where's the data, where's the human" has been central to my career. The Jumpsuit Story: Why AI Personalization Is Still Just Segmentation Ken Roden: Back in 2019, you talked about being excited for AI to become truly personal—not segment-based. Flash forward to December 2026. How close are we to actual personalization? Amanda Berger: I don't think we're that close. I'll give you an example. A friend suggested I ask ChatGPT whether I should buy a jumpsuit. So I sent ChatGPT a picture and my measurements. I'm 5'2". ChatGPT's answer? "If you buy it, you should have it tailored." That's segmentation, not personalization. "You're short, so here's an answer for short people." Back in 2019, I was working on e-commerce personalization. If you searched for "black sweater" and I searched for "black sweater," we'd get different results—men's vs. women's. We called it personalization, but it was really segmentation. Fast forward to now. We have exponentially more data and better models, but we're still segmenting and calling it personalization. AI makes segmentation faster and more accessible, but it's still segmentation. Erin Mills: But did you get the jumpsuit? Amanda Berger: (laughs) No, I did not get the jumpsuit. But maybe I will. The Philosophy Degree That Predicted the Future Erin Mills: You started as a philosophy major taking "man versus machine" courses. What would your college self say? And did philosophy prepare you in ways a business degree wouldn't have? Amanda Berger: I actually love my philosophy degree because it really taught me to critically think about issues like this. I don't think I would have known back then that I was thinking about "where does the machine end and where does the human begin"—and that this was going to have so many applicable decision points throughout my career. What you're really learning in philosophy is logical thought process. If this happens, then this. And that's fundamentally the foundation for AI. "If you're short, you should get your outfit tailored." "If you have a customer with predictive churn indicators, you should contact that customer." It's enabling that logical thinking at scale. The Metrics That Actually Matter: Leading vs. Lagging Indicators Erin Mills: You've called NRR, churn rate, and NPS "lagging indicators." That's going to ruffle boardroom feathers. Make the case—what's broken, and what should we replace it with? Amanda Berger: By the time a customer churns or tells you they're gonna churn, it's too late. The best thing you can do is offer them a crazy discount. And when you're doing that, you've already kind of lost. What CS teams really need to be focused on is delivering value. If you deliver value—we all have so many competing things to do—if a SaaS tool is delivering value, you're probably not going to question it. If there's a question about value, then you start introducing lower price or competitors. And especially in enterprise, customers decide way, way before they tell you whether they're gonna pull the technology out. You usually miss the signs. So you've gotta look at leading indicators. What are the signs? And they're different everywhere I've gone. I've worked for companies where if there's a lot of engagement with support, that's a sign customers really care and are trying to make the technology work—it's a good sign, churn risk is low. Other companies I've worked at, when customers are heavily engaged with support, they're frustrated and it's not working—churn risk is high. You've got to do the work to figure out what those churn indicators are and how they factor into leading indicators: Are they achieving verified outcomes? Are they healthy? Are there early risk warnings? CSAT: The Most Underrated Metric Ken Roden: You're passionate about customer satisfaction as a score because it's granular and actionable. Can you share a time where CSAT drove a change and produced a measurable business result? Amanda Berger: I spent a lot of my career in security. And that's tough for attribution. In e-commerce, attribution is clear: Person saw recommendations, put them in cart, bought them. In hiring, their time-to-fill is faster—pretty clear. But in security, it's less clear. I love this example: We all live in houses, right? None of our houses got broken into last night. You don't go to work saying, "I had such a good night because my house didn't get broken into." You just expect that. And when your house didn't get broken into, you don't know what to attribute that to. Was it the locked doors? Alarm system? Dog? Safe neighborhood? That's true with security in general. You have to really think through attribution. Getting that feedback is really important. In surveys we've done, we've gotten actionable feedback. Somebody was able to detect a vulnerability, and we later realized it could have been tied to something that would have cost $4 million to settle. That's the kind of feedback you don't get without really digging around for it. And once you get that once, you're able to tie attribution to other things. Bringing CS Into the Sales Cycle: The 70% Rule Erin Mills: You're a religious believer in bringing CS into the sales cycle. When exactly do you insert CS, and how do you build trust without killing velocity? Amanda Berger: With bigger customers, I like to bring in somebody from CX when the deal is at the technical win stage or 70% probability—vendor of choice stage. Usually it's for one of two reasons: One: If CX is gonna have to scope and deliver, I really like CX to be involved. You should always be part of deciding what you're gonna be accountable to deliver. And I think so much churn actually starts to happen when an implementation goes south before anyone even gets off the ground. Two: In this world of technology, what really differentiates an experience is humans. A lot of our technology is kind of the same. Competitive differentiation is narrower and narrower. But the approach to the humans and the partnership—that really matters. And that can make the difference during a sales cycle. Sometimes I have to convince the sales team this is true. But typically, once I'm able to do that, they want it. Because it does make a big difference. Technology makes us successful, but humans do too. That's part of that balance between what's the machine and what is the human. The Art of Getting Customers to Articulate Their Goals Ken Roden: One challenge CS teams face is getting customers to articulate their goals. Do customers naturally say what they're looking to achieve, or do you have a process to pull it out? Amanda Berger: One challenge is that what a recruiter's goal is might be really different than what the CFO's goal is. Whose outcome is it? One reason you want to get involved during the sales cycle is because customers tell you what they're looking for then. It's very clear. And nothing frustrates a company more than "I told you that, and now you're asking me again? Why don't you just ask the person selling?" That's infuriating. Now, you always have legacy customers where a new CSM comes in and has to figure it out. Sometimes the person you're asking just wants to do their job more efficiently and can't necessarily tie it back to the bigger picture. That's where the art of triangulation and relationships comes in—asking leading discovery questions to understand: What is the business impact really? But if you can't do that as a CS leader, you probably won't be successful and won't retain customers for the long term. AI as Companion, Not Replacement: The Employ Philosophy Erin Mills: At Employ, you're implementing AI companions for recruiters. How do you think about when humans are irreplaceable versus when AI should step in? Amanda Berger: This is controversial because we're talking about hiring, and hiring is so close to people's hearts. That's why we really think about companions. I earnestly hope there's never a world where AI takes over hiring—that's scary. But AI can help companies and recruiters be more efficient. Job seekers are using AI. Recruiters tell me they're getting 200-500% more applicants than before because people are using AI to apply to multiple jobs quickly or modify their resumes. The only way recruiters can keep up is by using AI to sort through that and figure out best fits. So AI is a tool and a friend to that recruiter. But it can't take over the recruiter. The Delegation Framework: What Do You Hate Doing? Ken Roden: How do you position AI as companion rather than threat? Amanda Berger: There's definitely fear. Some is compliance-based—totally justifiable. There's also people worried about AI taking their jobs. I think if you don't use AI, AI is gonna take your job. If you use AI, it's probably not. I've always been a big fan of delegation. In every aspect of my life: If there's something I don't want to do, how can I delegate it? Professionally, I'm not very good at putting together beautiful PowerPoint presentations. I don't want to do it. But AI can do that for me now. Amazingly well. What I'm really bad at is figuring out bullets and formatting. AI does that. So I think about: What are the things I don't want to do? Usually we don't want to do the things we're not very good at or that are tedious. Use AI to do those things so you can focus on the things you're really good at. Maybe what I'm really good at is thinking strategically about engaging customers or articulating a message. I can think about that, but AI can build that PowerPoint. I don't have to think about "does my font match here?" Take the parts of your job that you don't like—sending the same email over and over, formatting things, thinking about icebreaker ideas—leverage AI for that so you can do those things that make you special and make you stand out. The people who can figure that out and leverage it the right way will be incredibly successful. Making the Case to Keep Humans in CS Ken Roden: Leaders face pressure from boards and investors to adopt AI more—potentially leading to roles being cut. How do you make the case for keeping humans as part of customer success? Amanda Berger: AI doesn't understand business outcomes and motivation. It just doesn't. Humans understand that. The key to relationships and outcomes is that understanding. The humanity is really important. At HackerOne, it was basically a human security company. There are millions of hackers who want to identify vulnerabilities before bad actors get to them. There are tons of layers of technology—AI-driven, huge stacks of security technology. And yet no matter what, there's always vulnerabilities that only a human can detect. You want full-stack security solutions—but you have to have that human solution on top of it, or you miss things. That's true with customer success too. There's great tooling that makes it easier to find that needle in the haystack. But once you find it, what do you do? That's where the magic comes in. That's where a human being needs to get involved. Customer success—it is called customer success because it's about success. It's not called customer retention. We do retain through driving success. AI can point out when a customer might not be successful or when there might be an indication of that. But it can't solve that and guide that customer to what they need to be doing to get outcomes that improve their business. What actually makes success is that human element. Without that, we would just be called customer retention. The Framework: When to Use Digital vs. Human Touch Erin Mills: We'd love to get your framework for AI-powered customer experience. How do you make those numbers real for a skeptical CFO? Amanda Berger: It's hard to talk about customer approach without thinking about customer segmentation. It's very different in enterprise versus a scaled model. I've dealt with a lot of scale in my last couple companies. I believe that the things we do to support that long tail—those digital customers—we need to do for all customers. Because while everybody wants human interaction, they don't always want it. Think about: As a person, where do I want to interact digitally with a machine? If it's a bot, I only want to interact with it until it stops giving me good answers. Then I want to say, "Stop, let me talk to an operator." If I can find a document or video that shows me how to do something quickly rather than talking to a human, it's human nature to want to do that. There are obvious limits. If I can change my flight on my phone app, I'm gonna do that rather than stand at a counter. Come back to thinking: As a human, what's the framework for where I need a human to get involved? Second, it's figuring out: How do I predict what's gonna happen with my customers? What are the right ways of looking and saying "this is a risk area"? Creating that framework. Once you've got that down, it's an evolution of combining: Where does the digital interaction start? Where does it stop? What am I looking for that's going to trigger a human interaction? Being able to figure that out and scale that—that's the thing everybody is trying to unlock. The 8-Hour Workflow Reduced to 30 Minutes Erin Mills: You've mentioned turning some workflows from an 8-hour task to 30 minutes. What roles absorbed the time dividend? What were rescoped? Amanda Berger: The roles with a lot of repetition and repetitive writing. AI is incredible when it comes to repetitive writing and templatization. A lot of times that's more in support or managed services functions. And coding—any role where you're coding, compiling code, or checking code. There's so much efficiency AI has already provided. I think less so on the traditional customer success management role. There's definitely efficiencies, but not that dramatic. Where I've seen it be really dramatic is in managed service examples where people are doing repetitive tasks—they have to churn out reports. It's made their jobs so much better. When they provide those services now, they can add so much more value. Rather than thinking about churning out reports, they're able to think about: What's the content in my reports? That's very beneficial for everyone. By 2027: The Hardest CX Role to Hire Erin Mills: Mad Libs time. By 2027, the hardest CX job to hire will be _______ because of _______. Amanda Berger: I think it's like these forward-deployed engineer types of roles. These subject matter experts. One challenge in CS for a while has been: What's the value of my customer success manager? Are they an expert? Or are they revenue-driven? Are they the retention person? There's been an evolution of maybe they need to be the expert. And what does that mean? There'll continue to be evolution on that. And that'll be the hardest role. That standard will be very, very hard. Lightning Round Ken Roden: What's one AI workflow go-to-market teams should try this week? Amanda Berger: Summarization. Put your notes in, get a summary, get the bullets. AI is incredible for that. Ken Roden: What's one role in go-to-market that's underusing AI right now? Amanda Berger: Implementation. Ken Roden: What's a non-obvious AI use case that's already working? Amanda Berger: Data-related. People are still scared to put data in and ask for themes. Putting in data and asking for input on what are the anomalies. Ken Roden: For the go-to-market leader who's not seeing value in AI—what should they start doing differently tomorrow? Amanda Berger: They should start having real conversations about why they're not seeing value. Take a more human-led, empathetic approach to: Why aren't they seeing it? Are they not seeing adoption, or not seeing results? I would guess it's adoption, and then it's drilling into the why. Ken Roden: If you could DM one thing to all go-to-market leaders, what would it be? Amanda Berger: Look at your leading indicators. Don't wait. Understand your customer, be empathetic, try to get results that matter to them. Key Takeaways The Human-AI Balance in Customer Success: AI doesn't understand business outcomes or motivation—humans do. The winning teams use AI to find patterns and predict risk, then deploy humans to understand why it matters and what strategic action to take. The Lagging Indicator Trap: By the time NRR, churn rate, or NPS move, customers decided 6 months ago. Focus on leading indicators you can actually influence: verified outcomes, engagement signals specific to your business, early risk warnings, and real-time CSAT at decision points. The 70% Rule: Bring CS into the sales cycle at the technical win stage (70% probability) for two reasons: (1) CS should scope what they'll be accountable to deliver, and (2) capturing customer goals early prevents the frustrating "I already told your sales rep" moment later. Segmentation ≠ Personalization: AI makes segmentation faster and cheaper, but true personalization requires understanding context, motivation, and individual circumstances. The jumpsuit story proves we're still just sophisticated bucketing, even with 2026's advanced models. The Delegation Framework: Don't ask "what can AI do?" Ask "what parts of my job do I hate?" Delegate the tedious (formatting, repetitive emails, data analysis) so humans can focus on strategy, relationships, and outcomes that only humans can drive. "If You Don't Use AI, AI Will Take Your Job": The people resisting AI out of fear are most at risk. The people using AI to handle drudgery and focusing on what makes them irreplaceable—strategic thinking, relationship-building, understanding nuanced goals—are the future leaders. Customer Success ≠ Customer Retention: The name matters. Your job isn't preventing churn through discounts and extensions. Your job is driving verified business outcomes that make customers want to stay because you're improving their business. Stay Connected To listen to the full episode and stay updated on future episodes, visit the FutureCraft GTM website. Connect with Amanda Berger: Connect with Amanda on LinkedIn Employ Disclaimer: This podcast is for informational and entertainment purposes only and should not be considered advice. The views and opinions expressed in this podcast are our own and do not represent those of any company or business we currently work for/with or have worked for/with in the past.

Send us a textThe 12 Days of Christmas series on Clipped continues with another practical tip to help creators work faster without losing their voice. Today is Day 4 of 12, and this episode focuses on using AI as a starting point—not a replacement for your thinking.AI tools are everywhere now, and most creators are already using them in some form. This episode explains how to use AI the right way: for outlines, drafts, research, and idea generation—while still keeping your personality, experience, and point of view front and center.

How are customer expectations evolving when people are talking less, trusting less, and switching brands faster than ever? In this episode, we break down the four major shifts reshaping customer experience in 2026 and why traditional listening tactics are failing right when companies need them most. Our guest is Isabelle Zdatny, Head of Thought Leadership at the Qualtrics XM Institute and co-creator of one of the largest global CX studies in the world. With data from 20,000 consumers across 14 countries, Isabelle reveals the surprising trends leaders cannot afford to overlook and why trust has become the real driver of customer behavior. Chapters 00:00:00 Meet Isabel Zdatny, Head of Thought Leadership at Qualtrics XM Institute 00:04:43 The Surprising State of Customer Experience Heading Into 2026 00:10:44 Why AI-Powered Customer Service Is Failing Customers 00:15:07 How to Use AI to Enhance Rather Than Replace Human Experience 00:19:41 The Silent Customer Crisis: Why Feedback Has Dropped to All-Time Lows 00:25:03 Conversational Surveys and Predictive Models: The Future of Customer Listening 00:34:55 Why Value Alone Won't Keep Customers Loyal in 2026 00:38:18 The Trust Equation: How Economic Uncertainty Changes Customer Behavior 00:42:51 The Personalization Paradox: Consumers Want It But Don't Trust It 00:54:10 What Will Surprise Us Most About 2026: Two Wildly Different Predictions

Dr. Karen Sutherland is a multi-award winning educator and author from the University of the Sunshine Coast in Australia. As a Certified AI Consultant and Director of Dharana Digital Marketing Agency, Dr. Sutherland specializes in using AI for strategic marketing and communication. In addition to designing and delivering training and workshops globally for over a decade, her research spans AI in strategic communication, B2B relationships, social media pedagogy and practice. She has authored two editions of her book 'Strategic Social Media Management – Theory and Practice' Palgrave Macmillan, downloaded more than 170k times, 'Transmedia Brand Storytelling - Immersive Experiences from Theory to Practice' Palgrave Macmillan, and 'Public Relations and Strategic Communication', Oxford University Press. Her latest book, '⁠Artificial Intelligence for Strategic Communication⁠,' , Palgrave Macmillan, has been adopted across 20+ countries. Dr. Sutherland has featured in global media including  the Wall Street Journal, Euro News AAP, ABC, Nine, Sky News and has been Ticker's AI and social media expert for the past five years. 

In this episode, we're joined by Youssef Hounat, product leader, ex-auditor, and (unexpectedly) freestyle-rap-ready builder of tools for accountants. He went from training at Ernst & Young to helping scale DataSnipper into one of the Netherlands' unicorns, and now he's building again as Head of Product at ComplianceWise. We unpack what's actually changing inside product teams: AI stops being a rewrite/search tool and becomes a teammate that takes real work off your plate. Youssef shares how the best teams reduce context switching, turn customer research into a habit, and use agentic workflows + MCPs to connect tools like email, Jira, Figma, and docs without becoming a “fleshy meat puppet” copy-pasting between 10 tabs. Here are some of the key questions we address: Why do 99% of teams still use AI wrong, and what mindset shift fixes it? How do you turn customer research into a continuous habit using transcripts + automated pipelines? What's a real example of AI helping product push back on “build this to close the deal” and finding the true request underneath? How do top teams use MCP + coding agents to move from idea → PRD → Jira tickets without leaving the terminal? What's the difference between a prototype you build to learn vs a product you build to earn — and why vibe-coded output can't go straight to production? How do you avoid reinventing the wheel and start with small weekly automations that compound? What's the real risk behind shadow AI usage  and how do you get IT onside instead of blocked?

Host Susan Diaz sits down with her business buddy and go-to-market consultant Suzanne Huber to talk about what AI has actually changed in marketing. Together they explore AI as "robot arms" (an extension of expertise), why first-draft AI content gets a bad rap, how modern marketers use AI for research, planning, editing, and proposals, and why thought leadership and personal brand matter more than ever. Episode summary Susan and Suzanne have been talking about AI since 2022. In this episode, they make it official. Suzanne introduces a metaphor that sticks: AI as "robot arms". You're still the driver. AI can extend your reach, speed up the grunt work, and help you close expertise gaps—but it still needs human judgment, critical thinking, and craft. They compare marketing before vs after AI: headlines, research, applying feedback, simplifying complex plans into executive-friendly formats, cross-checking sources (especially Canadian vs US), and building repeatable workflows with custom GPTs. They also tackle the bigger questions: Does expertise still matter? Is personal brand becoming more important in the age of AI? What should writers do if they feel threatened? Spoiler: AI can speed up output. But insight, values, differentiation, and taste are still the human edge.   Key takeaways AI is "robot arms" not a replacement brain. It's an extension of expertise. You still need to steer, evaluate quality, and avoid publishing raw first drafts that can damage trust. First-draft AI is the content factory problem. AI-assisted content gets a bad reputation when junior-level or high-volume systems publish credible-sounding fluff with no real subject matter expertise behind it. Craftsmanship still matters. Marketing got faster because the grunt work collapsed. Headlines, rewrites, reformatting, applying feedback, outlining, and turning long documents into charts/tables can happen in minutes - not hours. You still refine, but you're starting from a better baseline. Research and fact-checking changed dramatically. Instead of trawling search results for hours (and getting US-default sources), AI tools can surface targeted sources fast - then humans choose what's credible and relevant. Custom GPTs shine for repeatable processes. Susan shares how she uses custom GPTs (including MyShowrunner.com) for guest research, interview questions, emails, and packaged deep research briefs - turning recurring work into reusable systems. Expertise always matters - especially for positioning and thought leadership. Differentiation, values, hot takes, and human intuition are what attract the right people (and repel the wrong ones). AI can assist, but it can't replace lived POV. Personal brand matters more in the age of AI. As audiences get more suspicious of generic content and AI avatars, trust increasingly attaches to real humans with visible ideas, proof, and consistency. For writers who feel threatened: use it or get outpaced. AI can accelerate production for factual formats (press releases, timely content). Writers who combine craft + AI + fast learning become the force multipliers. But journaling/introspective writing still belongs to the human-only zone. Episode highlights [01:29] Suzanne's "robot arms" metaphor: AI as an extension of expertise. [02:47] Why first-draft AI should never leave your desk. [03:56] The telltale signs of lazy AI writing (and why it gets a bad rap). [05:00] Before vs after AI: the research + writing process changes. [07:24] Simplifying complex work: plans → tables → charts for execs. [09:10] Deep research for Canadian sources without wasting hours. [10:25] Custom GPT workflows (MyShowrunner + research briefs). [12:29] Where expertise still matters in an AI-saturated world. [16:56] Personal brand: attracting the right people + repelling the wrong ones. [20:00] AI for proposals and even pricing guidance. [22:00] Advice for writers who feel threatened by AI. If you've been resisting AI because you're worried it will erase your craft, try this reframing: Use AI for the grunt work. Keep the human parts for the parts that build trust: taste, judgement, voice, and values. And if you want a simple starting point, ask yourself: What could use "robot arms" in your marketing workflow this week - headlines, research, rewrites, proposals, or planning? 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.   Connect with Suzanne Huber on LinkedIn.   

Send us a textAre you scaling the wrong thing... successfully?If your 2025 planning feels heavy, misaligned, or nonexistent — it's not because you're lazy. It's because you're still using a corporate operating system for a boutique business. In this episode, Dawn Andrews drops the velvet boot of truth to show you why most female founders sabotage their year-end planning and how AI can help you get radically honest, strategic, and aligned.Download The Feedback Fix — because planning means nothing if your team can't run with the ball. Get the free guide to giving feedback that actually lands and drives accountability. Key TakeawaysStop planning like you have a CFO — Your three-person team doesn't need quarterly OKRs and a content calendar that takes 30 people to execute.AI is your honesty coach — Use it to uncover revenue patterns, energy drains, and strategic misalignment.Only 3 things matter: What made money, did you enjoy it, and did it make a difference?Decisions create constraints — It's not about setting goals, it's about choosing what you'll stop, amplify, and build.Your dream business won't come from a LinkedIn-optimized strategy. It comes from truth, clarity, and alignment.Resources & Links:Freebie: The Feedback FixJoin the Community: AI for Founders Free GroupRelated Episodes:110 | 3 Custom GPTs That Save Female Founders 16 Hours a Week102 | 3 SOPs Every Founder Should Build in 30 Minutes (Using AI)Want to increase revenue and impact? Listen to “She's That Founder” for insights on business strategy and female leadership to scale your business. Each episode offers advice on effective communication, team building, and management. Learn to master routines and systems to boost productivity and prevent burnout. Our delegation tips and business consulting will advance your executive leadership skills and presence.

NOTE: This was recorded in late October 2025AI is already inside the tools you use. Waiting it out is no longer an option.In this episode, I speak with Karen Sutherland, author of Artificial Intelligence for Strategic Communication, who, at the time of the recording, was fresh from a Marketing AI Conference in the US.We cut through the noise and talk about how PR and comms teams are actually using AI day to day, what works, what breaks, and where people are getting it wrong.This is not about replacing people or chasing shiny tools. It is about saving time on the work you hate, protecting quality, and building skills your team will still need in five years.If you run an agency or work in-house and feel stuck between curiosity and fear around AI, this episode gives you a clear place to start.We coverWhy AI agents change how work gets done, not just how fastThe real risk for junior staff and how to avoid hollow skillsHow teams are using custom GPTs to speed up reporting without sounding genericA simple framework for integrating AI safely and sensibly into comms workMap your tasks before touching tools. Start with repetitive work that drains time, not creative judgment.Use AI as a first draft assistant, then edit like a professional. Quality control becomes a real job, not an afterthought.Train AI on your own writing and reports so outputs sound like you, not the internet.Regularly check whether AI is saving time and protecting standards, not just pushing content out faster.DescriptionPractical takeawaysGUESTKaren Sutherland - Senior Lecturer, Public Relations, University of the Sunshine CoastLOCATION: Sunshine Coast, AustraliaBook: Artificial Intelligence for Strategic Communication by Karen E. SutherlandNEW TO PR?- Check out the new podcast 'Getting A Job In PR' - https://gettingajobinpr.comSUBSCRIBE- Video and Audio links here - https://thepublicrelationspodcast.com/listen/Or search for "The Public Relations Podcast" on all good podcast appsCONNECT WITH ME- LinkedIn - https://www.linkedin.com/in/richard-midson/- Website and newsletter - https://thepublicrelationspodcast.com/- 'Getting A Job In PR' - https://gettingajobinpr.comFUTURE GUESTS- Check out: https://thepublicrelationspodcast.com/one-sheet/

Most indoor playground and play café owners don't need more ideas going into a new year — they need better execution on the ones they already have.In this episode, I break down exactly how I'm using AI right now to help my indoor playground business owner clients review numbers, tighten systems, and remove the operational friction that quietly drains time and profit.This isn't about trends or tech overwhelm. It's a step-by-step, practical walkthrough of how I recommend using AI as an analyst, operations assistant, and planning tool so you can head into 2026 with clearer priorities, stronger systems, and far less on your plate.BLOG for this episode05:00–11:00 Strategy 1: Revenue analysis to find 2026 opportunities11:00–15:10 Strategy 2: Fix party systems before busy season15:10–17:10 Strategy 3: SOPs that don't depend on the owner17:10–19:00 Strategy 4: Floor-plan-based cleaning and safety19:00–23:10 Strategy 5: Prevent membership churn with AI23:10–25:35 Strategy 6: Pricing and add-on cleanup25:35–27:55 Strategy 7: Customer message scripts and decision trees27:55–29:50 Strategy 8: Policies and incident reporting systems29:50–31:40 Strategy 9: Repurpose marketing content fast31:40–34:15 Strategy 10: Website clarity, conversion, and SEO34:15–38:35 Strategy 11: Partner and sponsor generation for 2026OTHER RESOURCES:Play Cafe Academy & Play Makers SocietyGetting Started With Your Play Cafe [YouTube Video Playlist]What's Working In The Indoor Play Industry 2025 GuideFund Your Indoor Play Business [Free Training]Indoor Play Courses & 1:1 Consulting WaitlistMichele's InstagramMichele's WebsitePlay Cafe Academy YouTube ChannelETSY Template ShopPrepare Your Indoor Playground For a RecessionPlay Cafe Academy & Play Makers SocietyQuestions and Support: Support@michelecaruana.com Play Cafe Academy & Play Makers Society: http://bit.ly/3HES7fDQuestions and Support: Support@michelecaruana.com Simplify and Scale with 50% OFF WellnessLiving: https://discover.wellnessliving.com/playcafeacademyActive Campaign Free Trial: https://www.activecampaign.com/?_r=D6IYK3HG

About Jason Hreha:Jason Hreha is a behavioral scientist and entrepreneur specializing in applying behavioral science to solve business challenges. After studying neuroscience at Stanford and conducting research in BJ Fogg's Persuasive Technology Lab, Jason has spent 15 years developing Behavioral Strategy, a methodical approach for turning research into actionable business solutions. As Global Head of Behavioral Science at Walmart, he established and led the company's first behavioral science team, and he also founded Dopamine and co-founded Kite.io, later acquired by Quixey. As CEO of Persona, Jason transforms talent assessment through research-backed psychometric tools that predict employee performance and fit, and his book Real Change challenges conventional approaches to habits through science-based frameworks. Jason's work has been cited in Atomic Habits and featured in Inc.com, Knowledge at Wharton, and BigThink, and he continues to advise organizations on applying behavioral science for innovation and growth. In this episode, Dean Newlund and Jason Hreha discuss:Understanding how core personality traits drive leadership effectivenessExploring why emotional stability underpins real emotional intelligenceExamining the limits of adult personality change and what that means for teamsRecognizing how interpersonal friction often comes from mismatched stylesConsidering how AI models express measurable personalities that shape user behavior Key Takeaways:Identify your own trait profile using a validated Big Five assessment so you can play the leadership “hand” you actually have instead of chasing traits you do not possess.Reduce conflict by assuming others cannot easily change their styles and instead adapt your expectations so collaboration becomes easier and less personal.Strengthen your culture by clarifying norms, incentives, and strategic consistency so the environment aligns behavior without needing personality change.Use AI tools more effectively by understanding their default personality traits and adjusting your prompts or model choice to complement—not mirror—your own tendencies. "It's hard to be emotionally intelligent if you're angry or upset or annoyed or freaked out.” — Jason Hreha Connect with Jason Hreha:  Website: https://www.personatalent.com/Blog: https://www.thebehavioralscientist.com/Book: https://www.amazon.com/stores/author/B0CVCZ2VR9YouTube: https://www.youtube.com/@thebehavioralscientistLinkedIn: https://www.linkedin.com/in/hreha/ & https://www.linkedin.com/company/personatalent/X (Twitter): https://x.com/jhreha & https://x.com/PersonaTalentFacebook: https://www.facebook.com/choosepersona/Instagram: https://instagram.com/the.behavioral.scientist   See Dean's TedTalk “Why Business Needs Intuition” here: https://www.youtube.com/watch?v=EEq9IYvgV7I Connect with Dean:YouTube: https://www.youtube.com/channel/UCgqRK8GC8jBIFYPmECUCMkwWebsite: https://www.mfileadership.com/The Mission Statement E-Newsletter: https://www.mfileadership.com/blog/LinkedIn: https://www.linkedin.com/in/deannewlund/X (Twitter): https://twitter.com/deannewlundFacebook: https://www.facebook.com/MissionFacilitators/Email: dean.newlund@mfileadership.comPhone: 1-800-926-7370 Audio production by Turnkey Podcast Productions. You're the expert. Your podcast will prove it.

AI isn't coming to the car business.It's already here, and it's influencing who customers buy from before your team ever speaks to them.In this episode of The Get More Frank Podcast, I bring you Episode 20 of Follow The Money, featuring Amie Lindaas, Director of Research & Insights at Cars.com. We break down brand-new consumer research that reveals how car shoppers are actually using AI tools like ChatGPT, Gemini, and marketplace AI during the vehicle buying process.This is not a theory episode. This is data, behavior, and reality.Here's what the research confirms.Nearly every car shopper is aware of AI. The majority have already used it. Almost half are actively using AI while shopping for a car. And 97 percent of AI users say it influenced the vehicle they ultimately purchased. That means opinions are being formed earlier, preferences are being shaped faster, and tolerance for friction is lower than ever.We unpack how shoppers are using AI to compare vehicles, research pricing, locate inventory, and narrow down choices long before they ever submit a lead or walk into a dealership. We also dig into where AI stops being trusted and where human interaction still matters most, especially around trade-ins, financing, negotiation, and final purchase decisions.This episode matters if you care about car sales, dealership marketing, lead quality, reputation, customer trust, and staying relevant in modern automotive retail.We also tackle the biggest misconception dealers have about AI. AI is not replacing salespeople. It's replacing outdated thinking, inconsistent data, and weak messaging. Dealers who align their inventory, pricing, and online presence with what AI-powered shoppers are seeing will win. Dealers who ignore it will lose customers before those customers ever show up in their CRM.I'm Frank J. Lopes, President of Strong30 Automotive, where we help dealerships grow through smarter marketing, advertising, sales strategy, and training. This podcast exists for one reason: to give dealers, managers, and sales professionals the truth about what's really driving results in the car business.If you want to understand how buying decisions are being made today, not how they were made five years ago, this episode is required listening.Because in today's car business, perception is shaped before the first conversation.And if you want to win, you have to understand where that perception comes from.It's time to Follow The Money.

Software is still eating the world, and AI is speeding up the clock. In this episode, Amir talks with Tariq Shaukat, co CEO at Sonar, about what it really takes for non tech companies to build like software companies, without breaking trust, security, or quality. Tariq shares how leaders can treat AI like a serious capability, not a shiny add on, and why clean code, governance, and smart pricing models are becoming board level topics. Key Takeaways• “Every company is a software company” does not mean selling SaaS, it means software is now core to differentiation, even in legacy industries. • The hardest shift is not tools, it is mindset: moving from slow, capital style planning to fast iteration, test, learn, and ship. • AI works best when leaders stay educated and involved, outsourcing the whole strategy is a real risk. • “Trust but verify” needs to be a default posture, especially for code generation, security, and compliance. • Pricing will keep moving toward value aligned consumption models, not simple per seat formulas. Timestamped Highlights• 00:56 What Sonar does, and why clean code is really about security, reliability, and maintainability • 05:36 The Tesla lesson: mechanics commoditize, software becomes the experience people buy • 09:11 Culture plus education: why software capability cannot live in one silo • 14:21 Cutting through AI hype with program discipline and a “trust but verify” mindset • 18:23 Boards, governance, and setting an “acceptable use” policy for AI before something goes wrong • 25:18 How software pricing changes in an AI world, and why Sonar prices by lines of code analyzed A line worth saving:“Define acceptable risk as opposed to no risk.” Pro Tips you can steal• Write down what you want AI to achieve, the steps to get there, and the metric you will use to verify outcomes. • For code generation, scan and review before shipping, treat AI output like a draft, not a final answer.• Set clear rules for what is allowed with AI inside the company, then iterate as you learn. Call to ActionIf you want more conversations like this on software leadership, AI governance, and building real impact, follow The Tech Trek and subscribe on your favorite podcast app. If someone on your team is wrestling with AI rollout or developer productivity, share this episode with them.

UNLOCK THE 13 SYSTEMS EVERY AGENCY OWNER NEEDS TO REACH 8 FIGURES:https://bit.ly/41Sm05NIn this episode, Jordan Ross sits down with Todd Taskey to unpack what really drives the value of a digital marketing agency when it's time to sell. They explore how AI, tech enablement, and recurring revenue models are reshaping business valuations and exit strategies. Todd breaks down the financial levers like EBITDA, buyer types, and strategic acquisitions that can dramatically affect an agency's sale price. Whether you're preparing for a near-term exit or planning long-term growth, this episode offers a roadmap to positioning your agency for maximum value in a rapidly evolving market.ChaptersIntroduction to Business ValuationMarket Trends and Valuation MultiplesThe Impact of AI on Agency ValuationStrategic Acquisitions and Market PositioningRevenue and Retention as Key MetricsNavigating the Future of Agency GrowthThe Role of Strategic BuyersConclusion and ResourcesTo learn more go to 8figureagency.coTo reach out to Todd go to www.towerpartners.comTo listen to Todd go to SecondBitePodcast.com

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

Kara Tsuboi covers today's top stories. CNET editors recommend top gifts for a smarter home. Artificial intelligence is shaping the way consumers buy gifts this holiday season. Best tech toys to give your kids.

AI permeates K-12 education, but the rush to adopt new tools often bypasses critical questions about equity, bias, and human connection. On this episode of Trending in Education, host Mike Palmer sits down with Stephanie Smith Budhai and Marie K. Heath, co-authors of the new book Critical AI in K-12 Classrooms: A Practical Guide for Cultivating Justice and Joy. Together, they dismantle the "myth of inevitability" surrounding EdTech and explore how educators can reclaim agency in the face of rapid technological change with AI. From the historical resistance of Sojourner Truth to the concept of the classroom as a "Home Place," the conversation offers a refreshing, techno-skeptical framework that prioritizes student flourishing over big tech's framing. Key Takeaways: Reframing the Narrative: Why "Justice and Joy" must remain central to education, ensuring schools are spaces of affirmation rather than just sites of data extraction. The "Home Place" Concept: How bell hooks' notion of a "Home Place" helps teachers create safe harbors where students can critically interrogate harmful AI outputs and resist standardized bias. Sojourner Truth as Metaphor: A look at how Sojourner Truth co-opted and subverted the cartes de visites photography of her day to fund abolition—and how modern students and educators can similarly "sell the shadow to support the substance". Pedagogies of Resistance: An overview of culturally sustaining, fugitive, and abolitionist pedagogies that equip teachers to challenge oppressive structures within AI and educational technology. The Four Ps of Action: Practical steps for moving forward through Personal, Professional, Pedagogical, and Participatory action. Why You Should Listen: This conversation moves beyond the basic "how-to" of generative AI tools. Instead, it tackles the moral and ethical dimensions of bringing powerful, often biased technologies into the classroom. If you are an educator, administrator, or parent looking for a way to navigate the AI hype with your values intact, this episode provides the historical context and practical strategies needed to foster true digital agency. Like, Share, and Follow wherever you get your podcasts to stay ahead of the curve on the future of learning. Visit us at TrendinginEd.com for more. Time Stamps: [00:00] Intro: Criticality in the Age of AI [01:58] Stephanie's Origin Story: From Nursing to EdTech [04:58] Marie's Origin Story: Reluctant Teacher to Critical Scholar [09:25] Writing the Book: Centering Justice in Tech [11:20] Why Justice and Joy Matter [16:00] Bell Hooks and the Classroom as "Home Place" [20:30] Confronting AI Bias: The "High School Boy" Example [23:00] Sojourner Truth and Co-opting Biased Tech [29:00] The Myth of Inevitability: Do We Have to Use AI? [33:00] Culturally Sustaining, Fugitive, and Abolitionist Pedagogies [41:40] The 4 Ps: Taking Action Towards Just AI [44:00] Conclusion

When dealer principal Joe Shaker of Shaker Auto Group started digging into customer feedback, he uncovered a hard truth: even loyal, satisfied customers still felt uncertainty about what was happening behind the service doors. That insight sparked the creation of TruVideo, now one of the most widely used communication platforms in automotive.In this episode, Joe walks through the journey — the early “aha” moments, the data that changed everything, the role of AI, and how video has redefined transparency in the modern dealership. He and Kaylee break down why doubt persists, how clear communication transforms revenue and retention, and what dealers can do right now to close trust gaps and elevate the customer experience.If you're ready to build real transparency, automate stronger processes, and modernize how your parts and service teams communicate, this episode is your roadmap.--------------------------------------------This show is powered by PartsEdge: Your go-to solution for transforming dealership parts inventory into a powerhouse of profitability. Our strategies are proven to amp up parts sales by a whopping 20%, all while cutting down on idle inventory. If you're looking to optimize your parts management, visit

In this episode, Nathan and Cameron dive deep into one of the most pressing theological questions facing today's church: What happens when worship, sermons, and spiritual formation collide with AI and morally complicated creators? Using provocative thought experiments—like whether Christians would eat fruit from a tree planted by an immoral person—they explore how believers should think about AI-generated worship music, sermons, artistic integrity, and the character of those who shape our spiritual lives. From EDM and emotional engineering to pastoral authenticity, formation, and the “food sacrificed to idols” dilemma, Nathan and Cameron offer rich, intellectually serious Christian commentary on how technology is reshaping worship and the future of the church. Perfect for Christians hungry for deep theology, cultural discernment, and thoughtful engagement with current events.DONATE LINK: https://toltogether.com/donate BOOK A SPEAKER: https://toltogether.com/book-a-speakerJOIN TOL CONNECT: https://toltogether.com/tol-connect TOL Connect is an online forum where TOL listeners can continue the conversation begun on the podcast.

Send us a textJanuary goals fade fast.Let's build a Q1 Game Plan you'll actually execute—with help from AI and one powerful 90-day sprint structure.By February, most goals are already forgotten. Want to be the exception? This episode shows you how to map your Q1 goal to weekly actions in 10 minutes using AI.In Day 12 of 12 Days of AI Quick Wins, Dawn reveals how to use AI to design a Q1 plan that doesn't collect digital dust. With one simple prompt, you'll go from vague intentions to a milestone-driven, week-by-week plan that lives in your calendar—not your imagination. It's how visionary founders actually get things done without burning out or getting stuck in “someday” land.Your Day 12 Action:Pick ONE Q1 goal that would make the next 90 days feel like a win.Run the Q1 planning prompt in today's episode.Map out your January. Add it to your calendar. Then review it every week.Key Takeaways:Set ONE clear Q1 goal. No more wish lists—focus fuels execution.Use the Q1 AI Planning Prompt to turn that goal into milestones, weekly actions, and priority filters.Build from January first. If it's not in your calendar, it's not happening.Tie your Q1 goal to your Weekly CEO Reset (Day 11) for consistent review and momentum.AI helps you plan smarter, faster, and with less decision fatigue.Resources & Links:Register FREE for the Day 13 Live AI Implementation PartyRelated Episodes:Day 1: Stop Overthinking ChatGPT: Free vs. $20—Which One Actually Matters for FoundersDay 2: The 3 AI Prompts Every Female Founder Needs in Her PhoneDay 3: Why ChatGPT Sounds Like a Robot (And the One Sentence That Fixes It)Day 4: AI Email Triage: End Inbox Overwhelm in 5 MinutesDay 5: The 5-Minute Meeting Prep AI Hack That Makes You Look Totally PreparedDay 6: Stop Rewriting Everything AI Writes: The 10-Minute Voice Training for FoundersDay 7: Overwhelmed? Brain Dump to AI and Get an Actual Plan (5 Minutes)DAY 8: Stop Rewriting the Same Emails: Build Your AI Template Library (15 Minutes)DAY 9: Stop Explaining the Same Thing: Create SOPs While You Work (AI + 10 Minutes)DAY 10: Stuck on a Big Decision? Use AI to Get Unstuck (3-Question Framework)DAY 11: Plan Your Week Like a CEO: Want to increase revenue and impact? Listen to “She's That Founder” for insights on business strategy and female leadership to scale your business. Each episode offers advice on effective communication, team building, and management. Learn to master routines and systems to boost productivity and prevent burnout. Our delegation tips and business consulting will advance your executive leadership skills and presence.

Banks today have a great number of customer experience pain points. There's the trust factor to consider, on whether customers feel their bank actually care about them and their financial struggles. But there's also the fact that customers expect a seamless experience across multiple channels, whether that's in the branch, mobile or at the branch.In today's episode of the Bank Customer Experience podcast, Brian McEvoy, chief retail banking officer at Webster Five, joined Bradley Cooper to discuss how banks can navigate these customer pain points.He said during the podcast that "people process technology in unison." In other words, the various platforms have to work together. It's not enough to have a fancy mobile app that doesn't integrate well with your other bank platforms or doesn't integrate with third party apps.McEvoy added that the hardest part for banks is: "How do you make a frictionless experience for the customer?" This is a particularly big problem as customers have far less patience for any frustration in the experience."If there's any pain point in the experience, our tolerance and patience is less than it used to be."So how do banks address this? McEvoy pointed to a few important elements:Refocus branches to have a custom experience for guests.Use AI to automate simpler tasks.Use a mobile-first strategy to ensure all your bank's features are accessible.During the discussion, McEvoy addressed several subtopics such as:Identifying pain points.Making a good branch experience.Keeping the personal touch while also using AI.Listen to the full discussion above.

With so many ways to make money online, many founders and creators have lost sight of the most powerful one: email marketing. John Ainsworth, founder of Data Driven Marketing, says you're leaving tons of money on the table if you're not doing it well. John is back on the pod to share his best tips and tactics on landing pages, upsells, lead magnets, and more. You might want to take some notes for this one! LINKS Rolodex Marketing Resource (https://docs.google.com/document/d/1jRV_ncgCWAMRB7tZZtnO7x0Tn5sE46-tYkwN6paVG3A/edit?tab=t.0) Free Email Marketing Resources (https://datadrivenmarketing.co/resources/) John's Podcast: The Art of Selling Online Courses (https://www.youtube.com/@john_ainsworth/videos) Meet John and other location-independent founders inside Dynamite Circle (https://dynamitecircle.com/) Hang out exclusively with 7+ figure founders (https://dynamitecircle.com/dc-black) Get 2 months of Perspective AI FREE with promo code TMBA (https://getperspective.ai/tmba) Share your thoughts about the podcast (https://getperspective.ai/interview/tmba-feedback) [takes 2 minutes] 22 FREE business resources for location-independent entrepreneurs (https://tropicalmba.com/resources) CHAPTERS (00:02:11) Email Marketing: A Must-Have Money Maker (00:11:50) 15 Steps to a High-Converting Landing Page (00:19:18) Do Webinars Still Work in 2026? (00:24:09) What Makes a Great Lead Magnet (00:29:09) The Power of Order Bumps and Upsells (00:36:58) How to Use AI to Improve Your Funnels (00:40:45) How to Make Extra Money with Trip Wires (00:44:37) Rapid-Fire Email Tips for 2026 (00:50:49) How John is Running His 7-Figure Agency CONNECT: Dan@tropicalmba.com Ian@tropicalmba.com Past guests on TMBA include Cal Newport, David Heinemeier Hannson, Seth Godin, Ricardo Semler, Noah Kagan, Rob Walling, Jay Clouse, Einar Vollset, Sam Dogan, Gino Wickam, James Clear, Jodie Cook, Mark Webster, Steph Smith, Taylor Pearson, Justin Tan, Matt Gartland, Ayman Al-Abdullah, Lucy Bella. PLAYLIST: Marketing to High-Dollar Clients (https://tropicalmba.com/episodes/marketing-to-high-dollar-clients) 6-Figure Sales Expert Calls You Out (Don't Keep Doing This in 2026) (https://tropicalmba.com/episodes/dont-keep-doing-this-2026) 8 Simple Steps for Improving Your Sales Funnel (https://tropicalmba.com/episodes/john-ainsworth-sales-funnel)

(Presented by ThreatLocker (https://threatlocker.com/threebuddyproblem): Allow what you need. Block everything else by default, including ransomware and rogue code.) Three Buddy Problem - Episode 76: On the show this week, Costin walks through how a single Romanian documentary kick-started nationwide protests, exposing how corruption can be perfectly legal when the law itself is gamed, and why this moment feels different, darker, and more consequential than past flare-ups. Plus, news on the React-to-Shell exploitation wave overwhelming the internet, why patching is structurally hard, and how APTs and criminals are converging on the same fragile dependency chain. Along the way, they take aim at Microsoft's shrinking transparency, the limits of vendor trust, and what it really means when defenders are told (again) to just patch and pray. Cast: Juan Andres Guerrero-Saade (https://twitter.com/juanandres_gs), Ryan Naraine (https://twitter.com/ryanaraine) and Costin Raiu (https://twitter.com/craiu).

Send us a textYou've got a full calendar and zero clarity. Here's how to flip the script in just 10 minutes using AI.If your week starts in panic-scroll mode and ends in “what did I even do?” mode—this one's for you. Let's build your Weekly CEO Reset and take back control.In Day 11 of 12 Days of AI Quick Wins, Dawn walks you through the Weekly CEO Reset—a 10-minute AI ritual to help you prioritize, plan, and protect your time. Instead of letting the week run you, this simple framework helps you brain-dump everything, sort by impact, and schedule what actually matters. Perfect for Sunday nights, Monday mornings, or any time you feel the chaos creeping in.Your Day 11 Action:Right now, open your calendar and block 10 minutes for your Weekly CEO Reset.Use the AI prompt in today's episode, and let the week start with clarity—not catch-up.Key Takeaways:This is planning, not doing. You need strategy time to stay out of reactive mode.Use the AI Weekly Reset Prompt to categorize your tasks into Must Do, Should Do, Want to Do, and Worried About.AI turns your chaos into a clear plan—top 3 priorities, realistic workload, and overcomplication flags.Your calendar = your power. Schedule your priorities like they matter—because they do.End the week smarter. Review Friday to learn, adjust, and grow.Resources & Links:Get the full 12 Days of AI Quick Wins Toolkit – just $7Register FREE for the Day 13 Live AI Implementation Party – win a 90-minute Strategy IntensiveRelated Episodes:Day 1: Stop Overthinking ChatGPT: Free vs. $20—Which One Actually Matters for FoundersDay 2: The 3 AI Prompts Every Female Founder Needs in Her PhoneDay 3: Why ChatGPT Sounds Like a Robot (And the One Sentence That Fixes It)Day 4: AI Email Triage: End Inbox Overwhelm in 5 MinutesDay 5: The 5-Minute Meeting Prep AI Hack That Makes You Look Totally PreparedDay 6: Stop Rewriting Everything AI Writes: The 10-Minute Voice Training for FoundersDay 7: Overwhelmed? Brain Dump to AI and Get an Actual Plan (5 Minutes)DAY 8: Stop Rewriting the Same Emails: Build Your AI Template Library (15 Minutes)DAY 9: Stop Explaining the Same Thing: Create SOPs While You Work (AI + 10 Minutes)DAY 10: Stuck on a Big Decision? Use AI to Get Unstuck (3-QWant to increase revenue and impact? Listen to “She's That Founder” for insights on business strategy and female leadership to scale your business. Each episode offers advice on effective communication, team building, and management. Learn to master routines and systems to boost productivity and prevent burnout. Our delegation tips and business consulting will advance your executive leadership skills and presence.

Tired of hearing about how AI is going to change your job? We sure are... That's exactly why the way we think about AI in relation to our work needs to be reshuffled. This week, Jim is eager to share one of his latest reads, which helps us reframe how we think about AI.

AI is everywhere—but how do you use it to create content that's more human, more you, and not generic junk?In this episode, I (Kim Rittberg—award-winning marketer & former media exec) break down how to use ChatGPT and other AI tools to craft content that connects. You'll learn my SAG Formula to filter and refine AI-generated ideas so they sound like you, reflect what you believe, and steer clear of sounding like every other post out there.

AI is everywhere—but how do you use it to create content that's more human, more you, and not generic junk?In this episode, I (Kim Rittberg—award-winning marketer & former media exec) break down how to use ChatGPT and other AI tools to craft content that connects. You'll learn my SAG Formula to filter and refine AI-generated ideas so they sound like you, reflect what you believe, and steer clear of sounding like every other post out there.

SaaStr 832: How to Use AI to Hyper-Customize Go-To-Market at Scale with SaaStr's CEO and Chief AI Officer In this episode from SaaStr AI London 2025,  SaaStr CEO and Founder Jason Lemkin and SaaStr's Chief AI Officer, Amelia Lerutte discuss the implementation and optimization of AI SDRs within various business contexts. They focus on key AI agents used for sales processes, data aggregation, and the customization of outbound and inbound messages. Real-world results, like increased email response rates, are highlighted along with practical steps for setting up and training AI SDRs. They also offer advice on selecting the right vendors, the importance of human oversight, and leveraging AI to improve qualification and customer interactions. Key takeaways include how AI can handle more interactions consistently and efficiently and the role of AI in augmenting human sales capabilities.  --------------------- This episode is Sponsored in part by HappyFox: Imagine having AI agents for every support task — one that triages tickets, another that catches duplicates, one that spots churn risks. That'd be pretty amazing, right? HappyFox just made it real with Autopilot. These pre-built AI agents deploy in about 60 seconds and run for as low as 2 cents per successful action. All of it sits inside the HappyFox omnichannel, AI-first support stack — Chatbot, Copilot, and Autopilot working as one. Check them out at happyfox.com/saastr  --------------------- Hey everybody, the biggest B2B + AI event of the year will be back - SaaStr AI in the SF Bay Area, aka the SaaStr Annual, will be back in May 2026.  With 68% VP-level and above, 36% CEOs and founders and a growing 25% AI-first professional, this is the very best of the best S-tier attendees and decision makers that come to SaaStr each year.   But here's the reality, folks: the longer you wait, the higher ticket prices can get. Early bird tickets are available now, but once they're gone, you'll pay hundreds more so don't wait.  Lock in your spot today by going to podcast.saastrannual.com to get my exclusive discount SaaStr AI SF 2026. We'll see you there.

-AI chatbots haven't come close to replacing teens' social media habits, but they are playing a significant role in their online habits. Nearly one-third of US teens report using AI chatbots daily or more, according to a new report from Pew Research. -It looks like Meta has decided to turn Instagram users into unwitting SEO spam pawns. On Tuesday, 404 Media reported that the platform is generating sensational, likely AI-generated headlines and descriptions for user posts without their knowledge or explicit consent. -Pebble just announced the Index 01, a smart ring for recording thoughts. It's a little ring with a built-in microphone and that's about it. The Index 01 is almost anti-tech in its simplicity. It's available for pre-order now. Learn more about your ad choices. Visit podcastchoices.com/adchoices

While teenagers may start out using AI chatbots for basic questions, their relationship with chatbot platforms has the potential to turn addictive. Plus, Anysphere CEO Michael Truell explained the features his company is focused on building out after reaching $1 billion in annualized revenue,. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Can you build an art career without social media? How helpful is AI, actually? Jake Parker, Lee White, and Anthony Wheeler discuss why human connections still outweigh algorithms and how you can use them to your advantage. 3 Point Perspective Podcast is sponsored by SVSLearn.com, the place where becoming a great illustrator starts!Click here for this episode's links and show notes.

As podcast guests, showing up unprepared, overly scripted, or simply repeating yourself in every podcast interview can quickly lead to burnout and a lack of results. But, there's a quick way to ensure you're always uniquely prepared for every podcast interview! In this episode, Mike Montague explains how to utilize AI to help with preparation and positioning for upcoming interviews. Get ready to tailor your message uniquely for every host and their audiences in a way that gets you remembered!MORE FROM THIS EPISODE: HTTPS://PODMATCH.COM/EP/361Chapters00:00 Harnessing AI for Podcast Preparation02:53 Crafting Your Podcast Persona05:45 Sharpening Your Talking Points09:04 Connecting Through StorytellingTakeawaysAI can help you show up sharper and more relevant.Great guests package their ideas well for hosts.Context builds trust, and AI can give you that context.Be interesting and memorable, not just prepared.AI can be the best brainstorming partner you've ever had.Use AI to save time in your prep and promotion.Know the show, know the host, and know the audience.Don't let AI make you sound more robotic.Treat AI like a coach, not a crutch.Find fresh stories and personal insights with AI.MORE FROM THIS EPISODE: HTTPS://PODMATCH.COM/EP/361

Stories can increase revenue by 376%, but only if you do them right. In one study, scientists proved that adding a fictional story to a cheap spoon on eBay increased its final selling price by 64%. They found the same result with wine, art, and charitable donations (Those used real stories though. They call it the "Rokia" Effect). Stories don't change the product. They change the value of the product in the customer's mind. But it can be hard to come up with them because we think they have to be about us, our amazing accomplishments, or our lives. THEY DON'T. In this video, I break down: The "Value Inflation" Data: Why stories mathematically increase conversion rates by 30%+. The Revenue Spike: Why a specific type of story can lead to 376% more revenue per customer. The Anti-Personal Brand: How to use stories without ever being the "main character." The Danger Of AI: Why purely AI-generated stories usually cause a 62% DROP in trust (and how to fix it). My Story-Based Workflow: How I use AI (Ojoy) for "Deep Research" and structuring—so I can deploy this strategy without staring at a blank page, making stuff up, or being too boring. It's a cool little system: Use AI to find the story, so the story can sell the product for you.

Send us a textTired of Explaining the Same Thing Twice? Turn It Into an SOP—in 10 MinutesYou keep saying, “I should really write this down.” But let's be honest—you won't. Here's how to document as you do—no extra time required.If you're the only one who knows how to do it, you're the bottleneck. Let's fix that in 10 minutes—without ever “sitting down to document.”In Day 9 of 12 Days of AI Quick Wins, Dawn teaches you how to turn any repeatable task into a team-ready SOP—while you're doing it. Whether it's onboarding clients, prepping for sales calls, or giving feedback, this method lets you narrate the process in real-time while AI formats it into a clean, usable doc. Say goodbye to “I'll document it later”—and hello to delegation that actually works.Your Day 9 Action:Next time you catch yourself explaining something (again), open ChatGPT and narrate it instead.Use the SOP prompt to generate a clear, usable doc.Save it, share it, and start reclaiming your time—one process at a time.Key Takeaways:Repeat = delegate-ready. If you've explained something more than twice, it's SOP-worthy.Narrate while you work. Open ChatGPT, talk through the process like a cooking show host.Use the SOP Prompt: AI turns your messy monologue into numbered steps, tools, and timing.You don't write it—AI does. You just talk, scan, and save.Put it where your team lives. Not buried in folders—make it accessible and actionable.Resources & Links:Get the full 12 Days of AI Quick Wins Toolkit – just $7Register FREE for the Day 13 Live AI Implementation Party – win a 90-minute Strategy IntensiveRelated Episodes:Day 1: Stop Overthinking ChatGPT: Free vs. $20—Which One Actually Matters for FoundersDay 2: The 3 AI Prompts Every Female Founder Needs in Her PhoneDay 3: Why ChatGPT Sounds Like a Robot (And the One Sentence That Fixes It)Day 4: AI Email Triage: End Inbox Overwhelm in 5 MinutesDay 5: The 5-Minute Meeting Prep AI Hack That Makes You Look Totally PreparedDay 6: Stop Rewriting Everything AI Writes: The 10-Minute Voice Training for FoundersDay 7: Overwhelmed? Brain Dump to AI and Get an Actual Plan (5 Minutes)DAY 8: Stop Rewriting the Same Emails: Build Your AI Template Library (15 Minutes)Want to increase revenue and impact? Listen to “She's That Founder” for insights on business strategy and female leadership to scale your business. Each episode offers advice on effective communication, team building, and management. Learn to master routines and systems to boost productivity and prevent burnout. Our delegation tips and business consulting will advance your executive leadership skills and presence.

Payer algorithms now drive denials, audits, and prior authorization decisions before a human ever reviews the case. This episode breaks down how automated payer models impact hospital revenue—and what leaders must do to strengthen oversight, governance, and defensibility.Brought to you by www.infinx.com

AI 시대 외국어를 왜 배워야 할 지 함께 생각해봅시다 :) 이번 에피소드에서는 전직 통번역사이자 현직 뉴욕 교사인 소피(Sophie)가 바라본 'AI 시대의 언어 학습'에 대해 이야기합니다.변화된 환경: 텍스트 생성 AI와 함께하는 콘텐츠 창작의 명과 암사라진 직업: 자동 번역 기술의 발전과 통번역 시장의 변화핵심 질문: 기술적 편의성(전동 휠체어)과 인간의 주체적 노력(걷기) 사이의 균형결론: 우리가 기계에 의존하지 않고 스스로 사고하고 언어를 구사해야 하는 진정한 이유#코리안뉴요커 #AI시대 #영어공부 #외국어학습 #교육에세이 #뉴욕생활 #번역기 #챗GPT #인문학 #동기부여AI의 발전 속에서 인간의 역할에 대해 고민하는 분들께 추천합니다.

In this episode, Dan Uyemura of PushPress returns to discuss the future of fitness technology with host Eric Malzone. They dive into PushPress's evolution into an AI-powered gym management platform, exploring how artificial intelligence is reshaping operations for independent, community-focused gyms. Dan shares real-world examples of AI in action—from automated member management and smart reporting to AI coaching assistants that personalize member experiences. The conversation also tackles the bigger picture: why AI adoption is essential for survival in today's fast-moving tech landscape, how gyms can leverage AI as a team member rather than a job replacer, and why the fitness industry remains uniquely human and resilient in the face of automation. Whether you're a gym owner, coach, or tech enthusiast, this episode offers a practical and forward-looking view of how AI can empower small businesses to thrive.

How I Use AI in My Law Firm. If you want more profit in your law firm with less chaos, grab my Law Firm Profit Playbook - https://bigbirdaccounting.com/playbook.

In this episode, we break down Meta's move to centralize Facebook and Instagram support while testing a new AI support assistant. We also explore the reported plan to slash its Metaverse budget by up to 30% and what this signals for the company's shifting priorities.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/aihustle---------See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Things get real (and a little funny) as Steven Jack Butala and Jill DeWit dive into how to actually use AI in your land business today—without letting it script your entire life. In this Back to the Basics episode of The Land Academy Show, they break down why certain deals should never make it past your desk, especially those buried in steep HOA fees and niche communities. Learn how a single Discord post stirred up a valuable conversation on avoiding costly mistakes, filtering your mailers like a pro, and using AI as a smart, practical tool (not your business brain). Bonus: Some candid banter and lessons on what won't change in your relationship—no matter how advanced AI gets.

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

Imagine having your own world-class registered dietitian designing every meal to fit your lifestyle, help you lose fat, and maintain lean muscle without spending a cent. In this episode, Chalene explains how to use AI as your personal nutrition coach to create a fully customized calorie deficit plan that actually works. She walks you step by step through how to use ChatGPT to calculate your macros, design meals you will love, and fine tune your plan when progress slows. If you have ever thought it would be easy to lose weight if someone just told you exactly what to eat, this episode will show you how to make that happen. Watch this episode on YouTube this Sunday!!  https://www.youtube.com/@chalenejohnson/videos