PROMPT This

Episode Summary Season One has come to an end and the Prompt This team is taking a well-deserved break after 32 episodes in 32 weeks, dozens of operators, and hours of conversations about AI.  In this season finale, Clint and Greg step back and ask a simple question. What actually changed? The answer is not what you expect. They started this podcast thinking AI might reshape work someday. What they found is that it already has. Quietly, unevenly, and in ways most people are still missing. In this episode, they unpack the moments that changed their minds. Where they got it wrong early. Where the hype collapsed. And where the real signal showed up. You will hear why the idea of AI fully replacing jobs does not hold up in practice, but also why that does not mean your job is safe. You will hear what is actually working inside companies right now, and why most teams are still stuck talking about tools instead of getting results. There is also a shift they did not expect. The advantage is no longer going to the people who discovered AI first. It is going to the ones who quietly built it into how they work every day. This episode draws a line between curiosity and execution. Between people experimenting with AI and people using it to win. If you have been circling AI, watching from the sidelines, or telling yourself you will get to it later, this conversation will challenge that thinking. Season One was about figuring out what AI is. This episode makes it clear what happens next. Chapter Breakdown  00:00 – Opening and Season Finale Setup Clint and Greg frame this as a different kind of episode and reflect on finishing their first season. 01:07 – What It Took to Build Season One A look at the scale of the journey and how far they have come from the early days. 02:07 – The Shift from Curiosity to Real Usage How AI moved from a side experiment to part of everyday work. 03:33 – Why First Movers No Longer Have the Edge The playing field is leveling, but not for the reason most people think. 04:18 – Where AI Actually Delivers Value A grounded discussion on real use cases versus hype. 05:20 – The Moment That Changed Clint’s Thinking A sharp insight on ownership, credibility, and how to talk about AI. 07:17 – The Job Debate Revisited The hosts challenge their original stance and unpack what is really happening. 09:28 – The Three Big Takeaways from the Season What matters now and what does not. 11:11 – Tools vs Execution Why access to AI tools is no longer the differentiator. 11:39 – Closing the Season A direct message to listeners and a reflection on the journey. 12:23 – What to Expect in Season Two A shift from talking about AI to showing how to use it. 12:44 – Outro Wrapping Season One and setting up what comes next.

Guest Introduction Jason Rushforth is a seasoned Chief Revenue Officer and career sales operator who has built and scaled high-performing go-to-market teams across multiple organizations. He brings a sharp, field-tested perspective on how deals actually get done, where sales processes break, and how to fix them. More recently, Jason has been hands-on with AI in sales and marketing workflows, separating what delivers real impact from what just looks good in a demo.    Episode Summary  This episode cuts straight through the noise around AI in sales. Jason brings a CRO-level lens to a market flooded with promises. The core message is simple but often ignored. AI only matters if it solves a real problem. Everything else is just marketing. The conversation moves fast across three realities. First, most “AI-powered” tools are just repackaged SaaS with a thin layer of automation. Second, when AI works, it compresses weeks of work into minutes and changes how teams operate. Third, the real advantage comes from how operators use AI, not the tool itself. You will hear where AI is already delivering value today. Territory planning that used to take weeks now happens in minutes. Qualification gets sharper in real time. Pipeline generation becomes proactive instead of reactive. You will also hear where things break. Forecasting still struggles. Pricing models are unclear. And the gap between demo and reality is still wide. The through line is practical. Start with the problem. Test in small pilots. Use AI to guide decisions, but do not let it replace judgment. If you are responsible for revenue, this episode gives you a clear starting point and a filter for what actually matters. AI Challenge Call-to-Action  This week’s AI Challenge focuses on one simple idea: stop chasing AI tools and start solving real problems. Pick one friction point in your sales or marketing workflow. Then use AI to test a targeted solution through a small pilot. No big rollout. No long-term commitment. Just proof. Get the full breakdown, step-by-step instructions, and tools here: https://www.promptthis.ai/blog/how-to-select-ai-business-solutions-the-right-way  Chapter Breakdown  00:00 – Intro to Jason Rushforth Clint sets the stage with Jason’s background and why his perspective on AI is grounded in real-world revenue operations. 01:00 – Sales Operators Take Over Greg and Jason lean into their CRO roots while Clint jokes about getting pushed out of the funnel. 02:30 – AI Hype vs Reality Jason explains why most AI claims fall apart and how to evaluate whether a tool solves a real problem. 04:00 – How to Spot Fake AI Fast A practical framework for identifying tools that are just legacy SaaS with AI branding. 05:40 – Biggest AI Miss and Biggest Win A failed forecasting tool vs a standout territory management solution that compresses weeks into minutes. 08:30 – Why Simple Problems Win The best AI solutions are often the least flashy but solve real operational pain. 10:00 – “Beat the Machine” Mindset Using AI as guidance, not gospel, and why top performers outperform the model. 11:00 – AI for Sales Reps Using tools like ChatGPT for objection handling and confidence building in live deals. 12:00 – AI-Driven Qualification How AI prompts reps in real time to ask better questions and capture data automatically. 14:30 – Pipeline Still Rules Everything “Pipeline saves lives” and how AI can prioritize the right prospects at the right time. 16:00 – AI for Daily Sales Execution Tools that tell reps exactly who to contact and why, turning signals into action. 17:00 – AI in Inbound and BDR Workflows How AI is starting to automate lead routing and early-stage engagement. 18:30 – The SaaS vs AI Shift Jason’s take on the so-called SaaS disruption and where traditional companies still win. 21:00 – Why Product Alone Is Not Enough Clint pushes on the idea that companies are more than features, highlighting infrastructure and trust. 23:30 – The Pricing Problem Seat-based SaaS vs usage-based AI and why CFOs struggle with unpredictability. 27:00 – Where to Start with AI Jason’s playbook: identify problems first, then find solutions that directly address them. 29:00 – The Three Areas to Focus On Rep productivity, territory management, and better visibility into pipeline and forecasting. 31:00 – Start Small and Pilot Why testing before buying is the safest way to adopt AI without breaking your business. 32:00 – Closing Thoughts and Where to Find Jason Jason shares how to connect and encourages ongoing dialogue as the AI landscape evolves.

Guest Introductions Time for something a little different and have some fun. This episode brings back the ten most recent Prompt This guests and turns them into "Rapid Fire Smackdown" competitors. You get a mix of CEOs, operators, analysts, and AI builders including Erik Archer Smith, Emily Maxie, Julie Trelstad, Ken Roden, Warren Kucker, Brooks Bush, Bruce Daley, Joshus Gould, Dr. Shelli Hendricks, and Martin Schneider. Clint and Greg draft from this pool and go head to head. No long interviews. Just their best answers, put under pressure. Two teams with very excited captains. Five questions about AI realities. One AI judge.  Lots of fun.  Episode Summary This episode is fast, competitive, and a bit unpredictable. Clint comes in as the defending champion. Greg comes in prepared and looking to steal the belt. They draft teams from past guests and run five rapid fire questions that cut straight to what matters in AI right now. No theory. No polished talking points. Just real answers from people doing the work. What makes this one worth your time is how quickly the noise drops away. You hear what experienced operators actually think is overhyped. Where real competitive advantage is showing up. What they refuse to trust AI with. And where leaders are still getting it wrong. Some answers are practical. Some are blunt. A few are uncomfortable. And when ChatGPT is forced to pick winners, it exposes something even more interesting. AI does not always judge the way you expect. The momentum swings. The arguments tighten. And by the final round, it comes down to a single idea that cuts to the core of how AI should be used in business. You will have your own opinion on who won. Chapter Breakdown with Timestamps 00:00 – The Smackdown Returns A high-energy opening sets up a more competitive, more confident round two. 01:13 – Draft Day Clint and Greg build their teams from the last ten guests. Strategy starts early. 05:09 – Round 1: What’s Overhyped about AIStrong takes on where AI is already breaking down in the real world. 07:01 – Round 2: Where AI Advantage Is Coming From Speed versus specialization. Two very different paths to winning with AI. 09:07 – Round 3: What Task You’d Never Trust AI With Accountability shows up fast. Some lines people will not cross. 12:00 – Round 4: One AI Tool to Roll Out Everywhere A tactical answer collides with a more strategic one. This round shifts momentum. 14:18 – Round 5: The Biggest Misconception about AIThis is the one that matters. The answers get sharper and more opinionated. 17:00 – Final Decision ChatGPT makes the call. You may or may not agree, but one of the hosts is thrilled to take home the Rapid Fire Smackdown belt. 18:00 – Closing Thoughts A quick reflection on what these answers reveal about where AI actually stands today.  

Guest Joshua Gould is the Group CEO of thebigword, one of the world’s largest language services and multilingual technology companies. His organization supports governments, healthcare systems, and global enterprises where accuracy is critical and mistakes carry real consequences. He has spent decades at the intersection of language, technology, and global business. While he has long believed AI will transform translation, he is clear that it will not eliminate the need for humans. Instead, it will reshape how global companies operate and compete.   Joshua also hosts the Exec Craft channel on YouTube for CEOs and senior leaders looking to hone their business leadership skills.  https://www.youtube.com/@Exec_Craft AI Challenge Call-to-Action This week’s AI Challenge pushes you past basic translation. Most companies think going global with AI is as simple as translating a website. It’s not. The real challenge is operating in another language, not just writing in one. Try the challenge and learn how to translate your business, not just your words. 👉 Read the full challenge: https://www.promptthis.ai/blog/how-to-translate-your-business-not-just-your-words 👉 Share your results: https://www.promptthis.ai/contact   Episode Summary AI makes global business look easy. Translate your website, translate your pitch, and suddenly you are international. That is the story most people want to believe. This conversation breaks that idea apart. Josh Gould explains that translation is only a small piece of the problem. Culture, laws, customer expectations, and support all sit underneath the surface. You can translate everything perfectly and still fail the moment a customer asks a question you cannot answer. The discussion goes deeper into what is really happening in AI right now. There is a gap between what gets demoed and what actually works inside a business. Many tools look impressive, but when they hit real workflows, humans are still doing most of the work. At the same time, AI is creating massive opportunity. Demand for content and communication is exploding, and companies that use AI correctly can scale faster than ever. But there is a catch. AI does not fix broken processes. It amplifies them. The episode also explores what this means for jobs, hiring, and skills. Some roles are being replaced, but others are becoming more valuable. The advantage is shifting to people who know how to work with AI, not compete against it. The takeaway is clear. AI is powerful, but it is not magic. The companies that win will be the ones that focus on real problems, build strong workflows, and use AI as a tool, not a shortcut.    Chapter Breakdown 00:00 – Intro: Cutting through AI hype Clint and Greg set up the episode with a focus on what is real versus what is overhyped in AI. 02:00 – Meet Joshua Gould Background on The Big Word and the stakes of translation in global business. 03:00 – Does AI make global business easy? Debate on translation versus real-world complexity like culture and operations. 05:00 – Why translation alone is not enough Customer support, logistics, and product differences create real friction. 07:00 – How AI transformed the translation industry Lower costs led to massive demand growth instead of shrinking the market. 11:00 – AI interpretation and real-time language The shift from written translation to live spoken language powered by AI. 13:00 – Demo vs reality in AI adoption Why many companies sell AI features that customers do not actually use. 14:30 – The risk of AI inside broken workflows AI accelerates outcomes, good or bad. 18:30 – AI inside operations and call centers Automation, culture, and resistance inside real organizations. 21:00 – Where to start with AI in your business Focus on outcomes, clean data, and real problems before adding AI. 24:00 – Why orchestration beats picking one AI tool The case for using multiple AI systems instead of locking into one. 26:30 – Jobs: replaced or created? AI reduces some roles while increasing demand for others, especially in sales and strategy. 29:00 – Rethinking education and training Why apprenticeships may matter more than traditional degrees in an AI world. 32:00 – Tools Josh actually uses A practical look at AI tools in both business and personal workflows. 34:00 – AI Challenge: Translate your business Go beyond words and rethink how your company operates globally. 35:30 – Closing thoughts and where to find Josh Final insights and how to continue the conversation.

Guest Introduction Erik Archer Smith is a veteran marketing leader with nearly two decades of experience scaling enterprise SaaS companies from early traction to more than $150 million in annual recurring revenue. Over his career he has led demand generation, account-based marketing, brand, and growth teams at companies including CommerceIQ, Treasure Data, Arena, and Scale Venture Partners.    Today he is exploring a different path. Archer is building his passion project.  It is a direct-to-consumer AI product called ABCMe.ai which is an app that creates custom coloring books designed to help young kids practice early reading and writing skills. The idea started as a parenting hack and turned into a real company with a real product powered by AI.    Episode Summary Archer spent nearly two decades scaling enterprise SaaS companies. Then one afternoon he used ChatGPT to create a coloring page for his five-year-old son. That small moment turned into something much bigger. In this episode, he explains how that experiment became an AI-powered product and why many B2B marketing instincts translate surprisingly well into building a consumer business. But he also discovered something very different. In B2B you nurture prospects. In consumer products you often get a single shot. One click has to convert.  This imperative has taken his marketing skills to a whole next level. Archer also shares how he actually works with AI day to day, including a simple technique where he has different models challenge each other to pressure test ideas. The conversation ends with a candid discussion about AI and jobs, and why the real shift may be the rise of the “super operator,” someone who can orchestrate AI systems to do what once required an entire team. AI Challenge The Screen-Free AI Hour AI is usually marketed as a way to spend more time on screens. More dashboards. More tabs. More notifications. But what if AI could actually help you spend less time on screens? Inspired by Eric Archer Smith’s experience building ABCMe.ai, this week’s AI Challenge explores how AI can help structure activities that pull you away from devices instead of deeper into them. The challenge tests three simple ideas: Replace one kid screen moment with a printable AI-generated activity Let AI plan a short walk, then put the phone away Run a one-hour work block that requires no computer It’s a simple experiment that flips the usual AI narrative. Instead of AI consuming your attention, it helps create space for real-world moments. Read the full challenge and prompts here:   https://www.promptthis.ai/blog/how-to-use-ai-to-create-a-screen-free-hour  Chapter Breakdown 00:00 – Intro to Eric Archer Smith Greg introduces Archer and his background scaling SaaS companies and leading marketing teams. 02:00 – B2B marketing roots Archer explains how he got started building products and why he chose to learn go-to-market skills. 04:30 – The parenting moment that sparked ABCMe.ai A simple ChatGPT prompt for his son leads to the idea for personalized AI coloring books. 08:30 – From SaaS marketer to solo builder How Archer used AI tools to quickly build and launch a new product. 10:00 – What transfers from B2B to D2C Market analysis, positioning, and content strategy still work the same. 11:30 – The biggest difference: one-click conversion Consumer products often have a single chance to convert a customer. 14:00 – Archer’s real AI workflow Using multiple LLMs to challenge each other and improve thinking. 18:00 – Hidden technical breakthroughs How AI helped solve a non-obvious product architecture problem. 19:30 – Will AI replace jobs? Archer says yes, especially for junior roles and repetitive tasks. 22:30 – The rise of the “super operator” AI enables individuals to orchestrate work that previously required teams. 25:30 – Decision fatigue in the AI era Faster iteration means more decisions and more responsibility. 26:30 – Favorite AI tools right now Lovable, Vercel, Cursor, Replicate, and other tools Archer uses. 28:30 – Advice for professionals getting started with AI Use AI for content creation, personal writing assistants, and quick experimentation. 31:00 – Build something this weekend Archer’s final advice: start building and learn by doing.

Episode Summary AI is changing how knowledge work gets done, but it is not replacing experts the way many people fear. In this episode, Clint and Greg talk with longtime software analyst Bruce Daley about what really happens when experienced professionals start using AI tools in their daily work. Bruce began experimenting with large language models because he believed AI might eventually replace analysts. Instead, he discovered something more interesting. Analysts who learn to use AI gain a major advantage over those who do not. The conversation also digs into the mechanics of building an AI product. Bruce shares lessons from launching Analyst Copilot, including why token costs matter more than most founders expect and why curated data is the key to avoiding hallucinations. Finally, the episode closes with a practical takeaway. If you are early in your career or looking to stay competitive, learning how to design effective prompts may become one of the most valuable skills you can develop. Guest Introduction Bruce Daley is a longtime software industry analyst who has spent decades studying how major technology shifts reshape the enterprise software market. Over the course of his career, he has covered hundreds of technology companies and has been quoted in outlets such as The Wall Street Journal and the Financial Times. Bruce started his career as a software developer in the early days of enterprise computing before moving into industry analysis, where he spent years helping investors and business leaders understand how technology markets evolve. Recently, he made a major career shift. Instead of only analyzing the AI wave, he decided to build in it. Bruce is now the founder of Analysts Copilot, an AI-driven platform designed to help analysts, investors, and business leaders track and understand large sets of companies using large language models. Join Bruce for a live demo of Analysts Copilot when he is a guest on Carter Lusher's Tool Talk podcast on March 12, 2026.https://www.linkedin.com/posts/carterlusher_archat-analystrelations-artooltalk-activity-7436406958565404672-BmHv/  AI Challenge: Prompt Engineering Taste Test This week’s AI Challenge is designed to show just how much prompt design affects the quality of AI output. Take a simple question like:      “Explain the CRM market.” And then run it through an AI tool three different ways. First, use a basic prompt. Second, add structure. Specify tone, format, and constraints. Third, create an expert prompt that defines a role, audience, and desired output. Same model. Same question. But the answers will be dramatically different. That experiment will show you why prompt engineering is quickly becoming one of the most valuable skills in the AI era. You can find the full instructions here: https://www.promptthis.ai/blog/how-to-test-out-prompt-engineering  And if you want to share your results or your own AI experiments, reach out to us at: https://www.promptthis.ai/contact  Chapter Breakdown 00:00 – The AI hype problem The show opens with the mission of Prompt This: cutting through AI hype and focusing on real business applications. 01:11 – Introducing Bruce Daley Clint and Greg introduce Bruce and explain how he moved from software analyst to AI founder. 03:17 – Can AI replace analysts? Bruce shares why he initially tested AI to see if it could replace him and what he discovered instead. 04:56 – Using AI to track hundreds of companies How Bruce used large language models to scale his research coverage from dozens to hundreds of companies. 06:45 – What AI cannot replace in the analyst role Industry relationships, informal information networks, and professional judgment remain uniquely human advantages. 09:11 – Why AI improves research quality AI handles first drafts and repetitive work, giving analysts more time to refine insights and perspective. 09:23 – Comparing AI to past tech waves Bruce compares the AI moment to the rise of the PC and the internet. 11:09 – Build versus buy in the AI era Why infrastructure and developer tools come first, followed by applications that solve real business problems. 14:17 – Understanding tokens and AI cost models Bruce explains how token usage affects cost and why model selection matters. 15:07 – Lessons from building Analyst Copilot Early mistakes, unexpected token bills, and why cost discipline matters when building LLM products. 16:02 – The importance of data quality Why curated data is the best defense against hallucinations. 18:00 – The rise of prompt engineering Bruce explains why prompt engineering could become a major career skill. 18:49 – Real-world use cases for Analyst Copilot How sales teams, investors, and analysts use AI to stay informed and prepared. 20:44 – Why specialized AI tools beat generic prompts The advantage of curated data, structured prompts, and purpose-built interfaces. 23:14 – AI Challenge: Prompt Engineering Taste Test Clint and Greg introduce this week’s hands-on AI experiment. 24:30 – Where to find Bruce and Analyst Copilot Bruce shares where listeners can learn more about his work. 25:00 – Episode wrap-up Clint and Greg close out another episode of Prompt This.

Guest Introduction  Martin Schneider is Vice President and Principal Analyst at Constellation Research. He has sat on both sides of the table as a go-to-market operator and now as an industry analyst advising companies on AI, CRM, and customer experience. In this episode, he joins Clint and Greg to break down what agentic AI is actually delivering in the real world and how to measure it without getting lost in hype. If you run sales, marketing, or customer success, this conversation is about outcomes, not buzzwords.  Episode Summary  Everyone is deploying AI agents. Almost no one is measuring if they work. Martin shares research from companies experimenting with agentic AI in sales, marketing, and customer success. The headline insight is bold. Some teams are seeing up to 40 percent productivity gains in focused use cases like AI BDRs.  AI is not replacing entire teams, and he is clear about it. The companies that tried that approach paid for it in churn and broken customer experiences. The winners are using AI to augment humans and improve throughput, conversion, and margin. We unpack five KPIs that matter, why de-qualifying early is a competitive advantage, and why unpredictable usage costs are slowing adoption. Martin also outlines two practical starting points for leaders who want real results without blowing up their org chart. This episode is about disciplined deployment, measurable outcomes, and protecting margin while scaling smarter. AI Challenge This week’s AI Challenge is called The 5 Deal DQ Check. Export five open opportunities from your CRM. Paste in: Deal summary Discovery notes Close date Deal size ICP criteria Then ask AI: "Should we continue pursuing these deals or DQ them?" AI has no commission bias. It does not care about your quarter. It will tell you where hope has replaced evidence. Get the full instructions at:   https://www.promptthis.ai/blog/how-to-run-the-5-deal-dq-check-with-ai Run the challenge. Then tell us what you learned. Chapter Breakdown  00:00 – Cold open: AI agents everywhere, but who is measuring results? 01:50 – Meet Martin Schneider and his research focus 03:40 – Hype vs reality in agentic AI adoption 07:00 – The 40 percent productivity gain in AI BDR use cases 10:00 – Why de-qualifying early is a superpower 14:00 – Margin expansion and the AI powered sales organization 18:30 – The biggest blocker: unpredictable costs 23:30 – How to think about AI deployment strategy 26:30 – Where leaders should start: AI BDR and RFP automation 29:55 – AI Challenge: The 5 Deal DQ Check 31:15 – Final takeaways and where to find Martin  

Guest Introduction In this episode, there is no outside guest. It is just Clint and Greg, and that is the point. Clint is a longtime startup operator who has lived through multiple waves of tech change and knows what it takes to turn big ideas into real execution. Greg built and scaled sales organizations in Silicon Valley and knows how revenue actually gets created inside a company. Together, they pressure test AI in the real world for operators in sales, marketing, and leadership. Today, they go deeper than most business leaders are willing to go. Down to the command line. Into source code. Into Claude Code.  And into what it means to manage AI as a team of coders rather than use it like a chatbot.    Episode Summary This episode is about unlocking new power.  Most business leaders still treat AI like a smarter Google. A writing assistant. A chatbot. Clint argues that this mindset is already outdated. This week builds on last week's episode where Clint created Greg's new personal website (grosenthal.lovable.app) in less than five minutes using Lovable. Today, Clint walks Greg through Claude Code, running inside the terminal, connected to GitHub, modifying that original website. In minutes, they: Pull code from a repository Run a local web server Modify site content through AI Push changes live If you can use AI and set up your laptop as a web server, then this episode is for you. The key shift is this: you are no longer coding line by line. You are managing coders. The AI writes the code. You direct outcomes. Greg connects this to what it means for sales and business leadership. In the past, this is where non-technical executives would tune out and let the sales engineer handle the conversation. Now, with AI in the loop, he doesn't just need to follow the coders. He can direct. He can build.   The second half of the episode shifts to Claude Cowork, Anthropic’s newer desktop interface. Clint gives a candid review. Listen in to hear his view on the business-readiness of Claude Cowork. The takeaway is clear. Work is changing fast. The leaders who lean in will operate with leverage. The ones who wait will be managed by those who did not. AI Challenge: Go Beyond the Browser This week’s AI Challenge is simple and uncomfortable by design. If you are only using ChatGPT in a browser, you are playing small. Clint recently pushed himself into Claude Code inside a real source code repository. It required help to get started. It required some technical fluency. And it stretched him. That stretch is the point. Your assignment: Pick one tool beyond the obvious LLM interface. Spend two focused hours with it. Ship something real. Some starting points: Gamma for AI-powered presentations Clay for data enrichment and outbound workflows NotebookLM for deep research synthesis Claude Code for deep AI-assisted software development in all forms Lovable for AI-assisted web development Riverside for AI-powered media production Do not just explore. Produce. For full instructions and links to tools, go to: https://www.promptthis.ai/blog/how-to-go-beyond-chatgpt-and-upgrade-your-ai-stack  If you have deployed AI inside your business, we want your story. Go to the Contact page at https://www.promptthis.ai and tell us what worked and what failed. Chapter Breakdown 00:00 – Welcome to Prompt ThisFraming the episode around real AI leverage versus hype.    02:25 – From Lovable to LocalhostMoving from a no-code website builder into GitHub and local development. 05:06 – Managing Coders, Not Writing CodeThe mental shift from typing every line to directing AI execution. 07:06 – Ask AI What to DoThe practical habit that unlocks progress when you hit friction. 09:42 – Live Website Edits with Claude CodeExpanding the “fun” section of Greg’s website and watching AI modify real files. 12:49 – Parallel Coders in Multiple TerminalsHow one operator can now manage multiple AI coding agents at once. 14:23 – One Person as an Entire DepartmentThe new operating model for marketers, sales leaders, and founders. 16:31 – What Is Claude CoworkOverview of Anthropic’s desktop app and how it differs from browser-based tools. 19:55 – Using AI to Create Show NotesFeeding MP3 and transcript files into Claude Cowork to generate structured output. 21:11 – Hype Versus RealityAn honest assessment of where Claude Cowork stands today. 21:48 – This Week’s AI ChallengePush yourself beyond ChatGPT and build something real. 23:38 – Anyone Can Be a CoderThe broader implications for business leadership and execution.  

Episode Summary Instead of interviewing a guest, Clint and Greg run a live demo. The goal is straightforward: can a marketer build a professional website without waiting on developers? The answer is yes. Clint starts by generating a detailed Lovable prompt inside ChatGPT. The LLM researches Greg’s background, identifies positioning themes, and structures a multi-page personal site. That prompt is copied into Lovable. Within minutes, a complete website appears. Navigation works. Pages are structured. Calls to action are in place. Even pricing tiers are suggested. From there, the real insight emerges. Instead of writing code or touching CSS, Clint makes edits through plain English: Add a headshot from LinkedIn. Insert a “Fun” section about old school rap. Add color that reflects personality. Publish to a live URL. Each iteration takes seconds. The larger takeaway is not about a website. It is about control. Marketing teams no longer need to queue behind engineering. Revenue leaders can prototype landing pages, ROI calculators, and interactive tools themselves. What used to take days or weeks can now happen in one working session. Clint makes a key comparison. He used to build market sizing calculators and ROI tools in Excel. It would take days to refine them. Now, he builds interactive web versions in Lovable in half a day. That shift matters. This is not about replacing developers. It is about unlocking speed and creativity inside marketing and sales teams. If you’ve ever said, “We need to wait on the web team,” this episode is for you. Check out Greg's new website here: Greg Rosenthal | AI Strategy for Revenue Leaders Guest Introduction  This week is a little different. No outside guest. No interview. Just the two hosts in the lab. Clint and Greg sit down for a live working session and build a fully functional personal website in minutes using Lovable and ChatGPT. Clint brings the technical depth. Greg brings the revenue lens. Together, they break down what this means for sales leaders, marketers, and anyone who has ever waited two weeks for a landing page update. If you lead revenue or marketing, this episode will challenge how you think about speed, ownership, and execution. AI Challenge This week’s AI Challenge is simple and practical. Build your own personal website in under 30 minutes using Lovable and ChatGPT. Here’s what to do: Use ChatGPT to generate a structured website prompt about you. Paste that prompt into Lovable. Publish your site. Iterate with small refinements until it feels right. Then share it with us. Full step-by-step instructions are on the blog at:https://www.promptthis.ai If you’ve deployed AI in your business, tell us what worked and what failed. Go to:https://www.promptthis.ai/contact This is about doing, not watching.  Chapter Breakdown 00:00 – Opening AI intro and framing the episode as a live demo instead of a guest interview. 01:30 – Why Personal Websites Still Matter The strategic case for owning your digital presence as a leader. 04:00 – Generating the Website Prompt in ChatGPT Using AI to research, structure, and position a personal brand automatically. 12:30 – Building the Site in Lovable From one prompt to a functioning multi-page website in minutes. 17:00 – Live Iteration Adding a headshot directly from LinkedIn. No downloads. No code. 19:00 – Injecting Personality Creating a “Fun” section about old school rap to humanize a revenue leader. 22:00 – Design Adjustments Through Plain English Adding color and brand personality without touching design files. 23:30 – Publishing to a Live URL Going from idea to live site in a single session. 25:00 – The Bigger Implication for Marketing Teams Why marketers no longer need to wait on web developers for every update. 27:30 – AI Challenge Your assignment: build your own site and experience the shift firsthand. 29:30 – Closing Thoughts Lovable as a must-have tool in the modern marketing and revenue stack.

Episode Summary In this episode, the conversation moves away from sales and marketing tactics and into the human core of leadership. Clint and Greg sit down with Shelli Hendricks to explore what executive coaching really is, what it is not, and how AI is starting to intersect with leadership development.  Shelli explains the difference between everyday coaching skills and professional executive coaching, emphasizing that true coaching is not advice-giving or performance management. It is about holding space, asking better questions, and helping leaders discover their own path forward. The group then digs into where AI can genuinely help leaders today. Simulation, practice, pattern recognition, and removing administrative friction are clear wins. But when it comes to wisdom, judgment, compassion, and navigating complex human dynamics, AI still falls short. They also explore emerging research showing the cognitive risks of over-reliance on AI, including reduced mental engagement and the danger of echo chambers that reinforce existing beliefs. The discussion ultimately lands on a clear conclusion: the future belongs to AI-augmented leaders who double down on their inner development rather than outsource it. This episode is a grounded, thoughtful look at how leaders can use AI without losing the human edge that makes leadership matter. This conversation is part of our Leadership Series, exploring clarity‑first leadership in the age of AI. Explore the full series here → https://www.promptthis.ai/prompt-this-podcast-leadership-series Guest Introduction Dr. Shelli Hendricks is an executive coach, PhD in Organizational Development and Change, faculty member with the American Management Association, and founder of Blue Horizon Solutions, a leadership development and coaching firm. She has spent more than two decades coaching leaders through major transitions, organizational change, and the hard human moments that define real leadership. Her work focuses on helping leaders grow their self-awareness, judgment, and compassion while navigating increasingly complex environments shaped by technology and AI. This Week’s AI Challenge AI-Augmented Leadership Reality Check  This challenge builds directly on the conversation with Shelli. Your task:  Dictate to ChatGPT or write out a recent leadership situation you faced. A difficult conversation, a change initiative, or a decision under pressure. Ask ChatGPT to summarize the situation and identify what leadership skills you demonstrated. Ask ChatGPT where it thinks you might benefit from additional perspective or growth. Then ChatGPT one more question: Where would a human coach add value in this situation that AI cannot? Resources:  Full AI Challenge walkthrough: https://www.promptthis.ai  Join the community discussion: https://www.promptthis.ai/contact Chapter Breakdown 00:00 – Welcome to Prompt This and episode setup 01:50 – Introducing Dr. Shelli Hendricks and her coaching background 04:15 – The difference between everyday coaching and executive coaching 05:45 – Common misconceptions about executive coaching 06:55 – Where AI fits into leadership development today 08:00 – AI simulations and skill practice for new managers 10:20 – How AI can make leaders more human 12:00 – Clint’s experiment with AI as an executive coach 15:15 – The risk of AI echo chambers and false affirmation 16:30 – Why AI struggles with complex change and human nuance 18:40 – Leadership wisdom, awareness, and compassion 20:10 – Research on AI, cognition, and mental engagement 24:20 – AI as a thought partner versus a replacement 27:00 – AI-augmented leaders and future leadership competencies 29:40 – When executive coaching is most valuable 32:50 – Leading through AI-driven transformation 34:40 – Final takeaway for leaders 35:00 – AI Challenge and closing remarks