In this episode of AI Lab Unfiltered, Drew Veach (BizStream) and Pete Tarrin (New Wave) talk with Steven Lopez, Director of Manufacturing Solutions at The Right Place, about what AI really looks like in manufacturing—especially in the front office. They explore how AI can speed up quoting, clean up manual processes, integrate legacy systems, and help manufacturers see where they actually stand competitively. Steven shares how he uses AI to cut research time, run better assessments, and design dynamic tools that give leaders same-day insights—all while tackling fears around change, jobs, and “AI for the sake of AI.” Powered by ThinkTank Thought Leadership. Chapters(00:00) Intro: AI in the manufacturer’s front office(00:38) How ThinkTank Thought Leadership powers this podcast(01:33) Meet Steven Lopez & The Right Place’s mission(02:40) Competitiveness, “ugly babies,” and gap analysis(06:27) Where tech & AI fit in manufacturers’ reality(08:12) Fixing the front end: quotes, ERP, and AI-enabled speed(12:11) AI adoption across 13 counties & different types of manufacturers(17:44) AI as collaborator, org charts, and the future of director roles(23:28) Blank-check vision: AI-powered assessments that protect communities(35:32) Dynamic assessments, avatars, and rethinking how we help manufacturers

In this episode of AI Lab Unfiltered, Drew and Pete sit down with Shannon McCormick, Senior Data Scientist at Scandinavian Tobacco Group, to talk about what it really looks like to unleash AI inside your datasets and treat it like a smart coworker instead of a magic black box.Shannon walks through how she uses transactional and customer data in a B2C environment to drive better decisions across shipping, promotions, and retention—everything from scorecards and customer profiles to advanced predictive models with millions of rows. They dig into the messy realities of the job: why 70% of her time is still spent in SQL, why “garbage in, garbage out” still rules, and why you shouldn’t wait for perfect data before you start experimenting with AI.They also unpack the difference between LLM-powered analysis and classic machine learning, when a simple logistic regression beats building your own LLM, and how tools like Copilot and ChatGPT can extend (not replace) the skills of data scientists, marketers, and engineers. The conversation closes with a hopeful look at AI as a creator of new jobs, new businesses, and a radically lower barrier to entrepreneurship.If you’ve ever wondered how to actually use AI with your business data—without getting lost in the hype—this episode is your playbook.Chapters(00:00) Cold Open, Sponsor Shoutout & Episode Setup(01:35) What Does a Data Scientist Actually Do?(02:56) Inside B2C Data: Transactions, Shipping & Promotions(05:54) Predictive Marketing Models & Campaign Targeting(08:33) Analytics Beyond Big Tech: Meijer, Cigars & Mid-Sized Teams(10:42) Data Quality, Cleaning & “Tending the Data Garden”(13:54) Influencing Data Collection & Working with Data Engineering(14:58) Synthetic Data, Surveys & Learning from What You Don’t See(18:16) Getting Started with Data & AI (Even If You’re Not a Data Scientist)(21:25) LLMs vs Classic Machine Learning: Picking the Right Approach(25:07) AI as a Smart Coworker: Jobs, Skills & “Vibe Coding”(31:25) Everyday AI, Marketing Automation & New Entrepreneurs(43:57) Tradeoffs: Learning Deep Skills vs Letting AI Do the Work(46:46) Final Takeaways & Where to Find Shannon

In this episode of AI Lab Unfiltered, Drew and Pete tackle one of the most talked-about topics in modern industry: how AI is reshaping manufacturing. From job displacement fears to the rise of “cobots,” they explore how artificial intelligence can enhance—rather than replace—human roles. The hosts share insights on balancing efficiency with humanity, creating a positive workplace culture, and preparing teams for the future of human-AI collaboration. Chapters(00:00) Intro and AI in Manufacturing(01:22) Job Displacement Fears and Workforce Augmentation(07:54) Pros and Cons of AI Adoption(14:56) Culture, Leadership, and Employee Engagement(21:49) The Future of Work and Human-AI Collaboration(29:43) Closing Thoughts and Call to Action 

In this episode, Doug Landman from The Right Place and the Michigan Manufacturing Technology Center (MMTC) joins to discuss how manufacturers can transition from reactive to predictive maintenance—and see immediate savings. Doug explains how even small and mid-sized manufacturers can deploy low-cost sensors, leverage real-time monitoring, and use data to anticipate failures before they happen. The conversation explores practical strategies for reducing downtime, improving efficiency, and empowering teams through upskilling and data-driven decision-making. Chapters(00:00) Intro and Series Kickoff(03:20) Overview of The Right Place and MMTC(07:10) From Perfection to Progress: Start Small(14:20) Hands-On Learning and Data Fundamentals(20:15) Real-Time Monitoring and Predictive Insights(24:50) Low-Cost Retrofits: Sensors and Smart Maintenance(30:50) AI Beyond the Production Line(42:40) How Small Manufacturers Can Start(50:40) Lessons from Lean and Six Sigma(54:45) Risks, Funding, and Next Steps(1:02:10) Closing Thoughts and Resources

Pivoting isn’t failure—it’s progress.In this episode of the City Innovations Podcast, Chris Tromp (COO, City Innovations) talks with Josh Barker (CEO & Founder, City Innovations) about the emotional and strategic realities of changing course, calling it quits, or pivoting. They unpack why failure is a critical part of learning and how focusing on traction first leads to breakthroughs.They discuss:Why pivots don’t equal failureThe role of failure as learningWhen to pivot, persevere, or purgeThe dangers of false summits and the feature mythWhy traction metrics matter more than vanity metrics⏱️ Chapters: (00:00) Welcome and Intro: Chris Tromp and Josh Barker (01:22) Why Founders Struggle with Pivoting (05:34) Failure as Learning and Progress (09:18) Celebrating Learnings, Not Just Wins (14:10) When to Pivot vs. Persevere vs. Purge (19:27) False Summits, Burnout, and the Feature Myth (25:40) Small Pivots vs. Big Pivots: What Works (31:05) Communicating Pivots to Your Team (37:11) Red Flags: When It’s Really Time to Pivot (43:20) Startup Stories: Pivoting with Clients (49:18) Final Thoughts: Traction First and Avoiding Vanity MetricsWant to learn more?Check out our site.https://www.tractionfirstbook.com/