Podcast
Business AI Explained
Hosted by Vlad · EN
Business AI Explained is a podcast for founders and go-to-market teams who want to understand how AI creates real business impact.
Hosted by Vlad de Ziegler, the show features conversations with builders, operators, and revenue leaders implementing AI in sales, marketing, RevOps, and customer success.
Expect real examples, real constraints, and clear lessons from AI in production, not theory.
10episodes
Episodes
Newest firstAll episodes
I just hosted the largest AI event in history. What I learned about AI adoption - Igor Pogany
Jun 3000:26:26Tap to summarizeIgor Pogany just hosted the largest AI event in history — 600,000+ people — and grew a 400K+ channel teaching mid-career professionals how to actually use AI.So I asked him the obvious question: what did running it all teach you about using AI? His answer isn't about prompts or the newest tool. It's about context: stop treating AI like a vending machine, start feeding it your context, and use it to amplify the expertise you already have instead of trying to reinvent yourself.Igor Pogany — founder of The AI Advantage and now partnered with Tony Robbins and Dean Graziosi — teaches mid-career professionals (average age 50+) how to master AI instead of fearing it. We get into the practical playbook: why you should amplify your existing expertise instead of reinventing yourself, how to give AI enough context that it stops people-pleasing and hands you opinions you can trust, the two-rule test for avoiding AI slop, how to grow an audience by matching your viewer's worldview, and the "company brain" he uses to run a 50-person media company on AI.In this episode:• Why you should amplify your existing expertise with AI instead of reinventing yourself• How to give AI enough context that it stops people-pleasing and tells you the truth• The two rules for avoiding AI slop (never go 0 to 1, always seed it)• How to grow an audience by matching your viewer's worldview — and what a thumbnail really is• Why social media is networking at scale — and how Igor ended up working with Tony Robbins & Dean Graziosi• The "company brain" and Alfredo Hub setup Igor uses to run a 50-person company on AIChapters:0:00 The world's largest AI event (intro)2:50 Who Igor helps: mid-career pros vs AI anxiety4:10 Amplify what you do — don't reinvent yourself6:18 The fastest first win: photograph your fridge7:41 Using AI for decisions you can trust8:36 Context: how to stop AI people-pleasing13:25 Creating content with AI — without the slop15:17 The real skill: turning chaos into content17:30 Match your audience's worldview19:07 Grow an audience: networking at scale23:26 Compacted knowledge = time travel25:47 The Alfredo Hub: one place for every AI tool29:23 Company brain: a shared source of truthGuest: Igor Pogany, Founder @ The AI Advantage. Igor Pogany is the founder of The AI Advantage, one of the most-watched practical-AI channels on YouTube (400K+ subscribers), and Head of AI Education for the AI Advantage program he runs with Tony Robbins and Dean Graziosi. He teaches professionals how to use AI to save time and amplify the expertise they already have.Connect with Igor: https://www.linkedin.com/in/igorpogany/Connect with Vlad:• LinkedIn: https://www.linkedin.com/in/vladeziegler/• YouTube: https://www.youtube.com/@aiwithvlad• Work with Vlad (Elements Agents): https://www.elementsagents.com/• Come on the show: https://cal.com/vladimirelements/podcast-intro-call—Business AI Explained is a podcast for founders and GTM teams on how AI creates real business impact — real examples, real constraints, lessons from AI in production. Hosted by Vlad de Ziegler, founder of Elements Agents.
Transcribe →How to Actually Implement AI in Business — Michael LaVista
Jun 1100:29:09Tap to summarizeMost companies are buying AI, then quietly failing at the last mile. Michael LaVista has spent 25 years shipping the hard final stretch — here's how he gets AI into production.Michael LaVista, founder of Caxy (a Chicago software firm that's spent 25+ years staying a few steps ahead of the market), breaks down "last-mile AI" — why most AI projects run out of steam right at the end, and how to actually get them into production. We cover finding use cases worth building, the AI stack you can realistically hire for, driving adoption against real resistance, value-stream mapping to find the work that matters, guardrails for autonomous agents, and the rule that saves the most pain: solve the problem first, pick AI second. Real AI in production, not theory.In this episode:• What "last-mile AI" is — and why most AI projects run out of steam right at the end• How to find AI use cases worth building (let 100 ideas compete, keep the home runs)• Why automating tasks you already do is a weak AI strategy — and what to do instead• How to pick an AI stack you can actually staff and maintain• Driving adoption when part of your team is quietly resisting AI• Value-stream mapping, guardrails for autonomous agents, and when NOT to build it yourselfChapters:0:00 Cold open: pick the problem, not the hype1:20 Last-mile AI: where AI projects quietly die2:56 Why automating tasks is a losing bet3:53 "The board said use AI" — $100K/mo, zero accountability5:45 Finding use cases: let 100 ideas compete6:54 Idea to working software in 6 minutes8:07 The AI stack: pick tech you can actually hire for9:52 Adoption & the people who resist AI11:25 Value creation beats automation (proposals, IKEA)15:43 Right tool for the job: when NOT to use AI18:47 Value stream mapping: find the red-pen process21:28 Coding vampires & the autonomous-agent holy grail23:25 Guardrails: prompt injection & Bedrock24:58 Three steps ahead: a world where everyone builds27:46 Final advice: problem first, then go get helpGuest: Michael LaVista, Founder & CEO @ Caxy. Michael LaVista is the founder and CEO of Caxy, a Chicago-based software and AI transformation firm. For 25+ years he's helped mid-sized companies turn AI from a board mandate into something that actually ships — what he calls last-mile AI.Connect with Michael: https://www.linkedin.com/in/michaellavista/Connect with Vlad:• LinkedIn: https://www.linkedin.com/in/vladeziegler/• YouTube: https://www.youtube.com/@aiwithvlad• Work with Vlad (Elements Agents): https://www.elementsagents.com/• Come on the show: https://cal.com/vladimirelements/podcast-intro-call—Business AI Explained is a podcast for founders and GTM teams on how AI creates real business impact — real examples, real constraints, lessons from AI in production. Hosted by Vlad de Ziegler, founder of Elements Agents.━━━━━━━━━━━━━━━━━━━━━#BusinessAI #AIForBusiness #AIimplementation #AIstrategy #AIadoption
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$200M Selling Chicken In Under 3 Years — Leander Gruss, How Lanch Built a $200M Business with AI-native operations — Leander Gruss
Jun 200:38:47Tap to summarizeLanch went from zero to $200M in under three years selling chicken. Leander Gruss, Head of Growth at Lanch, will explain us how.In this episode:• Why you should never "vibe-code" your source of truth — and how to decide build vs buy• How a non-technical growth lead actually ships internal tools (the exact stack)• The 2-day prototype rule that stops AI builds from sprawling• Running shared AI agents for SQL, customer support and procurement across the org• Why clean, structured data — not bigger prompts — makes agents accurate• The buy-vs-build math that's wiping out their monthly software billsChapters:0:00 Cold open: own the transaction1:08 Meet Leander & Lanch (0 to $200M)3:41 The data warehouse that runs the business6:09 Writing SQL in minutes, not weeks7:22 Build vs buy: what NOT to vibe-code8:22 Building the route-optimization tool10:26 The build stack: Replit, Lovable, Claude Code, Vercel, Supabase11:55 Driving AI adoption + PRDs + cost limits15:39 Langdock & sharing agents across the org18:38 Context engineering & RAG for retrieval24:25 Benchmarking & evals26:33 Buy to build economics & maintenance32:45 Lovable + git + skills = 3-4x dev cycle37:40 Where to find LeanderGuest: Leander Gruss, Head of Growth @ Lanch. Leander Gruss leads growth at Lanch, the creator-backed food-tech company behind Loco Chicken and Happy Slice. He joined as one of the first employees and helped scale it from zero to $200M.Connect with Leander: https://www.linkedin.com/in/leander-gruss-aa1280147/Connect with Max: https://constructlabs.com/Connect with Vlad:• LinkedIn: https://www.linkedin.com/in/vladeziegler/• YouTube: https://www.youtube.com/@aiwithvlad• Work with Vlad (Elements Agents): https://www.elementsagents.com/• Come on the show: https://cal.com/vladimirelements/podcast-intro-call—Business AI Explained is a podcast for founders and GTM teams on how AI creates real business impact — real examples, real constraints, lessons from AI in production. Hosted by Vlad de Ziegler, founder of Elements Agents.
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Why Most AI Agent Projects Die at the Last Mile — Idan Raman
Apr 2100:26:40Tap to summarizeMost AI agent projects stall at the last mile: the legacy browser workflows no API can reach.Idan Raman, founder of Anchor Browser, joins Vlad to explain why browser agents are the missing piece in enterprise AI, how the Cloudflare partnership is changing the economics of automation, and why the OpenClaude security fallout was a wake-up call for anyone running computer-use agents in production. If you're evaluating AI agents for your business, this is the layer of the stack nobody's explaining clearly.In this episode:- Why 90% automated still isn't automated — the KYC last-mile problem- Computer use vs browser use, and when each one makes sense- The real security story behind the OpenClaude virality (leaked credit cards, stolen passwords)- How enterprises are pricing AI: the voice AI framework ($3/call → $0.30) applied to back-office work- Why open source LLMs are exploding inside large enterprises- The Cloudflare "web bot protocol" and why it's a win for everyone- Building a moat in AI infrastructure: "if it's hard, it's good"Chapters:00:00 Intro00:52 Computer use vs browser use03:34 KYC as the poster child06:08 The Cloudflare partnership09:01 When to use browser agents vs Playwright10:56 Security and the OpenClaude fallout14:05 Open source LLMs in the enterprise17:08 Pricing AI tools for enterprise21:19 Building a real moat in AI25:24 Dogfooding Anchor to grow Anchor29:45 What's nextGuest: Idan Raman, Founder @ Anchor Browser. Idan built Anchor Browser to solve the last-mile automation problem for enterprise AI agents.Connect with Idan: https://www.linkedin.com/in/idan-raman/Anchor Browser: https://anchorbrowser.io/Connect with Vlad:- LinkedIn: https://www.linkedin.com/in/vladeziegler/- YouTube: https://www.youtube.com/@aiwithvlad- Work with Vlad (Elements Agents): https://www.elementsagents.com/- Come on the show: https://cal.com/vladimirelements/podcast-intro-call—Business AI Explained is a podcast for founders and GTM teams who want to understand how AI creates real business impact. Hosted by Vlad de Ziegler.
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Why Most AI Training Fails at Work | Elise Masurel de Laval
Apr 1401:04:08Tap to summarizeAI training usually fails for a simple reason: it is too generic.In this episode of Business AI Explained, I sit down with Elise Masurel de Laval, co-founder of Catalyst.ai Academy, to break down what makes AI training actually work inside companies. Elise and her team focus on practical AI training for non-technical roles, with a strong emphasis on role-based use cases and learning by doing rather than abstract demos. They discuss why AI adoption needs to be tied to real business workflows, why peer-led learning often beats formal training, and how companies should think about shadow AI, governance, and long-term capability building. They also explore why AI agents create excitement early on but often become difficult to maintain unless internal teams can truly own them.They cover: Why most AI training programs fail The case for role-specific AI enablement Why peer practitioners are often the best teachers How to build relevance through real company use cases Why AI communities can outperform static courses How to think about shadow AI without overreacting Balancing experimentation with governance The hidden maintenance cost of AI agents Why practical adoption matters more than tool knowledge How non-technical teams can build AI confidence quickly This episode is for founders, operators, enablement leaders, consultants, and anyone trying to move from AI awareness to real adoption across teams.About the guest Elise Masurel de Laval is co-founder of Catalyst.ai Academy. Catalyst describes its approach as practical AI training for non-tech roles, and the company’s about page highlights Elise’s background in marketing, digital, sales, innovation, and executive leadership in education. Where to find Elise: → LinkedIn: https://www.linkedin.com/in/elise-masurel-de-laval-2579b999/?skipRedirect=true → Company: https://catalystacademy.ai/Work with Vlad: If you’re implementing AI in your operations and want hands-on help building real workflows: → https://www.elementsagents.com/Subscribe / follow Vlad: → LinkedIn: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad
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From Bankruptcy to Building Booxkeeping: Max Emma on Franchising, Bookkeeping and AI in Operations
Apr 800:35:05Tap to summarizeMax Emma started in landscaping and construction, then got hit hard during the 2008 recession, a period that eventually led to bankruptcy and some hard-earned lessons about risk, financial management, and resilience.He later co-founded Booxkeeping, a bookkeeping business built around fixed pricing, operational efficiency, and standardized financial reporting. That business went on to scale through franchising, becoming a standout model in the bookkeeping industry.In this episode of Business AI Explained, Vlad sits down with Max to unpack that journey and explore how AI is being used inside real business operations today. They discuss where AI genuinely saves time, why custom AI builds often disappoint, and how off-the-shelf tools like ChatGPT and QuickBooks can create real leverage when applied to the right workflows.They cover: Lessons from the construction industry and the 2008 recession The path from bankruptcy to building a new business Why bookkeeping was the opportunity Max chose to pursue How Booxkeeping scaled through franchising Where AI works well in finance and ops Why custom AI tools can be costly and impractical How AI helps evaluate franchise territories faster Using AI to automate notes, emails, and internal workflows Why efficiency gains matter more than hype How lower operating costs can become a competitive advantage This episode is for founders, operators, franchise builders, finance leaders, and anyone trying to understand what practical AI adoption looks like inside a real business.Where to find Max Emma: → LinkedIn: https://www.linkedin.com/in/maxemma/ → Company: https://www.linkedin.com/company/booxkeeping/Work with Vlad: If you’re implementing AI in your operations and want hands-on help building real workflows: → https://www.elementsagents.com/Subscribe / follow Vlad: → LinkedIn: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad
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AI Adoption Playbook for Sales, CS and Marketing | Charlotte Lucas, ScorePlay
Mar 3100:37:16Tap to summarizeAI adoption usually breaks when companies try to force it top-down or keep it stuck in experimentation.Charlotte Lucas is Head of Strategy at ScorePlay, where she’s driving AI adoption across the business to help teams in sales, customer success, marketing, and operations move faster and work smarter. As ScorePlay competes in sports broadcasting with a lean team, Charlotte is building practical AI workflows that save time, improve execution, and help teams scale without losing the human touch. In this episode of Business AI Explained, we break down what AI adoption actually looks like when it works: how to get buy-in, where to start, which workflows to prioritize, and how to combine executive sponsorship with team-level ownership. We also cover how AI can support relationship-driven work, why shared learning matters, and how to build trust in AI outputs across the company. We cover: Why AI adoption works best when leadership sponsors it, but teams own the use cases How to start with small, practical workflows that build trust quickly How ScorePlay is using AI across lead generation, deal desk ops, customer success, and marketing Why peer learning, internal sessions, and shared channels accelerate adoption How to match the right AI tools to the right teams What strong governance looks like: access, review loops, and exception handling How AI can strengthen relationship-driven work instead of replacing it Why automating high-impact, low-complexity workflows creates leverage across the business How unstructured data can become a strategic advantage with the right AI workflows What it takes to build an AI culture that works both top-down and bottom-up This conversation is for founders, operators, GTM leaders, strategy teams, and department heads trying to move from AI experimentation to real adoption across the company.Episode length: ~45 minutes👤 ABOUT THE GUESTCharlotte Lucas Head of Strategy, ScorePlayCharlotte Lucas leads strategy at ScorePlay and is driving AI adoption across the company to help teams save time, improve execution, and support sales, customer success, and marketing at scale.→ LinkedIn: https://www.linkedin.com/in/charlotte-lucas-ba479125/ → Company: https://www.scoreplay.io/🔗 WORK WITH VLADIf you’re implementing AI in your operations and want hands-on help building real workflows:👉 https://www.elementsagents.com/🔔 SUBSCRIBE→ Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvladWatch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.
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AI in Sales: How Enterprises Use Chatbots, Data & Automation to Close More Deals
Mar 2400:24:05Tap to summarizeAI is no longer just a buzzword in sales, it’s becoming the backbone of how companies engage customers, qualify leads, and scale go-to-market.In this episode, I’m joined by Adis Ceman, Regional Enterprise Sales Director at Cequens, a company building AI-powered communication systems across channels like WhatsApp, SMS, and voice.We go deep into how enterprises are actually using AI today, beyond the hype.We cover: How AI chatbots are replacing missed opportunities in customer support Why most companies fail at AI How to structure your data and prompts to get real results How AI is used in enterprise sales (lead generation, qualification, demos) The role of human touch in high-value deals (and why it still matters) How to use AI internally to train teams, build proposals, and move faster What signals actually matter when selling to enterprise clients Why speed + personalization are the real competitive advantages in 2026 One of the most valuable insights:AI doesn’t replace sales teams, it makes them faster, sharper, and more responsive.If you're building a product, running sales, or thinking about implementing AI in your company, this episode will give you a clear, practical view of what works.Episode length: ~24 minutes👤 ABOUT THE GUESTAdis CemanRegional Sales Director at Cequens - UAE→ LinkedIn: https://www.linkedin.com/in/adisceman/→ Company: https://www.cequens.com/🔗 WORK WITH VLADIf you’re implementing AI in your operations and want hands-on help building real workflows:👉 https://www.elementsagents.com/🔔 SUBSCRIBE→ Linkedin: https://www.linkedin.com/in/vladeziegler/→ AI with Vlad: https://www.youtube.com/@aiwithvladWatch the full video version on YouTube: https://www.youtube.com/@aiwithvladNew episodes every Tuesday.
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How AI Is Rewriting Hiring and Operations | Sean Griffith (Founder of Truffle)
Mar 1700:30:39Tap to summarizeMany companies are experimenting with AI.But very few are restructuring their operations around it.In this episode of Business AI Explained, Vladimir de Ziegler sits down with Sean Griffith, founder of Truffle, to discuss how AI is reshaping hiring, software workflows, and internal operations.Sean explains how his team is able to produce the same level of output with fewer than 10 people compared to what he previously experienced inside a publicly listed company doing over $300M in ARR.The conversation explores how startups and modern teams are beginning to replace traditional software tools with AI-driven workflows and how leaders can rethink operations to become fully AI-native.Sean also explains how Truffle is redesigning the hiring process using AI-assisted candidate screening, transcription, and evaluation to help HR teams move from hundreds of applicants to a shortlist much faster.The conversation covers:• How startups can control costs when rolling out AI features• Quick SEO opportunities to appear in LLM search results• How developers are replacing traditional software with Claude Code• How to structure operations for AI-native teams• Which tools and workflows companies should automate first• How AI is transforming hiring and recruitment processesIf you're building products, leading a startup, or exploring how AI can reshape your internal operations, this episode provides practical insights into the next generation of AI-native companies.Episode length: ~30 minutes👤 ABOUT THE GUESTSean GriffithFounder of Truffle→ LinkedIn: https://www.linkedin.com/in/griffithsean/→ Company: https://www.hiretruffle.com/🔗 WORK WITH VLADIf you’re implementing AI in your operations and want hands-on help building real workflows:👉 https://www.elementsagents.com/🔔 SUBSCRIBE→ Linkedin: https://www.linkedin.com/in/vladeziegler/→ AI with Vlad: https://www.youtube.com/@aiwithvladWatch the full video version on YouTube: https://www.youtube.com/@aiwithvladNew episodes every Tuesday.
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AI Implementation in Sales & Product Teams | Alexis d'Eudeville (Lemlist)
Mar 1200:40:08Tap to summarizeMost companies talk about AI.Very few actually implement it in production.In this episode of Business AI Explained, Vladimir de Ziegler sits down with Alexis d'Eudeville, AI Product Manager at Lemlist, to discuss how AI is being used inside real companies.Alexis shares practical lessons from building AI products, launching startups, and working at Google.They explore how AI is transforming product management, sales automation, and go-to-market strategy and why the most important factor is still keeping humans in the loop.The conversation covers:• How AI is implemented inside modern sales teams• The role of generative AI in product management• Why data quality matters for AI adoption• How companies can move from experimentation to AI in production• Practical examples of AI improving marketing and customer successIf you're a founder, operator, or builder trying to understand how AI is actually used inside businesses, this episode breaks down the real strategies behind AI implementation.Key Topics:AI implementation in businessAI in product managementSales automation and RevOpsGo-to-market strategyAI in production systemsChapters:00:00 Introduction – Alexis d'Eudeville & AI at Lemlist01:45 AI in Business: Why Implementation Matters05:12 How Companies Are Using AI in Production08:30 Generative AI for Content and Data Analysis12:45 Human-in-the-Loop AI and Ethical Considerations18:20 The Future of AI Tools in Business Workflows22:15 Real AI Examples in Marketing and Customer Success27:40 AI Adoption Challenges for Startups and SMEs31:05 How Companies Can Successfully Implement AI35:50 Key Takeaways: AI Impact on Business Growth38:15 Final Thoughts on the Future of AIEpisode length: ~40 minutes👤 ABOUT THE GUESTAlexis d’EudevilleAI Product Manager at Lemlist→ LinkedIn: https://www.linkedin.com/in/alexis-d-eudeville-348bb858/→ Company: https://www.lemlist.com/🔗 WORK WITH VLADIf you’re implementing AI in your operations and want hands-on help building real workflows:👉 https://www.elementsagents.com/🔔 SUBSCRIBE→ Linkedin: https://www.linkedin.com/in/vladeziegler/→ AI with Vlad: https://www.youtube.com/@aiwithvladWatch the full video version on YouTube: https://www.youtube.com/@aiwithvladNew episodes every Tuesday.
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