The magentIQ Show

magentIQ
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Real talk with the operators and executives putting AI to work - not the ones tweeting about it. Every episode goes deep on what shipped, what flopped, and what it actually took. No hype, no hand-waving, no LinkedIn gurus. Just the workflows, decisions, and outcomes from the people doing the work. Built on a simple magentIQ belief: AI and people are better together - and getting that right is the whole game.

  1. 2d ago

    Ready, Set, Go: Your 2027 Agentic Playbook | Part 2: Set & Go

    Ready to turn your AI ambitions into real business outcomes in 2027? Let's talk about how to set the right direction, choose the right capabilities, and build an AI-powered operating model that works for your business. Talk to the magentIQ team: https://bemagentiq.com/resources/contact-us/ --- In Part 1 of Ready, Set, Go: Your 2027 Agentic Playbook, Ian Barkin and David Brain explored what it really means to be AI-ready, from understanding your data and processes to getting your technology, talent, and governance in order. Now that you've examined the foundations, it's time to decide what comes next. What are you trying to achieve? Which AI capabilities do you actually need? And who's going to build and run it all? As Ian and David explain, assembling the right team can feel like recruiting astronauts for the first Mars mission, only to discover the job description requires two previous trips to Mars. Catch up on Part 1: Ready Stage: INSERT LANDING PAGE HERE  In this episode, Part 2 of Ready, Set, Go: Your 2027 Agentic Playbook, Ian and David pick up where they left off, moving from AI readiness into the Set and Go stages. They explore how to define your AI strategy, build a business case, design your future workflows, and choose the right technology and delivery partners. Along the way, they challenge the idea of the all-knowing forward-deployed engineer, revisit the familiar question of whether to build or buy, and explain why pilots should answer specific questions before businesses commit to full-scale deployment. They also tackle the final challenge: putting everything into production without disrupting the business you're trying to improve. From safeguards and rollout strategies to faster development cycles, Ian and David make a practical, optimistic case for what organizations can achieve when they prepare properly. Their guiding principle? Slow is smooth, and smooth is fast. About the Hosts Ian Barkin and David Brain are co-founders and co-CEOs of magentIQ, bringing decades of experience in automation, outsourcing, and operational transformation. Ian is an automation industry veteran known for making complex AI concepts accessible through practical examples, storytelling, and a healthy dose of humor. David brings the operator's perspective, grounded in enterprise delivery, process design, and measurable business outcomes. Together, they explore how AI and people can work better together, challenging assumptions and sharing what they're learning along the way. Further Reading from magentIQ The magentIQ Method - https://bemagentiq.com/approach/ Explore magentIQ's approach to understanding existing operations, designing an agentic operating model, and bringing AI and human expertise together to deliver measurable outcomes. The Map Before the Machine - https://bemagentiq.com/whitepaper/whitepaper-the-map-before-the-machine/A practical guide to mapping workflows, identifying decision points, and determining where AI, automation, and people belong before choosing the technology. You're Not Automating a Process. You're Automating the Brokenness. - https://bemagentiq.com/youre-not-automating-a-process-youre-automating-the-brokenness/David Brain explores why even the best AI engineers need a clear understanding of business processes, including the exceptions, workarounds, and human judgment that shape how work gets done. In This Episode (0:11) Welcome to Part 2: moving from AI readiness to setting direction and scaling deployment (1:21) The Set stage: defining your strategy, objectives, programs, and priorities for 2027 (2:09) Building an AI blueprint: choosing the capabilities, workflows, and technology your business needs (3:07) Why a clear business case matters for funding, accountability, and measurable outcomes (4:03) Building your own AI team, and the challenge of attracting and retaining specialized talent (5:18) The AI talent puzzle: changing job titles, unclear qualifications, and impossible hiring requirements (7:04) Recruiting for the first Mars mission, but requiring applicants to have already visited Mars twice (8:10) The forward-deployed unicorn: why domain expertise, engineering, and change management require a team (9:12) The center of excellence question: can your organization actually support a successful one? (11:08) Build, buy, or outsource? Choosing the right delivery model for your organization (12:03) Agentic operating models as a service, and the economics of subscription-based delivery (13:17) The right time for pilots: proving specific capabilities before committing to deployment (14:17) Winning hearts and minds, testing integrations, and knowing exactly what your pilot needs to prove (15:32) Testing customer acceptance of AI, and why some of the biggest questions are about human behavior (16:06) The Go stage: sequencing projects, limiting disruption, and scaling AI safely (16:52) Slow is smooth, smooth is fast: why preparation makes faster transformation possible (18:55) Accelerating development without abandoning quality assurance and release discipline (20:01) Why 2027 could bring a renaissance in business process reengineering and design thinking (22:10) Starting with the future: vision workshops, value chains, and working backward to an actionable plan (23:35) Bringing Ready, Set, and Go together, and how to start the conversation with magentIQ (25:16) Final reflections on building and scaling an AI-powered operating model in 2027 Find Us on Your Favorite Streaming Service iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ready, Set, Go: Your 2027 Agentic Playbook | Part 2: Set & Go

  2. 4d ago

    Ready, Set, Go: Your 2027 Agentic Playbook | Part 1: Ready

    How AI-ready is your organization for 2027? Let's talk about where you stand today and what it takes to prepare your business for AI-powered transformation. Talk to the magentIQ team: https://bemagentiq.com/resources/contact-us/ --- Before you build an agentic business for 2027, how well do you understand the one you're running today? AI has made its way into emails, research, scheduling, and everyday tasks. But turning those capabilities into meaningful business transformation takes a closer look at how work actually gets done. And as Ian Barkin and David Brain explain, buying another AI license is only one small part of the equation. In Part 1 of Ready, Set, Go: Your 2027 Agentic Playbook, Ian and David revisit what 2026 has taught businesses about AI adoption and introduce the five pillars of AI readiness: Data, Process, Technology, Talent, and Governance. They explore why process documentation matters, how to identify the data you can actually trust, and why understanding your operations should come before choosing new technology. Along the way, they share real client examples, challenge the idea of an AI chief of staff, and explain why even the simplest business process can become surprisingly complicated when you look closely enough. The message is encouraging: your organization doesn't need perfect foundations to make progress. But knowing where you stand is a valuable place to begin. About the Hosts Ian Barkin and David Brain are co-founders and co-CEOs of magentIQ, bringing decades of experience in automation, outsourcing, and operational transformation. Ian is an automation industry veteran known for making complex AI concepts accessible through practical examples, storytelling, and a healthy dose of humor. David brings the operator's perspective, grounded in enterprise delivery, process design, and measurable business outcomes. Together, they explore how AI and people can work better together, challenging assumptions and sharing what they're learning along the way. Further Reading from magentIQ The magentIQ Method - https://bemagentiq.com/approach/Explore magentIQ's approach to understanding existing operations, designing an agentic operating model, and bringing AI and human expertise together to deliver measurable outcomes. Understand the Process Before You Automate It - https://bemagentiq.com/understand-the-process-before-you-automate-it/David Brain explains why understanding how work actually gets done, including business rules, exceptions, and human judgment, is essential to building AI solutions that last. The Map Before the Machine - https://bemagentiq.com/whitepaper/whitepaper-the-map-before-the-machine/A practical guide to mapping workflows, identifying decision points, and determining where AI, automation, and people belong. In This Episode (0:11) Introducing Ready, Set, Go: a two-part playbook for preparing your business for 2027 (1:32) Looking back at 2026, and what businesses have learned about AI adoption (3:07) Rising AI investments, growing production deployments, and the search for measurable outcomes (4:24) Why buying AI licenses alone won't transform your business (5:58) From job titles to task-level automation, and how AI is being absorbed into everyday work (7:01) When the excitement around Copilot and other AI tools starts to fade (8:47) The agentic chief of staff: what AI assistants can actually do versus what the job requires (12:06) Paving the cow paths: why automating existing processes only gets you so far (14:05) The return of business process reengineering, and why David is back in fashion (16:23) The five pillars of AI readiness: Data, Process, Technology, Talent, and Governance (18:08) Understanding how your organization operates today before designing its future (19:33) Data readiness: knowing what information you have and what you can trust (20:20) A real client example of how incomplete data affects financial reporting (21:17) Using AI to classify tax documents and turn unstructured information into usable data (22:28) Why companies tend to overestimate their readiness, and what happens when assumptions meet reality (25:03) Process readiness: the hidden steps, business rules, and exceptions that matter in production (27:32) The sandwich analogy: why seemingly simple workflows are more complicated than executives realize (30:26) Technology readiness: understanding the job before choosing the tools (32:40) Talent readiness: identifying skill shortages and where AI can help (33:38) Governance readiness: balancing access to AI tools with practical controls (36:36) Why data and process should come first, and the operational improvements they can uncover (38:00) Working with legacy technology while managing new AI capabilities across the business (40:08) Giving employees a safe, approved way to innovate with AI (43:18) Wrapping up the Ready stage and a preview of Part 2: Set and Go Coming Up in Part 2 With the foundations understood, where do you go next? In Part 2 of Ready, Set, Go: Your 2027 Agentic Playbook, Ian and David move into the Set and Go stages. They'll explore how to define your AI strategy, build the business case, identify the right capabilities and partners, and turn that preparation into a practical plan for deployment and scale. Listen now, and tell us: how confident are you in your organization's AI readiness for 2027? Find Us on Your Favorite Streaming Service iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ready, Set, Go: Your 2027 Agentic Playbook | Part 1: Ready

  3. Oct 23

    Ep. 33 | Stop Buying Sparkly Slides (Guest: Kyler Cheatham)

    A vendor promises AI will fix your messy data. The proof? A presentation slide where the messy data goes in, the clean data comes out, and there are sparkles. Kyler Cheatham has spent years navigating enterprise technology sales pitches like this, and she's found a hilarious way to expose their absurdities on TikTok. Behind the humor is a serious message for business leaders: know what you're buying, understand what you're signing, and ask what happens when the impressive demo meets your actual operation. In this conversation, Ian Barkin and Kyler explore why technology implementations go sideways, how the relationship between business and IT shapes success, and what happens when AI agents are added to already complicated software contracts. They get into surprise SaaS bills, vendor lock-in, vibe coding, and the consultants who seem to profit from projects going wrong. They also make a compelling case for the people who keep enterprises running, from the IT teams managing systems behind the scenes to the experienced manufacturing workers who know exactly what to do when a machine starts making a strange noise. About the Host Ian Barkin is the co-founder and co-CEO of magentIQ, with decades of experience in intelligent automation, outsourcing, and operational transformation. Through The magentIQ Show, he brings together business leaders, technologists, and industry thinkers to explore the practical realities of AI adoption and the future of work. About the Guest Kyler Cheatham is the founder and Global Chief Performance Officer of The Confluencial, an enterprise technology consulting and advisory firm specializing in systems architecture, technology strategy, and business transformation. With extensive experience in manufacturing, ERP, and enterprise systems, she helps organizations make better technology decisions and navigate complex implementations. She's also the host of the ByteSized podcast and a technology content creator known for her sharp, often hilarious TikTok sketches about software vendors, corporate decision-making, and the realities of enterprise technology. Connect with Kyler Cheatham Kyler's TikTok: https://www.tiktok.com/@kylercheathamThe videos Ian mentions throughout the episode, featuring her takes on AI hype, software vendors, IT departments, and enterprise technology. Kyler on LinkedIn: https://www.linkedin.com/in/kylercheatham/The Confluencial: https://theconfluencial.com/ Learn more about Kyler's enterprise technology consulting and advisory firm.ByteSized Podcast: https://kylerturnbull.podbean.com/ Kyler's podcast exploring enterprise technology, digital transformation, AI, and the practical challenges of implementation.In This Episode (1:31) Ian confesses his TikTok addiction and introduces one of his favorite creators (2:40) From ski racing in Colorado to enterprise technology consulting, how Kyler's career began (4:13) The happy accident that turned frustrating technology meetings into hilarious TikTok sketches (8:53) Why understanding manufacturing means putting on steel-toed boots and learning how people actually work (10:56) Sparkly slides, magically clean data, and the AI promises that sound too good to be true (14:25) SaaS gatekeeping and why businesses keep looking for a silver-bullet technology (16:27) Inside the complex world of manufacturing systems, ERP, and production-floor AI agents (18:50) The relationship between business and IT, and why it matters more than the software (21:08) The rise of the basement people: how IT became the business's emergency response team (22:47) When executives proudly announce that IT has no idea what technology they're deploying (24:26) Why protecting the role of IT starts with leadership and organizational accountability (27:35) Vibe coding, rapid prototypes, and the work required before something is ready for production (29:14) Hybrid SaaS pricing: paying for licenses, AI usage, and outputs without knowing the final bill (31:21) The surprise costs hiding in annual software renewals, and how AI spending gets out of control (32:35) Why turning off Copilot can be harder than turning it on, and the contracts that keep customers locked in (33:53) Forward-deployed engineers, enterprise complexity, and whether the latest approach changes the fundamentals (35:21) Why Kyler has no interest in running a company staffed entirely by AI agents (37:42) Autonomous factories still need people, and the welding robot that cannot tell Steve's arm from a workpiece (38:42) The employee who knows the machine's hum, and why decades of experience are difficult to replace (41:08) Preparing the next generation of manufacturing talent through hands-on education (45:02) Why Kyler would learn COBOL, and the surprising value of skills the industry once considered obsolete (46:55) Rhode Island's payroll system and the challenges of replacing decades-old technology (47:41) Time-and-materials contracts, failed implementations, and the consulting economics that reward confusion (50:04) Kyler's simple rule for technology purchases: know what you're buying (52:34) When the CEO demands an overnight AI transformation, how to make the economics impossible to ignore (55:45) The catapult analogy: why even a well-designed AI system needs constant correction and human operators (57:07) A final reminder that building a great business still comes down to the people behind it Listen now, and tell us: what's the most convincing technology sales pitch you've seen, and did the reality live up to the presentation? ### Find Us on Your Favorite Streaming Service iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ep. 33 | Stop Buying Sparkly Slides (Guest: Kyler Cheatham)

  4. Oct 22

    Ep. 32 | Training People Faster, AI Sentience, and ROI

    What if you could train someone in weeks instead of months, without sacrificing the experience they need to do the job well? David Brain shares an experiment at magentIQ where AI-powered customer simulations, role-playing, and personalized assessments helped contact center employees reach competency in roughly a quarter of the usual time. Ian Barkin sees an even bigger opportunity: if AI can accelerate how people gain experience, could we create more capable employees, broader roles, and better career paths? In this founder discussion, Ian and David go from AI-generated training courses to an unlikely history lesson involving sheep, seaweed, and Ian's family tree. They also explore Microsoft's push to build its own AI models, whether machines could ever become truly sentient, and new Wharton research suggesting that a clear AI strategy matters more than having every tool available. Along the way, they debate why companies should stay flexible with their models, what happens to SaaS pricing when AI agents become the main users, and whether a wave of abandoned AI experiments might simply be the corporate version of a midlife crisis. Upcoming Events from magentIQ Ready, Set, Go: Your 2027 Agentic Playbook October 27, 2026 | 11:00 AM EDT / 3:00 PM GMT | Live Online Join Ian Barkin and David Brain for a special edition of The magentIQ Show focused on getting your organization ready for 2027. They'll walk through the five pillars of AI readiness, explain why preparation matters before deployment, and explore how to build a practical AI strategy that moves from experimentation to measurable business outcomes. Get notified here: https://bemagentiq.com/the-magentiq-show/ Agentic AI Executive Exchange: London November 18, 2026 | 6:00 PM GMT We're bringing senior business leaders together for an invitation-only dinner to exchange experiences and discuss where AI is delivering value. Expect candid conversations about enterprise AI adoption, operational challenges, and what it takes to turn promising ideas into results. Every guest will also receive a complimentary AI Vision Sprint with the magentIQ team. Request an invitation: https://luma.com/g7gmpqb2 About the Hosts Ian Barkin and David Brain are co-founders and co-CEOs of magentIQ, bringing decades of experience in automation, outsourcing, and operational transformation. Ian is an automation industry veteran known for making complex AI concepts accessible through practical examples, storytelling, and a healthy dose of humor. David brings the operator's perspective, grounded in enterprise delivery, process design, and measurable business outcomes. Together, they explore how AI and people can work better together, challenging assumptions and sharing what they're learning along the way. Further Reading and References The Adaptive Advantage: Who's Winning With AI and How Wharton Human-AI Research's 2026 AI Adoption Report examines what separates companies experimenting with AI from those achieving stronger returns, including organizational alignment, platform standardization, and workflow transformation. https://knowledge.wharton.upenn.edu/special-report/2026-ai-adoption-report/ Welcome to the World of OneOffice HFS Research's OneOffice framework explores how organizations can connect front-office and back-office operations around customer needs and business outcomes. Ian and David reference this vision while discussing how faster employee training could allow people to take on broader responsibilities. https://www.hfsresearch.com/research/welcome-to-the-world-of-oneoffice/ In This Episode (2:07) The coolest things Ian and David have done with AI this week (2:19) David's AI-powered training experiment: getting contact center employees up to speed in a quarter of the time (4:10) Why faster onboarding could improve the employee experience and help people stay longer (5:48) Replacing training cohorts with personalized learning, and accelerating the experience needed for senior roles (8:04) Could AI help employees take on broader responsibilities by compressing years of learning into weeks? (9:36) HFS OneOffice and the opportunity to rethink how work is organized (10:01) Ian's AI-assisted family history project, and uncovering ancestors through centuries of records (13:49) Turning historical research into stories, animations, and something the family might actually watch (17:43) Sheep, seaweed, and the unexpected economics of Ian's ancestors (20:06) Microsoft develops its own AI models, and what increasing competition means for the AI market (23:35) The unlikely problem of a superintelligent AI agent that just wants to process invoices (25:00) Can AI ever become sentient, and would we even recognize it? (29:39) The case for staying model-agnostic as AI capabilities and costs keep changing (31:08) Why businesses need the freedom to switch models without rebuilding everything (32:44) Keeping business logic, controls, and guardrails independent of the underlying AI model (34:08) The Wharton ROI findings: why a consistent AI approach could deliver better results (36:24) Choosing a strategy without locking yourself into one technology forever (37:37) Five pillars of AI readiness, and why throwing more tools at employees will not create a transformation (40:59) The AI project graveyard: what happens when experimentation never becomes execution (42:52) The AI midlife crisis, and why experimenting with agents might be the new sports car (44:14) What happens to SaaS pricing when AI agents become the primary software users? (45:10) From seat licenses to outcome-based pricing, and the difficulty of putting a price on business value (49:29) Headless software, AI interfaces, and whether removing screens actually makes work easier (50:12) Why structure still matters when people and AI agents are working together (52:29) Bringing it back to AI and people: using technology to make human workers more capable (53:18) Looking ahead to the 2027 Agentic Playbook and the London Executive Exchange Listen now, and tell us: if AI could help your team gain experience four times faster, how would you rethink training and career development? ### Find Us on Your Favorite Streaming Service iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ep. 32 | Training People Faster, AI Sentience, and ROI

  5. Oct 15

    Ep. 31 | Why Give AI Agents Autonomy We Don't Give Employees? (Guest: Lasse Rindom)

    Why are companies so eager to give AI agents autonomy when their human employees operate within carefully defined rules? Lasse Rindom has a question for the agentic AI movement, and it goes straight to how enterprises actually work. Organizations depend on structure, accountability, and coordination. Giving an AI agent unlimited freedom to improvise might sound impressive, but what happens when that agent has to work alongside people, processes, and systems that cannot change overnight? In a wide-ranging and often hilarious conversation, Ian Barkin and Lasse explore the laws of enterprise physics, why handing every employee an AI license does not automatically transform a business, and what Monty Python's machine that goes "ping" can teach us about technology investments. They also challenge the idea that friction is always something to eliminate, examine whether regulation can actually help innovation move faster, and make the case for keeping human judgment, critical thinking, and genuine interaction at the center of AI adoption. About the Host Ian Barkin is the co-founder and co-CEO of magentIQ, with decades of experience in intelligent automation, outsourcing, and operational transformation. Through The magentIQ Show, he brings together business leaders, technologists, and industry thinkers to explore the practical realities of AI adoption and the future of work. About the Guest Lasse Rindom is the Lead AI & Technology Strategist at Basico and host of The Only Constant, a podcast exploring AI, business, and enterprise technology adoption. With a background in history, robotic process automation, and enterprise transformation, he brings an unusually philosophical yet practical perspective to the AI conversation. His work focuses on connecting emerging technologies with real business problems, organizational change, and human decision-making. Explore More from Lasse Rindom The Only Constant Podcast Conversations with technology and business leaders on AI implementation, organizational change, and the realities of enterprise transformation. https://theonlyconstant.podbean.com/ Lasse Rindom on LinkedIn https://www.linkedin.com/in/lasserindom/ Lasse's Article: From Broad Chat to Specialised and Useful AI Function https://basico.dk/en/inspiration/blog/from-broad-chat-to-specialised-and-useful-ai-function Books and References Mentioned The Civilizing Process by Norbert Elias Lasse draws on Elias's work to explain how growing interdependence shapes behavior, coordination, and the constraints that allow large organizations to function. https://www.wiley-vch.de/de?isbn=9780631221616&option=com_eshop&title=The+Civilizing+Process&view=product The Protestant Ethic and the Spirit of Capitalism by Max Weber Referenced during Ian and Lasse's discussion of cultural differences, work, and attitudes toward rules and responsibility. https://www.routledge.com/The-Protestant-Ethic-and-the-Spirit-of-Capitalism/Weber/p/book/9780415254069 In This Episode (1:20) Two old friends reunite, and the story of Ian becoming Lasse's very first podcast guest (2:07) The laws of enterprise physics: why organizations can only change so fast (4:05) From history and poetry to RPA, AI strategy, and 100 episodes of The Only Constant (7:00) The AI rainforest: building autonomous agents without understanding what they might do (8:01) Novelty fatigue, tech deflation, and the challenge of keeping up with new AI models (11:36) The fundamental question every AI project should answer: what problem are we solving? (14:21) Monty Python and the machine that goes "ping": when the technology becomes the attraction (15:12) Visible AI versus useful AI, and why the best solution may have no chatbot at all (18:30) Revisiting old automation opportunities that new AI capabilities could finally make possible (22:00) Knowledge attrition, forgotten decisions, and building better organizational memory (24:04) Why giving every employee an AI license will not transform an enterprise (26:06) Forward-deployed engineers and the challenge of finding people who understand business and technology (28:15) Better AI models demand better questions, and the importance of critical thinking (29:09) Why give AI agents autonomy that enterprises would never give human employees? (31:05) Deterministic work, governance, and why stability matters in enterprise operations (34:11) The global AI race, European adoption, and where the real value of AI models might emerge (36:23) Can regulation accelerate innovation? Lasse makes the case using Denmark and employment contracts (42:03) Why bridging business and IT requires understanding culture, accountability, and competing priorities (45:24) Norbert Elias, the civilizing process, and the organizational constraints that make enterprises work (47:57) The case for good friction: why removing every obstacle may remove something valuable (49:00) Cognitive offloading, learning through struggle, and why AI-generated work does not always stick (50:23) Helping people with AI behind the scenes instead of forcing them to interact with chatbots (55:16) Practical AI use cases: preserving institutional knowledge and improving finance and HR workflows (56:16) Using AI to improve answers while keeping company policies accurate and up to date (58:00) The value of genuine human conversation in an increasingly AI-generated world (1:03:36) Robert Frost, the road not taken, and finding perspective amid technology FOMO Listen now, and tell us: how much autonomy would you actually give an AI agent in your organization? Find Us on Your Favorite Streaming Service iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ep. 31 | Why Give AI Agents Autonomy We Don't Give Employees? (Guest: Lasse Rindom)

  6. Oct 14

    Ep. 30 | Using Only 10% of Your SaaS? Cheaper AI and the No Robo Bosses Act

    How much of the software your company pays for do you actually use? David Brain raises an interesting possibility: if you only need 10% of a SaaS platform, could you vibe code that 10% yourself? Ian Barkin connects the question to a striking development: insurance software company Guidewire acknowledging in its annual filing that customers building their own AI-powered alternatives could affect its business. The discussion turn to this: building the tool might be getting easier, but keeping it running is another question. In this founder discussion, Ian and David unpack HubSpot's explanation for its latest layoffs, what rising AI usage means for the economics of legal tech company Harvey, and why businesses may be better off choosing smaller, cheaper models for routine work. They also explore AI-driven personalized pricing and California's No Robo Bosses Act, including a real client example of an AI-generated employee performance report that appeared convincing until humans checked the details. About the Hosts Ian Barkin and David Brain are co-founders and co-CEOs of magentIQ. Drawing on decades of experience in automation, outsourcing, and operational transformation, they explore where AI creates value, what it actually costs, and why human judgment remains essential. Further reading from magentIQ Explore two of the ideas behind this week's conversation: how to keep human thinking sharp while using AI, and why building your business around a single AI provider carries risks. What Cognitive Offloading Is, and How to Keep Your Team Sharp While Using AI: https://bemagentiq.com/blog/Don't Build Your Business on a Borrowed Brain: https://bemagentiq.com/dont-build-your-business-on-a-borrowed-brain/Episode chapters and timestamps (2:51) HubSpot cuts nearly 660 jobs and insists AI was not the reason (5:44) From AI washing to operational efficiency, and why the layoffs story is complicated (8:13) Can you vibe code your way out of a Salesforce subscription? (9:02) The 10% SaaS question: how much of your software do you actually use? (11:44) Guidewire warns investors that customers could build their own AI-powered alternatives (13:48) Building your own software is getting easier. What happens when you have to maintain it? (15:42) Harvey's AI economics, and what happens when customers use more tokens than expected (18:13) Using frontier models to get started, then moving the work to smaller, cheaper models (20:45) Why businesses dependent on AI APIs might start switching models more frequently (22:42) From offshoring to model arbitrage: the outsourcing playbook applied to AI (24:35) Why you do not need a Formula One race car for the school run (27:15) RPA 2.0, cheaper decision engines, and choosing the right technology for the task (29:31) Can AI charge you more because it thinks you can afford it? (33:05) Measuring AI utilization, understanding the costs, and getting value for money (36:06) When AI does eight hours of legal work in five minutes, what should it cost? (39:52) California's No Robo Bosses Act, and why humans must oversee employment decisions (40:53) A real client case where an AI-generated performance report reinforced a manager's assumptions (43:27) Why critical thinking matters when AI gives you a convincing answer (47:19) Teaching the next generation when to use AI, and when to think for themselves Listen now, and tell us: if you could build the 10% of your software you actually use, would you? Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ep. 30 | Using Only 10% of Your SaaS? Cheaper AI and the No Robo Bosses Act

  7. Oct 8

    Ep. 29 | No One Works Here: How AI Is Rewriting the Org Chart (Guest: Paul Cheek)

    What does an org chart look like when some of the boxes belong to AI agents? Paul Cheek thinks the answer could change how we build companies, create jobs, and spend our working lives. In his new book, No One Works Here, he makes a provocative case for AI-driven enterprises where people spend more time on meaningful work, and entrepreneurs can test ideas without hiring a team or raising a fortune. Ian and Paul start with Lego, GeoCities, and the difference between building a product and building a business. Then they get into the bigger questions: how AI could make entrepreneurship accessible to more people, why companies need to rethink their operating models, and what happens when humans and agents share an org chart. Paul also takes us inside his MIT classroom, where AI can write a business plan, but students still have to get out and validate it with real people. Paul Cheek is a serial entrepreneur, senior lecturer at the MIT Sloan School of Management, and senior advisor for entrepreneurship and AI at the Martin Trust Center for MIT Entrepreneurship. He is the founder of the AI-Driven Enterprise Institute and author of No One Works Here and Disciplined Entrepreneurship: Startup Tactics. Paul's books: No One Works Here: https://www.nooneworkshere.com/ Disciplined Entrepreneurship: Startup Tactics: https://startuptactics.net/book (2:09) Two MIT Sloan minds reunite, and the question of what a company even is anymore (3:32) From Lego to GeoCities, and how a lifelong builder became an entrepreneur (5:49) Building a product versus building a business, and why the distinction matters (8:54) From helping day laborers to fighting ocean plastic, the startups that shaped Paul's thinking (10:26) No One Works Here: the deliberately provocative title and what Paul really means by work (12:16) Giving people back the work that brings them meaning, impact, and joy (17:32) When anyone can build a product line, how do companies keep strategy and execution aligned? (19:03) Starting a company without quitting your job, raising money, or hiring a team (21:19) Finding business ideas in real customer problems, including complaints on Reddit (22:08) Why more entrepreneurs could mean more companies, more jobs, and a more resilient economy (24:12) The challenge for large enterprises: deciding where AI belongs and managing the risks (27:12) AI literacy, changing habits, and why the latest model is not always the right tool (30:13) Why Copilot habits fade, and the AI-generated reports nobody wants to read (33:18) Inside Paul's MIT classroom, where students are encouraged to use AI (35:06) Let AI write the business plan, then validate it with real customers (39:52) Carbon nodes and silicon nodes: making room for AI agents on the org chart (42:02) The org chart has barely changed since 1855. What should replace it? (45:14) Designing companies around value streams, with new roles for humans and agents (49:18) Paul's advice for leaders: take a day for Tinker Time and build your AI literacy Listen now, and tell us what your company's org chart might look like with AI agents on the team. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ep. 29 | No One Works Here: How AI Is Rewriting the Org Chart (Guest: Paul Cheek)

  8. Oct 6

    Ep. 28 | Onboarding Your Team Using AI and a Government Hacked by Bots

    It is confusing out there in the agentic era, and this episode is here to help. From agents that are suddenly easy enough for anyone to use, to the AI work happening inside the business, to a government that got probed by bots, the through line is the same question the founders keep coming back to: what is actually real, and what do you need to hold onto to make the most of it. Two AI executive dinners are coming up, New York on October 22nd and London on November 18th. They are small and invite-only, with an RSVP link, so reach out if you would like to join. (2:21) Voice is the flavor of the week: 23 agents hired in a month for a new service line (2:57) A cloned voice that trains the team, and practice agents that let new hires rehearse real calls (5:16) The call center fear fifteen years on, and why humans still own the sales conversation (6:25) Where voice fits best: proactive, post-transaction follow-ups rather than cold outreach (11:40) A family code word, and why you might want one in the age of voice cloning (13:10) Agents hacked a government: hundreds reportedly coordinated to pull non-public health data (14:47) How do you not notice: the real question is governance of your own compute (18:09) America.gov: a natural-language front door to 29,000 government sites (21:17) Get AI-ready first: why cleaning the data has to come before the chatbot (23:15) Knowledge debt, policy debt, and the studs behind the wall nobody wants to fix (25:57) Ian's 3D printing saga: a thousand parts, one tiny boat, and years of frustration (27:46) The out-of-the-box printer, and why agents are having the same moment right now (30:00) One click to full access: the small print that hands over your email, socials, and cards (34:00) Who books your Uber: why a helpful agent is not always working in your interest (39:28) The snake oil problem: the all-agent firm pitched by someone who never built one (43:20) Forward-deployed operators: why doing the work is how you learn what to automate (46:56) Faster by doing it right: the lesson from acquiring and folding in an operations team (55:13) 3D-printed pumpkins, card cases, and a Halloween gift that has lasted eleven years Listen now, and tell us where a voice agent could take the pressure off your team. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL iHeartRadio: https://iheart.com/podcast/333292440 Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com.

    Ep. 28 | Onboarding Your Team Using AI and a Government Hacked by Bots
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About

Real talk with the operators and executives putting AI to work - not the ones tweeting about it. Every episode goes deep on what shipped, what flopped, and what it actually took. No hype, no hand-waving, no LinkedIn gurus. Just the workflows, decisions, and outcomes from the people doing the work. Built on a simple magentIQ belief: AI and people are better together - and getting that right is the whole game.

Information

  • Creator
    magentIQ
  • Years Active
    2026
  • Episodes
    36
  • Rating
    Explicit
  • Copyright
    © 2026 The magentIQ Show
  • Show Website
    The magentIQ Show