The magentIQ Show

The magentIQ Show Ep. 10 | The Biggest AI Model Is Rarely the Right One, AI Budgets Are Not Adding Up, and Speed Is Not a Strategy

59 min · Gestern
Episode The magentIQ Show Ep. 10 | The Biggest AI Model Is Rarely the Right One, AI Budgets Are Not Adding Up, and Speed Is Not a Strategy Cover

Beschreibung

Ian Barkin and David Brain go behind the scenes on the agentic platform they have been building, and dig into why the biggest model is rarely the right one, why this year's AI savings are quietly funding next year's budget, and why going faster will not fix a process that was never designed for AI in the first place. A practical, pattern matching conversation from two people who have lived through this cycle before. (0:00) Why there is nothing safe and low hanging in AI transformation, and how big, bold, brash expectations slow you down (0:55) Founders journal: black t-shirts, decision fatigue, GLP-1s, and the great tailor shortage (10:54) The Bain study: AI is not delivering the expected impact, and next year's budget is built on savings that never showed up (16:08) The underpants gnomes problem: use AI, question mark, value is not a plan (21:30) Capturing the thinking, not just the steps: David on building an agentic platform rooted in process re-engineering (28:28) The 10x myth: why companies keep trying to 10x a broken process instead of redesigning it (30:49) Why the forward deployed engineer puts too much on one set of shoulders (38:45) Orchestrating the right model: vendor lock-in, and why you don't need a McLaren to drive down the street (40:31) Small and custom language models: lower cost, lower energy, and good enough for most real work (43:49) Chinese and open source models, the nine month gap, and the regulation that may be coming (48:54) Recursive, self improving models and why a human master architect still has to stay in the loop (53:07) The hype versus reality gap, told through the Siri that won't tell you if it's going to rain Listen now, and send us your questions. We work through this stuff too. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 [https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951] Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL [https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL] iHeartRadio: https://iheart.com/podcast/333292440 [https://iheart.com/podcast/333292440] Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com [info@bemagentiq.com].

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Episode The magentIQ Show Ep. 10 | The Biggest AI Model Is Rarely the Right One, AI Budgets Are Not Adding Up, and Speed Is Not a Strategy Cover

The magentIQ Show Ep. 10 | The Biggest AI Model Is Rarely the Right One, AI Budgets Are Not Adding Up, and Speed Is Not a Strategy

Ian Barkin and David Brain go behind the scenes on the agentic platform they have been building, and dig into why the biggest model is rarely the right one, why this year's AI savings are quietly funding next year's budget, and why going faster will not fix a process that was never designed for AI in the first place. A practical, pattern matching conversation from two people who have lived through this cycle before. (0:00) Why there is nothing safe and low hanging in AI transformation, and how big, bold, brash expectations slow you down (0:55) Founders journal: black t-shirts, decision fatigue, GLP-1s, and the great tailor shortage (10:54) The Bain study: AI is not delivering the expected impact, and next year's budget is built on savings that never showed up (16:08) The underpants gnomes problem: use AI, question mark, value is not a plan (21:30) Capturing the thinking, not just the steps: David on building an agentic platform rooted in process re-engineering (28:28) The 10x myth: why companies keep trying to 10x a broken process instead of redesigning it (30:49) Why the forward deployed engineer puts too much on one set of shoulders (38:45) Orchestrating the right model: vendor lock-in, and why you don't need a McLaren to drive down the street (40:31) Small and custom language models: lower cost, lower energy, and good enough for most real work (43:49) Chinese and open source models, the nine month gap, and the regulation that may be coming (48:54) Recursive, self improving models and why a human master architect still has to stay in the loop (53:07) The hype versus reality gap, told through the Siri that won't tell you if it's going to rain Listen now, and send us your questions. We work through this stuff too. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 [https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951] Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL [https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL] iHeartRadio: https://iheart.com/podcast/333292440 [https://iheart.com/podcast/333292440] Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com [info@bemagentiq.com].

Gestern59 min
Episode The magentIQ Show Ep. 9 | The Velocity Gap: Why AI at Home Races Ahead While AI at Work Stalls (Guest: Phil Fersht) Cover

The magentIQ Show Ep. 9 | The Velocity Gap: Why AI at Home Races Ahead While AI at Work Stalls (Guest: Phil Fersht)

People can plan a week of meals, diagnose an ailment, and draft a proposal with AI on a Sunday, then walk into work on Monday and find everything still stuck in silos, legacy systems, and tribal knowledge. In Episode 9 of The magentIQ Show, Ian Barkin sits down with industry analyst and icon Phil Fersht to name that dissonance, the velocity gap, and to talk honestly about why so few enterprises are closing it, what real AI transformation actually demands, and why authentic human voice matters more than ever in an age of AI slop. Phil Fersht is widely recognized as one of the world's leading analysts on reinventing business operations to exploit AI and global talent. He is the founder and CEO of HFS Research, the analyst who authored the first report on Robotic Process Automation in 2012, and the voice who coined OneOffice, trademarked the Generative Enterprise, and more recently framed the rise of Services-as-Software. He is also the author of Horses for Sources, the most widely read blog in the global services industry, now in its nineteenth year, and a three time Analyst of the Year. Here is what Ian and Phil unpack: * Why the velocity gap exists, the widening distance between how fast people adopt AI personally and how slowly their organizations actually move, with only a small fraction of the global 2000 making real headway * Why LLMs are not AI transformation, and why meaningful change requires CEO and COO sponsorship and a wholesale rewiring of people, data, and process rather than incremental tweaks * Why authentic voice is becoming a differentiator as AI slop floods inboxes and feeds, and how to use these tools for research and structure without losing the soul of what you write * Why the future of services belongs to nimble, process led, outcome driven firms, and why being close to the operation beats dropping a full stack engineer into a problem The throughline is energizing rather than alarming. The organizations that win will be the ones whose leaders treat AI as a fundamental rethink of how the business runs, stay close to their processes, and keep real human judgment and voice at the center. The opportunity to leap ahead is wide open, especially for the small and nimble. Listen now and tell us how wide the velocity gap looks in your own organization. Resources from Phil Fersht: Podcast, From the Horse's Mouth, Intrepid Conversations with Phil Fersht: * Apple: https://podcasts.apple.com/us/podcast/from-the-horses-mouth-intrepid-conversations-with/id1769638427 [https://podcasts.apple.com/us/podcast/from-the-horses-mouth-intrepid-conversations-with/id1769638427] *  Spotify: https://open.spotify.com/show/7uS2O3N9JdQnpWLT22qy5O [https://open.spotify.com/show/7uS2O3N9JdQnpWLT22qy5O] *  YouTube: https://www.youtube.com/@FromTheHorsesMouthPod [https://www.youtube.com/@FromTheHorsesMouthPod] Blog, Horses for Sources: https://www.horsesforsources.com/ [https://www.horsesforsources.com/] Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com [info@bemagentiq.com].

23. Juni 202658 min
Episode The magentIQ Show Ep. 8 | Lessons Not Learned: Why Unlimited Tokens Backfire, the Process Map You Cannot Skip, and the Myth That Speed Is a Strategy Cover

The magentIQ Show Ep. 8 | Lessons Not Learned: Why Unlimited Tokens Backfire, the Process Map You Cannot Skip, and the Myth That Speed Is a Strategy

The company burning billions on AI is somehow getting less done. In Episode 8 of The magentIQ Show, Ian Barkin and David Brain dig into why, working through the mistakes the AI era keeps repeating even though most of them were supposed to be learned a decade ago. Here is what Ian and David unpack: * Why the era of unlimited tokens is turning, and why disciplined AI is proving cheaper and more productive than handing everyone a blank cheque to use as much as possible * Why choosing the tool before defining the problem still trips teams up, and why a demo is no substitute for knowing where you are and where you actually want to go * Why expecting staff to 10x themselves overnight is a tall order, and why the forward deployed engineer cannot be a whole team of specialists squeezed into one person * Why speed for its own sake is not a strategy, and how the old trade off between time, cost, and quality still holds no matter how fast the tools have become The throughline is encouraging rather than cautionary. The teams that win are the ones that map where they are, agree on the outcome they want, choose the right tool for the job, and give their people the design time and support to do it well. Enthusiasm builds momentum, but pairing it with context and a little hard won history is what turns an AI project into a real result. Listen now and tell us which lesson you see playing out most in your own organization. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 [https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951] Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL [https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL] iHeartRadio: https://iheart.com/podcast/333292440 [https://iheart.com/podcast/333292440] Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com [info@bemagentiq.com].

17. Juni 202648 min
Episode The magentIQ Show Ep. 7 | The Work Slop Problem: Why You Still Own Everything AI Makes for You (Guest: Andreas Welsch) Cover

The magentIQ Show Ep. 7 | The Work Slop Problem: Why You Still Own Everything AI Makes for You (Guest: Andreas Welsch)

AI can draft a report in seconds, but it cannot put its name on it. In Episode 7 of The magentIQ Show, Ian Barkin sits down with Andreas Welsch, ten year AI veteran, LinkedIn Learning instructor, and author of two books written entirely by hand. Their conversation cuts past the hype to a question every leader is now living with: when output is effortless, how do you keep the quality, the judgment, and the accountability that make it worth anything at all? Here is what Ian and Andreas unpack: * What work slop really is, how AI output that just shifts the labor and the bottleneck onto whoever receives it, and why you are never off the hook for the quality of what you ship * Why staying in the loop matters, drawn from Andreas's own experience letting AI build an app unsupervised and ending up with something he could not understand or trust * How to enable people to use AI well, with real training and a learning curve, rather than throwing a tool over the fence and expecting productivity to appear * Why the human edge becomes the differentiator as everyone converges on the same tools and data, and why people remain the heart and soul of a business The throughline is refreshingly practical. AI is a powerful new tool, not a substitute for craft, and the leaders who win will be the ones who pair it with real expertise, keep people close to the work, and treat quality as something they still own. Smart, sharp, and hype free. Resources from Andreas Welsch: LinkedIn Learning courses: https://www.linkedin.com/learning/instructors/andreas-welsch Books:  * The HUMAN Agentic AI Edge: https://intelligence-briefing.com/human-agentic-ai-edge/ * AI Leadership Handbook: https://intelligence-briefing.com/ai-leadership-handbook/ Listen now and tell us how you are keeping quality and accountability in your own AI workflows. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 [https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951] Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL [https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL] iHeartRadio: https://iheart.com/podcast/333292440 [https://iheart.com/podcast/333292440]

11. Juni 202640 min
Episode The magentIQ Show Ep. 6 | Real AI Use Cases, a Six Figure Win, and What Doing AI Right Actually Looks Like Cover

The magentIQ Show Ep. 6 | Real AI Use Cases, a Six Figure Win, and What Doing AI Right Actually Looks Like

The whether of AI is settled, or at least that's what our webinar audiences told us. What people are hungry for now is the how. In Episode 6 of The magentIQ Show, Ian Barkin and David Brain answer the questions that came straight from the people in their recent webinars, share fresh survey data on where AI adoption really stands, and walk through a client who saved six figures a year by building AI in the right way, with people firmly in the loop. In this episode, Ian and David unpack: * What the latest survey data reveals about AI maturity, and why the sharp jump into production over six months is a genuinely positive signal * Why token maxing a model to do a job a simple automation could handle is bringing a bazooka to a knife fight, and how to match the tool to the task * The John Briggs story: how one founder saved 150 to 200 thousand dollars a year and built a smarter client portal by partnering rather than going it alone * How confidence scores and human QA keep people in the loop, so you trust AI's answers without losing the ability to check its work Find out why the operators who win are the ones who start where the pain is, choose the right tool, design for outcomes, and build AI and people to work better together. The opportunity is real, the wins are already happening, and the path from why to how is more achievable than the noise would have you believe. Listen now and tell us how you are moving from why to how in your own organization. Find us in your favorite streaming service: iTunes: https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951 [https://podcasts.apple.com/us/podcast/the-magentiq-show/id1896570951] Spotify: https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL [https://open.spotify.com/show/033f2oKxnFr5fmcpdSHjSL] iHeartRadio: https://iheart.com/podcast/333292440 [https://iheart.com/podcast/333292440] Got a perspective worth sharing? We are always looking for guests. Reach out at info@bemagentiq.com [info@bemagentiq.com].

9. Juni 20261 h 11 min