I talk with Greg Matson, Senior Vice President and Head of Marketing and Products at Solidigm, about the storage infrastructure powering the AI boom. We get into why AI training and inference require massive amounts of data, how GPUs, SSDs, and data centers work together, and why storage can't be an afterthought for companies building enterprise AI.

We also discuss the scale of today's AI data center buildout, how Solidigm is using AI internally, and what this means for the future of work, education, and the skills people will need in an AI-first world.

June 19, 2026: Anthropic's Fable 5 shutdown appears to be tied to SK Telecom, Project Glasswing, Amazon researchers, the White House, David Sacks, and a dispute over whether Anthropic should fix or de-deploy the model. Fortune 500 companies just hit record revenue, profit, revenue per employee, and profit per employee while shrinking headcount for the second year in a row, raising a bigger question about productivity gains without job growth. New data from LV8 founder Griffin Hadrill shows AI-generated creative ads are underperforming human-made ads by 3 to 5 times, which is a reminder that originality, emotional connection, and human judgment still matter.

Greg Matson, Senior Vice President and Head of Marketing and Products at Solidigm, joins me to explain why storage is one of the most important and overlooked parts of the AI infrastructure boom. We talk about what actually happens when you use tools like ChatGPT or Claude, why AI training and inference require massive amounts of data, and how GPUs, SSDs, and data centers work together behind the scenes.

Greg also breaks down why AI data centers are being built at such a massive scale, how much storage a single GPU can require, why enterprise AI depends on modern data infrastructure, and how Solidigm is using AI internally to improve forecasting, engineering, software testing, and product development. We also get into what this means for the future of work, education, and the skills people will need in an AI-first world.

This episode is sponsored by Solidigm.

June 18, 2026: Companies are starting to count the real cost of AI after two years of broad experimentation, from rising token bills to the higher wage premiums commanded by AI-skilled workers. Then I look at Senator Ruben Gallego's push to investigate ghost jobs and whether AI-powered hiring platforms are distorting the labor data policymakers rely on. Finally, I break down Wall Street's hiring dilemma: AI can automate junior-level work, but it cannot replace the apprenticeship that develops future rainmakers, dealmakers, and senior leaders.

June 17, 2026: Anthropic's Claude Fable 5 and Mythos models were pulled after a government directive raised concerns about jailbreak risks, creating a wake-up call for companies building critical workflows on frontier AI models they don't actually control. Then I get into Meta's AI transformation struggles, including layoffs, employee reassignments, low morale, surveillance concerns, and what leaders can learn from one of the most visible AI change-management failures so far. Finally, I break down PwC's 2026 Global AI Jobs Barometer, which shows that AI isn't collapsing the labor market but splitting it into two tracks: roles where AI increases the value of human judgment, and roles where AI makes work easier for non-experts to perform.

Kelle Fontenot, Chief Digital Officer at KPMG, joins me to talk about how one of the world's largest professional services firms is embedding AI into the way work gets done. Kelle shares how KPMG is approaching enterprise AI adoption through its AIQ program, why AI requires close partnership between digital, HR, technology, and the business, and what it takes to drive change across 250,000 people globally.

We also get into the realities of AI adoption inside a large, highly regulated organization: digital teammates, AI agents, tool overload, trust, security, and why traditional training alone doesn't change behavior. Kelle offers a practical look at how leaders can move beyond experimenting with AI and start making it part of the everyday flow of work without losing human judgment along the way.

June 12, 2026: SpaceX made history with the largest IPO ever recorded, raising $75 billion in its NASDAQ debut and instantly becoming one of the most valuable companies in the United States. But under the hood, this isn't just a rocket company anymore. It's a bet on Starlink, reusable rockets, and xAI's massive AI infrastructure. Then I get into the first-ever appearance of OpenAI, Anthropic, and Google DeepMind leaders at the G7 Summit, and what it means when the most powerful AI companies in the world are now part of global policy conversations. Finally, I break down Jeff Bezos' $12 billion raise for Prometheus, a new company building an "artificial general engineer" that could reshape manufacturing, aerospace, pharma, defense, and the future of high-skill knowledge work.

June 10, 2026: Palantir CEO Alex Karp is warning tech leaders that bragging about AI-driven layoffs is a major political mistake and could fuel backlash against the entire industry. Then I get into a new Reuters/Ipsos poll showing that 53% of Americans fear AI could put them or someone in their household out of work, which means AI job anxiety is no longer a fringe concern. Finally, I break down the "great flattening," with new data showing that 41% of employees say their companies trimmed management layers last year, and why eliminating too much middle management could create a serious leadership pipeline problem for the future.

June 9, 2026: Meta is investing $115 million into America's Workforce Academy to train electricians, welders, plumbers, fiber technicians, and other skilled tradespeople for the AI infrastructure boom. This isn't charity, it's a talent pipeline for the data centers, wiring, fiber, and physical systems AI depends on. Then I get into Anthropic's release of Claude Fable 5, its most powerful publicly available AI model yet, and what it means for trust, accuracy, pricing, and accountability as AI moves deeper into business operations.

We have all worked at a place where we felt like just another number in a spreadsheet. It is incredibly frustrating when you offer feedback that seems to vanish into a black hole of corporate bureaucracy. But what if your company actually treated your voice like a strategic roadmap for the future?

In this episode, DJ Casto, the EVP and Chief Human Resources Officer at Synchrony, joins us to explore how his team transformed their culture to become the number one best place to work in 2026. DJ shares the secrets behind their decade-long journey of separation from GE Capital and how they climbed the rankings by anchoring their identity in the concept of trust.

We dive deep into their philosophy of co-creation, where active listening through quarterly pulse surveys and roundtables allows employees to directly design the culture they want to inhabit. Discover how Synchrony applies agile software principles to HR by launching minimal viable products for benefits like personalized wellness coaches and on-site therapists to see what truly resonates with the workforce.

We also tackle the modern challenge of AI, moving past the doom and gloom to discuss how technology can actually unlock human creativity and fulfill more enriched roles. You'll learn how to foster employee accountability through a focus on critical experiences rather than rigid job paths. This episode unpacks how you can build a high-trust organization where continuous improvement is a lifestyle rather than a one-time goal.

Watch the full video on YouTube

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