No One Works Here: What AI Actually Changes About Work

MIT built a job title from scratch because Paul Cheek didn't fit any that existed. Now he's ranking the S&P 500 on AI maturity, and the results may surprise you. We get into why AI literacy has to come before AI strategy, why the best managers may not be the ones who make you feel good, and why human fit still matters in a world full of capable agents. Paul also breaks down the four types of AI adopters he found in corporate America and why some of the loudest companies about AI are doing the least. **Key takeaways:** - Why "no one works here" doesn't mean nobody has a job, it means the nature of work has changed - The four characteristics Paul uses to evaluate any AI opportunity - Why AI literacy has to come before AI strategy, governance, or data cleanup - The real difference between a personal AI swarm and shared agency across a team - Why good middle management may be the most underrated skill in an AI-native organization - What Paul's S&P 500 AI maturity research revealed about the gap between what leaders say and what their companies actually do - Why human fit and self-awareness still matter even as AI absorbs more of the work - Why the biggest competitive risk isn't AI replacing workers, it's AI-native companies replacing entire organizations Connect with Jason: https://www.linkedin.com/in/jasonbaumgarten/ Email the show here: jason@fithappens.fm 00:00 Cold open: the MIT job that didn't exist 01:11 Introducing Paul Cheek and the book's premise 02:16 Paul's early years and entrepreneurial roots 04:50 Becoming MIT's first hacker in residence 07:04 The real success rate of startups 10:43 Why the unemployed are learning AI fastest 13:42 What Paul brings to the classroom that a PhD doesn't 16:40 Boards, risk, and the risk of not using AI 19:32 Reinventing work instead of automating the cow paths 20:22 Why AI actors demand organizational redesign 22:13 Adjusting the bar for AI agents versus humans 23:13 The $225 million simulation and the phishing twist 25:24 From doing the toil to designing the intent 27:05 The four characteristics for spotting real AI opportunities 29:48 Why AI literacy must come before AI strategy 33:13 Automation versus real transformation 34:08 The real threat: AI-native firms replacing others in the market 36:07 Personal swarm versus shared agency 39:22 Why human fit still matters in an AI economy 43:40 Governance as the number one human role 46:35 Managing a fleet of agents versus managing people 47:36 Why good middle management is the most underrated skill 55:09 Where friction should disappear, and where it shouldn't 62:00 Rating the S&P 500 on AI maturity 69:23 What boards get wrong about AI literacy 73:35 Short-term ROI thinking versus scalable intelligence 78:11 Speed round with Paul Cheek