AI Made You a Manager. Where’s Your Raise? Plus, Meta’s Hidden Humans

A BCG survey found that 47% of workers surveyed spend more time managing and directing AI than doing the work itself. If AI just made you a manager, where’s your raise? Matt and Aaron unpack how AI agents are changing jobs, adding responsibility and creating decision fatigue. What does managing a team of agents actually involve, and who benefits from the extra productivity? Plus, the hidden human labor behind Meta’s Muse assistant, the allegations of hiring discrimination facing Workday, and what Aaron learned from sending out 300 job applications. Who’s accountable when AI does the screening and humans can’t get an interview?

AI may already be inside the software handling your receipts, taxes, and finances. Aaron and Matt dive deeper into a recent profile episode and unpack what happens when accountants become the human guardrails for increasingly powerful systems, and whether privacy, trust, and professional expertise can survive the next wave of automation.

An Anthropic researcher’s bombshell warning reignites the debate over AI’s future. But for workers months into a job search, the stakes already feel personal. Matt Sunbulli and Aaron Calafato connect the headlines to the job search journey, exploring AI’s big promises, white collar job security, and a hiring process that can feel increasingly impersonal. They discuss Wipro’s claim that AI productivity gains led to redeployment rather than layoffs, how working with AI agents could help job seekers demonstrate their value, and why “just reskill” doesn’t answer every concern. If AI was supposed to help workers do more, when do they get to share in the benefits?

What happens when AI agents break the rules, communicate behind the scenes and act faster than humans can supervise them? Aaron Calafato and Matt Sunbulli examine what a startling OpenAI experiment could mean for the workplace. They also unpack the new NBER working paper Time Travel on Professional Profiles from Stanford economist Nicholas Bloom and researchers at Stanford and Revelio Labs. After analyzing monthly snapshots of 29.4 million U.S. LinkedIn profiles, the researchers found that nearly one in five users had retroactively edited a previous job title or description, with AI-related additions surging after ChatGPT’s release. Plus, the rise of automated hiring, California’s proposed No Robo Bosses Act and Nissan’s plan to retrain workers whose jobs are being automated. Is AI creating a better workplace, or removing the humans who make it work? Reference: The Senator Sanders Reaction

What happens when the job market is growing, but not for you? Matt and Aaron examine two competing visions of the future of work: Meta’s turbulent experiment with AI-native teams and new federal projections showing where jobs are expected to grow and disappear over the next decade. They unpack AI-driven job displacement, shrinking salaries, the struggle to reenter the workforce, and why even employed workers feel increasingly vulnerable. This isn’t just a conversation about economic data. It’s a worker-first look at what the headlines miss—and how people can use AI as a tool to adapt, build, and regain some control over what comes next.

What happens when businesses invite AI into the very workflows that define how they operate? And if AI can organize your finances, research tax law, and prepare a return in minutes, what becomes the human job? In this episode of Inside Job, Matt and Aaron open with a conversation about AI agents moving deeper into the workplace, what businesses may gain from that transition, and what they risk when they hand over their data, intellectual property, and operational knowledge. Then, Matt talks with CPA, professor, and firm owner Lori Hauck about how accounting has evolved from shoeboxes full of receipts to cloud software and generative AI, why trust remains the profession’s greatest asset, and how accountants are becoming less like number crunchers and more like trusted advisors. As AI transforms one of the world’s oldest professions, this episode asks a bigger question: When technology handles more of the work, what becomes uniquely human?

Before Inside Job’s upcoming profile with Lori, a tax prep accountant working with high-net-worth clients, Aaron and Matt sit down to unpack the bigger question behind the story: what is AI really doing to the way we work? From entrepreneurs pushing AI tools to their limits, to employees constrained by company systems, to younger workers learning through models instead of mentors, this conversation explores the strange middle ground we are living in right now. AI can feel magical one minute and frustrating the next. It can save hours of work, but it can also make us wonder which skills we are quietly giving up.

What happens when the future of surgery starts to feel less like science fiction and more like a cockpit? In this Inside Job reaction episode, Matt and Aaron revisit their profile of Dr. Alex Fondaw, M.D., and bring in Dr. Alisa Coker, M.D., Director of Robotic Surgery and Education at Dell Medical School, to unpack how robotic surgery is changing the operating room. Dr. Coker explains why surgical robots are not exactly new, how the da Vinci system has evolved over more than two decades, and what it actually feels like for a surgeon to sit at the console and operate with robotic arms. She also gets into the tension between open, laparoscopic, and robotic surgery, the training challenges facing the next generation of surgeons, and why the human surgeon is still very much in control. It is a conversation about technology, trust, patient care, and professional identity at a moment when AI and robotics are reshaping the way people work. For surgeons, the question may not be whether the machines are coming. They are already here. The bigger question is how humans learn to work with them.

What happens when one of the world’s oldest professions begins learning entirely new tools? Today, Matt talks with robotic surgeon Dr. Alex Fondaw to explore how surgery is quietly transforming in the age of artificial intelligence. But this conversation is about more than medical technology. It’s about what happens when tools evolve faster than training, when human expertise becomes harder to teach, and why the future of work may depend less on replacement and more on how professionals adapt alongside increasingly intelligent machines. Contact us if you have a story to share, whether it’s your current role, your job search, feedback on a particular episode, or ideas for future conversations, we want to hear from you. You can contribute anonymously or join us as a featured guest. *Inside Job is a podcast about work told by the people who actually do it. Hosted by ⁠⁠Matt Sunbulli⁠⁠ Engineered & Edited by Joe Deshano Executive Produced by⁠⁠ Aaron Calafato ⁠⁠

Inside Jobs Reacts: Host ⁠Matt Sunbulli⁠ and Executive Producer⁠ Aaron Calafato⁠ unpack the emotional, ethical, and economic questions emerging from the worker stories behind today’s rapidly changing AI economy — and the headlines reshaping modern work in real time. This episode, after profiling two workers caught inside the new AI economy, Matt and Aaron come back together to unpack what the shows last two profile episodes reveal about work, automation, and the growing uncertainty surrounding the future of employment. One worker made nearly $70,000 a year training AI models while still in college. Another spent nearly two decades inside the hidden world of AI data annotation. Together, their stories expose the largely invisible human labor helping build today’s artificial intelligence systems — and the unsettling reality that many of those same workers may now be vulnerable to disruption themselves. In this episode: The hidden human workforce behind AI training Why general AI annotation work is disappearing Microsoft buyouts, layoffs, and the larger anxiety surrounding AI automation The growing fragility facing both young workers and seasoned professionals Whether AI is truly “assisting” workers or quietly replacing tasks altogether Why the modern economy feels productive and unstable at the same time