Proton CTO Bart Butler makes the case that the privacy company is really selling trust, then traces how encryption, Swiss jurisdiction, and a foundation-controlled ownership model are meant to keep that promise intact. The conversation turns from corporate ideals to harder tests: FBI requests routed through Switzerland, looming European surveillance laws, child-safety demands, age verification, and the problem of building AI tools without surrendering user control.

Bruce Daisley talks with organizational psychologist Rob Briner about the workplace ideas companies cling to despite thin evidence, from engagement surveys and psychological safety to culture change and growth mindset. Their debate circles a simple demand: stop reaching for fashionable tools before defining the problem you are actually trying to solve.

Molly Graham talks with investor and former TaskRabbit CEO Stacey Brown-Philpott about treating religious faith as a real decision-making framework at work, not a private belief to be hidden from professional life. Their conversation moves from fundraising and leadership to boundaries, community, and the risks of making work the sole source of meaning.

A veteran product leader turned money coach talks through the strange blind spot of affluent tech workers: people who optimize everything at work while neglecting taxes, concentrated stock risk, estate planning and the mechanics of compounding. The conversation moves from his own career pivot to the emotional realities of sudden wealth, the limits of traditional financial advising and the practical habits that keep high earners from leaving fortunes on the table.

A frantic day of AI releases sharpened the industry’s new fault line: not just which model scores highest, but which gets close enough for far less money. Weighing OpenAI’s new Sol, Terra and Luna against Anthropic, xAI and Meta, the conversation argues that price-performance, not raw benchmark supremacy, may decide where people actually work AI into coding, finance and everyday software tasks.

Nilay Patel and Peter Kafka treat Comcast’s breakup as the latest collapse of the old “content plus pipes” fantasy, tracing how a generation of telecom-media mergers failed to turn internet access into cable TV all over again. Their conversation follows the money from NBCUniversal and Versant to Peacock, sports rights, and broadband monopolies, asking what media companies can still own that the internet has not already commodified.

A wide-ranging AMA traces Gergely Orosz’s shift from Uber manager to independent publisher, then circles through AI hiring, code quality, startup culture and the engineers still finding leverage in a choppy market. Along the way, he argues that AI is less a doctrine than a tool, and that careers are future-proofed less by credentials than by proximity to relevant work.

Molly Graham talks with executive recruiter Ify Walker about the "work twisties," the destabilizing loss of purpose and self-trust that can follow grief, burnout, or a career that no longer fits. Their conversation traces how Walker rebuilt her inner compass and why radical honesty matters in hiring, leadership, and figuring out where you actually belong.

At Cannes, two longtime UTA executives explain how influencer careers became full-scale media companies, built through strategy meetings, product launches, and careful management of platform risk. The conversation treats creators less as internet personalities than as entrepreneurs navigating algorithms, brand deals, physical goods, and the looming pressures of AI.

A recruiter and founder unpacks a report drawn from conversations with 18 chief product officers, tracing how investor-backed companies still mistake product for delivery rather than strategy. The discussion lingers on reporting lines, commercial accountability and the organizational habits that quietly doom product leaders before they can create value.

At Cannes, Digitas North America CEO Amy Lanzi argues that advertising’s AI boom resembles the overhyped promises of programmatic, with platforms selling automation while agencies and brands still need human judgment, strategy, and data fluency. The conversation also traces the rise of creators as full-fledged marketing businesses and the growing fight over who controls the relationship between brands, audiences, and the platforms in between.

Natalia, Every’s head of consulting, describes how AI agents are moving from novelty to everyday infrastructure: managing sales ops, triaging email, building family care systems, and turning research into personalized learning tools. The conversation also argues for a clearer division of labor, with human judgment and off-the-shelf software still essential even as custom agents absorb administrative work.

In a live TED conversation, Molly Graham makes the case for careers built through risky leaps rather than orderly promotions, arguing that fear, awkwardness, and reinvention are often signs of growth. She reflects on scaling fast-moving companies, the value of asking naive questions, and the need for leaders to build environments where people can do their best work.

Roger Daley returns to discuss how Blackstone’s pandemic-fueled rise led to its merger with Weber, and what it takes to fuse a fast, entrepreneurial upstart with a storied but siloed legacy brand. The conversation ranges from antitrust limbo and tariff pressures to creator marketing, overseas manufacturing, and the culture overhaul required to run one company with two very different identities.

Ford CEO Jim Farley talks with Joanna Stern about the company’s risky effort to rebuild its electric-vehicle strategy around cheaper, simpler cars, while arguing that software, tariffs and Chinese competition are reshaping the entire auto business. The conversation widens into Farley’s view that America’s bigger crisis is not just EV profitability but a hollowed-out culture that undervalues factory, trade and emergency-service work.

Edwin Chen, the founder of data-labeling and evaluation firm Surge, describes training frontier models as a kind of schooling for AGI, where benchmarks now stretch from middle-school math to research-level discovery. The conversation widens into a debate over whether AI should optimize for human flourishing or the same engagement traps that warped social media, and what deeply personal data may be worth in teaching models taste, judgment, and voice.

Harvard Business School professor Linda Hill argues that innovation is less about lone brilliance than about building cultures, roles, and routines that let people co-create, experiment, and scale new ideas. She lays out why leaders must make space for others, bridge silos, and act more like wayfinders than visionaries with a fixed map.

HBR on Leadership signs off after more than 150 episodes, with host Hannah Bates announcing the show’s pause and a renewed focus on HBR IdeaCast and other projects. The farewell doubles as a thank-you to the production team and listeners who made the past four years of leadership conversations possible.

AWS chief Matt Garman argues that AI will reorder white-collar work rather than erase it, even as Amazon automates more tasks and trims parts of its own workforce. The conversation ranges from college AI degrees and shaky labor data to enterprise adoption, data center backlash, and the question of whether efficiency gains create new jobs fast enough.

A former Facebook executive revisits the company’s famous ethos of moving fast, arguing that its real aim was rapid learning rather than reckless breakage. The conversation traces how psychological safety, technical guardrails, and a founder’s temperament shape a culture that can scale without turning failure into blame.