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.

At Cloaked, head of product Kyler describes how an internal AI “harness” evolved from a personal fix for prompt-copying drudgery into companywide infrastructure installed on every managed computer. The conversation traces a distinctly AI-native operating model, with Slack agents for nontechnical staff, coding agents for power users, and layered guardrails designed to make automation useful without making it reckless.

Patreon CEO Jack Conte says the company has outgrown its old role as a payments layer and is rebuilding itself as a discovery, hosting and community platform for creators squeezed by algorithmic feeds, Apple’s fees and AI-fueled slop. The conversation ranges from social media’s failures to the payment and moderation pressures of running a creator business that now competes more directly with Instagram, TikTok and Substack.

Anthropic engineering leader Fiona Fung describes a software world where code is abundant, initiative matters more than syntax, and managers rely on AI to track quality, feedback, and the work itself. The conversation traces how engineering, product management, and team culture are being remade by agents, even as loneliness, fear, and accountability become harder problems to solve.

Gary Shteyngart revisits the eerie prescience of Super Sad True Love Story and traces how a culture of ranking, optimization, and screen-mediated life has hollowed out intimacy and pleasure. The conversation turns toward beauty, craft, and conviviality as stubborn forms of resistance to a joyless, hyper-efficient age.

A weekend scramble over Anthropic’s newly released Claude Fable 5 became a test case for how the Trump administration may regulate AI: through formal safety policy or through panicked, personalized power. Nilay Patel and Verge reporter Hayden Field trace the model’s abrupt shutdown, the export controls that followed, and the industry’s growing fear that political risk now sits alongside technical risk.

Rob Ayers traces how deployment practices evolved from weekly release boards to progressive delivery, arguing that feature toggles, roll-forwards, and platform teams do more to reduce risk than ritualized rollbacks. The conversation also untangles GitOps beyond its name, surveys Kubernetes at enterprise scale, and considers how AI-driven code velocity may shift CI/CD from speed toward safety.

GitHub’s Kyle Daigle describes a software world remade by coding agents, where pull requests and commits are surging, nondevelopers are building apps, and maintainers need new controls to keep pace. The conversation follows the business and product consequences of that shift, from model routing and token costs to the long game of training tools on a developer’s habits and context.

Leadership coach Anne Morriss argues that hard organizational problems persist not because they are unsolvable, but because leaders misdiagnose them, underinvest in trust and storytelling, and wait too long to act. She lays out a five-step approach that starts with humility and buy-in, then uses speed as the final mechanism for turning intention into real change.

As AI coding tools shift from one-off prompts to self-directed automations, the conversation breaks down loops in plain English: scheduled tasks, hooks and goal-based agents that keep working until a job is done. Working through Claude Code and Codex, it also makes the case for guardrails, isolated workspaces and clear validation before handing autonomous agents the keys.

At Platformer’s first live show, Casey Newton and guests take stock of AI’s contradictory role in the workplace: a source of anxiety, a generator of strange new job titles, and a tool that may make software creation radically more personal. The conversation moves from Atlassian’s enterprise “context graph” to Eugenia Kuyda’s vision of companions and bespoke apps, tracing how automation may reshape both office work and the products people use every day.

Molly Graham talks with former Stripe COO Claire Hughes Johnson about the hidden chaos inside celebrated careers and breakout companies, where outages, doubt, and bad bets sit alongside growth. Their conversation turns on how to tell the difference between a difficult stretch worth enduring and a situation that demands an exit.

Product leader turned creator Peter Yang talks through leaving Roblox for a self-funded solo run, trading calendar-gridlock and corporate ladder ambitions for a builder’s life shaped by AI tools, family time and public experimentation. The conversation traces how he uses agents to automate the drudgery, sharpen his strategy and protect the craft from slipping into slop.

Claire Vo and Braintrust CEO Ankur Goyal make the case that coding agents belong in the hardest engineering work, from query optimization and data migrations to the unglamorous discipline of CI. Their conversation argues that the real leverage comes from rigorous evals: defining success clearly, letting models explore the how, and using systems to extend human judgment rather than replace it.

Skydio chief executive Adam Bry argues that autonomous drones are moving from camera toys to networked infrastructure, with their most consequential uses in emergency response, utility inspection, and military reconnaissance. The conversation turns on whether the United States can build a domestic drone industry at scale while navigating bans on Chinese rivals, the politics of surveillance, and the moral limits of AI in warfare.

A sudden U.S.-ordered shutdown of Anthropic’s Fable 5 has set off a fight over AI safety, export controls and who gets to decide when a jailbreak justifies pulling a frontier model offline. The conversation weighs incompetence against political theater, while warning that if the ban sticks, access to advanced AI could hinge on nationality, ID checks and a far broader crackdown across the industry.

Mark Zao-Sanders makes the case for timeboxing as both a productivity tool and a way to restore calm: put tasks on the calendar, assign them real limits, and let intention outrun distraction. The conversation links better planning to better collaboration, arguing that visible commitments and clear deadlines reduce anxiety for individuals and teams alike.

Financial Times writer Sarah O’Connor argues that AI’s effect on work is not an unstoppable natural force but a series of choices shaped by power, policy and the people closest to the job. Drawing on reporting from translators, nurses, software developers and Hollywood writers, she makes the case that the real fight is over human agency and what kinds of work should remain irreducibly human.