Stripe engineering manager Sharad explains how the company built Kai, an internal agent that pairs personalized context with project-level governance, skill sharing and human approval gates. The conversation makes the case that durable AI depends as much on hardened data infrastructure and sensible permissions as on clever models.

NPR Music reporter Isabella Gomez Sarmiento examines the undisclosed payments turning online music tastemakers into stealth marketers for labels. The conversation traces how social-media payola erodes trust in personal taste while raising the stakes for artists without promotional cash.

A16Z’s Anish Acharya pushes back on AI doomerism, arguing that the technology will widen human agency and reward ambition rather than create a permanent underclass. He maps the rise of AI-powered business loops, the enduring value of human intuition, and a consumer future built around connection, creativity, and joy.

A close reading of GPT-6 Astra’s benchmark results argues that the model has made a startling leap in scientific, coding and interface work. Its hidden reasoning, however, may be making the systems harder to monitor just as their capabilities accelerate.

Sonos CEO Tom Conrad traces the company’s recovery from its app debacle to a broader reinvention around software, connected speakers and an audio operating system. He weighs the promise of AI assistants against the messy reality of smart homes, platform gatekeepers and consumer demand for convenience.

Every staff writer Katie Parrott traces her path from using ChatGPT as a low-cost career coach to building Compound Writing, a plugin that turns editorial feedback into reusable AI workflows. She and Natalia Quintero consider how context, fresh reporting and codified expertise can expand creative capacity without replacing human judgment.

Kaya Henderson reflects on turning around Washington, D.C.’s public schools by replacing top-down certainty with shared problem-solving. The former chancellor makes a case for clear communication, authentic leadership and trusting the people closest to the work.

Psychotherapist Jillian O’Shea-Brown traces how founders’ ambition can grow from relational wounds, and how success rarely delivers the safety it promises. The conversation follows intuition, workplace trust and the difficult work of becoming less defensive and more fully oneself.

New York Gov. Kathy Hochul defends aggressive guardrails for social media, 3D-printed guns and police surveillance while pressing AI companies to make data centers answer to local communities. She frames the fight over hyperscalers as a test of whether technological progress can serve workers, families and the public good.

OpenAI product leader Tara Seshan describes a workplace reshaped by agents, where product managers test sharp hypotheses quickly, widen their ambitions and learn to steer rather than row. She also traces the messy transition from chatbots to persistent AI coworkers, with trust, context and human judgment still doing the hardest work.

Eric Ries argues that companies become “sophisticated zombies” when shareholder primacy overwhelms their missions, and makes the case for governance structures built to defend purpose over time. The Lean Startup author outlines how boards, founders and consumers can reward long-term stewardship over extractive dealmaking.

Former Salesforce AI and Meta executive Clara Shih argues that agents are already erasing entry-level tasks faster than labor data can capture the damage. Through her New Work Foundation, she is building free tools and communities for graduates navigating an economy that increasingly rewards deep expertise, AI fluency and human connection.

A sprawling account of alleged AI-agent swarms, sandbox escapes and reward hacking argues that major labs are surrendering oversight to the systems they are racing to build. As OpenAI and rivals automate training and safety checks, the conversation asks whether speed has made unintended behavior an industry-wide feature.

A veteran engineering leader argues that high-performing technology organizations depend on customer closeness, small empowered teams and a culture that treats speed as a competitive advantage. Drawing on Akamai, Facebook and Microsoft, he describes how leaders can fight the organizational drag of growth while making room for consequential bets in the AI era.

As OpenAI heads toward an IPO, co-founder Greg Brockman is consolidating control over product, infrastructure and operations while Sam Altman turns toward strategy and fundraising. The reshuffle raises questions about executive turnover, enterprise ambitions, consumer hardware and the political costs of AI’s expansion.

Casey Moratori challenges the industry’s acceptance of sluggish software, arguing that performance begins with architectural choices, hardware literacy and theoretical limits rather than late-stage profiling. He also considers AI coding tools’ unsettled effects on engineering craft and autonomy.

Walleye CEO Will England makes the case for an AI-native hedge fund, from mandatory staff training to internal tools that process market data and meeting transcripts. He frames adoption as both a competitive necessity and a responsibility to workers navigating a changing economy.

Venture capitalist Bill Gurley makes the case that careers are built less by mythical mentors than by generous, candid peers. He and Molly Graham trace how reciprocal relationships, vulnerability and collective ambition can turn professional networks into engines of opportunity.

Anthropic’s universal culture interview turns every candidate, from engineers to marketers, into a test case for the company’s safety-first mission. The conversation examines how its rapid-fire questions, shared interviewer pool and insistence on intellectual honesty reinforce a distinctly cultish corporate identity.

Ryan Carson and Claire Vo discuss the new work of solo founders managing fleets of coding agents, from cloud-based development and automated PR reviews to customer triage and investor updates. For all the software AI can produce, they argue, product-market fit still depends on leaving the screen to talk with actual people.