Casey Newton tests Raycast’s Glaze by building a Nightwing-themed to-do list, a custom Platformer archive search tool, and a half-finished source tracker, using the experience to argue that AI-made software is getting more visual, more personal, and more immediately useful. The appeal is less technical novelty than the thrill of instantly reshaping the tools that used to make users live with their compromises.

A Gusto product leader traces how one company’s AI adoption moved from informal demos to quarterly hackathons, shared tooling and an expectation that everyone, not just engineers, learns to build. The conversation argues that sustained time, paired practice and connected data matter more than slogans if companies want AI fluency to change how work gets done.

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.

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.

Paul Cobblestone traces Supabase’s rise from a side project and open-source Postgres toolkit into a foundational backend platform, shaped by product positioning, relentless shipping and a refusal to sacrifice developer trust for lock-in. The conversation also follows how remote culture, community-led growth and successive AI tailwinds turned a database company into infrastructure for millions of builders.

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.

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.

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.

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.

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.

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.

Mike Krieger describes how living with Anthropic’s new Fable 5 model reshapes work from prompting to delegation, turning AI from a clever assistant into something closer to a teammate. The conversation follows what that shift means for software engineering, verification, workplace collaboration and the widening gap between a person’s intent and their ability to build.

Product leader Noah Weiner explains why many companies asking for AI help really need a return to first principles first, with the technology serving as a tool rather than a strategy. The conversation follows his “free range” consulting practice through small businesses, private equity turnarounds and startup law, while arguing that AI is compressing discovery, prototyping and decision-making into a far faster operating rhythm.

Tony Fadell argues that breakthrough products come from identifying real pain, pairing it with newly viable technology, and shaping the entire customer journey, from interface to marketing story. He warns that AI can accelerate prototyping but cannot replace human judgment, taste, and responsibility without leaving builders with brittle products and long-term debt.

Figma’s CMO argues that great marketing in 2026 is less about channel tactics than about creating coherence across product, growth, brand and community. The conversation traces how that mandate changes in an AI-saturated market, why shared goals matter more than siloed metrics, and how companies keep their taste and humanity as they scale.

A conversation about the so-called SaaS apocalypse argues that AI will not kill software so much as multiply it, pushing more people into building while preserving the value of products that handle maintenance, context and trust. Along the way, the speakers compare homemade agents, email triage, design systems and Figma’s bet that the future belongs to proactive, personalized tools that move fluidly between code and design.