An OpenAI leader sketches a near future where persistent AI agents handle most online work, while humans trade configuration and rote coding for taste, creativity and collaboration. The conversation considers the strain of agent-driven scale, the need for safety guardrails, and the push to make AI less like an app and more like ambient infrastructure.

Molly Graham revisits her “give away your Legos” career advice for an AI era, arguing that workers must embrace change without surrendering judgment, taste or accountability. The conversation makes room for the grief of lost work while asking what human roles should become next.

Former Snap and Discord product leader Peter Sellis makes the case for ideologically aligned teams, ruthless focus on core users and a product culture built around restraint. He also dissects why mediocre PMs proliferate, why Snap’s advertising business faced structural limits and how AI may raise the value of taste.

Roman Ugarte traces GrokBot’s rapid rise from a skunkworks knowledge-work experiment to a cloud-based cadre of AI colleagues. The conversation makes the case for stripping away software clutter and giving bots the autonomy, memory and computers to take on real work.

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.

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.

Enterprise sales veteran Jen Abel maps the 15-step path from first outreach to signed contract, arguing that information advantage and careful project management beat rigid scripts. The conversation treats demos, pilots and procurement as chances to build internal champions rather than merely advance a pipeline.

OpenAI’s Ian Silber argues that designers rattled by AI’s rapid advance are confronting an uncertain role, not an obsolete one. He describes a field where curiosity, systems thinking and a willingness to ship imperfect ideas matter as much as pixel-level polish.

Tom Verrilli, Whatnot’s chief product officer, makes the case for fewer, sharper product managers and more engineers and designers with the context to make decisions themselves. The conversation doubles as a critique of tech’s bureaucratic middle layers and a defense of hands-on leadership in an AI-accelerated era.

Netflix product and technology officer Elizabeth Stone argues that generative AI is blurring job boundaries without erasing the value of craft, pushing companies to prize systems thinkers, stronger infrastructure and cultures built on talent density, autonomy and accountability. She sketches a future where agents accelerate product development, analysis and entertainment production, while human judgment and storytelling remain the core differentiators.

Instagram chief Adam Mosseri sketches a workplace where AI shrinks product teams, blurs job boundaries and makes taste, judgment and strategy more valuable than sheer execution. He also argues that an internet flooded with synthetic media may ultimately reward authenticity, even as Instagram struggles to label, rank and moderate what is real.

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.

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.

Benedict Evans argues that AI is a platform shift on the scale of the internet or mobile: transformative, messy, and still too early for anyone to know where the real value or disruption will settle. He pushes back on jobpocalypse panic, sketching a slower, more uneven reshaping of work in which adoption, distribution, and new kinds of services matter more than apocalyptic forecasts.

Dan Shipper argues that AI is remaking work less by replacing people than by changing the interfaces around them: companywide agents in Slack, desktop copilots that become the operating system for knowledge work, and SaaS products rebuilt for humans and machines to collaborate together. He is strikingly bullish on the survival of SaaS, the rise of forward-deployed AI operators, and the prospects for product managers and full-stack designers who learn to ride the models.

Hardware veteran Caitlin Kalinowski argues that AI’s next great expansion will happen not on screens but in factories, robots and supply chains, where safety, manufacturing know-how and geopolitical risk matter as much as software. Drawing on stints at Apple, Meta and OpenAI, she sketches a future shaped by AR, drones and reindustrialization, while warning that war may change faster than consumer tech.

Eric Ries argues that good companies rarely collapse because of competition; they are more often hollowed out by governance, incentives and financial pressure that turn success into a liability. Drawing on examples from Anthropic, Novo Nordisk, Cloudflare and Philip Morris’s disastrous purchase of Vectura, he makes the case that founders must build mission protection into both culture and corporate structure before it is too late.

Max Schoening, Notion’s head of product, argues that AI is making the first draft of software nearly free while shifting the real differentiator to agency, taste and the discipline to make something obviously good. The conversation ranges from designers coding in terminals to the persistence of SaaS, all under a larger claim that the people who thrive will be the ones who act as if the world is changeable.

Evan Spiegel argues that durable consumer apps are won as much by distribution as by product-market fit, and that Snap’s survival has depended on building ecosystems and hardware that are harder to copy than software features. He describes a design culture built on relentless output, close contact with users, and a belief that AI’s future will be shaped less by technical possibility than by human acceptance.