A company’s frontier team can keep pace with fast-moving AI without pulling everyone else into a cycle of distraction. Operators, editors and engineers describe how rapid experimentation becomes durable products, clearer workflows and more focused work.

Factorial Capital’s Matt Hartman traces his path from backing Hugging Face’s chatbot beginnings to investing in technical founders who can chase newly programmable possibilities. He argues that as AI compresses development cycles, the ability to learn from users and rapidly refine a product becomes the defining startup advantage.

Persistent AI agents are beginning to sort themselves into two camps: personal assistants that tame the noise of daily life and company agents that accumulate shared institutional knowledge. Every’s team weighs the appeal of a beloved bot against the efficiencies of a single, evolving workplace intelligence.

Sam Altman argues that AI’s real value lies not in replacing people but in giving them more room to create, build and direct their own lives. At OpenAI’s DevDay, he frames autonomous agents, live documents and developer platforms as tools for a new entrepreneurial renaissance.

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.

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.

Portola’s founders trace how an embodied AI companion became a storytelling experiment, with users and models co-writing relationships, memories and alien-world lore. The conversation considers AI less as a replacement for writers than as a new medium shaped by improvisation, responsiveness and human taste.

Microsoft’s CTO argues that the next phase of AI hinges less on raw model gains than on an open, secure agentic web capable of taking action across systems. He also defends makers’ right to choose between handcraft and automation, whether in code, woodworking or ceramics.

Benchmark partner Sarah Tavel traces AI’s likely consumer evolution from technically driven breakthroughs to socially native products, arguing that the next winners will make powerful tools easier to share, trust and use. She also considers network effects, stablecoins and the ways AI could sharpen venture capital’s decision-making.

Benchmark partner Sarah Tavel traces AI’s consumer future from Google’s technical beginnings to the product-led rise of social platforms. She argues that the next major AI company may turn prompt-sharing, personal agents and network effects into a genuinely social experience.

Kevin Kelly ranges from Annie Dillard’s ecstatic prose to the long arc of technological change, reflecting on why some futures arrive late, sideways, or not at all. The conversation turns on AI’s uncanny usefulness, the difficulty of defining intelligence, and the pleasures of creating for an audience of one.

Every’s team breaks down how a new premium tier built around discounted AI tools produced the biggest subscription-revenue jump in the company’s history. The conversation doubles as a snapshot of how builders are using agents to automate the dull parts of work, orchestrate software stacks, and turn expensive experimentation into something more accessible.

Granola CEO Chris Pedregal talks with Every’s Dan Shipper about the knife-fight reality of building through the AI boom, where even breakout products feel precarious. Their conversation widens from meeting notes to the bigger contest over AI-native work: the interfaces, context, and invisible systems that could remake how people think and collaborate on the job.

A writer and technologist describes using AI as both intoxicant and tool, building bespoke software while guarding his mornings and attention so the work that matters does not get flattened into productivity theater. The conversation moves from vibe coding and the collapse of old SaaS moats to the stubborn value of weird books, deep focus and human particularity in an epochal technological shift.

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.

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.

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.

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.

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.

A spirited debate over whether AI agents will erase jobs or reorganize them argues that automation mostly cheapens yesterday’s expertise, making human judgment, taste and direction more valuable. Drawing on life inside an aggressively AI-native company, the conversation pushes back on layoffs-and-doom narratives and treats adaptation, not retreat, as the real dividing line.