Productivity

Garry Tan: "Personal AGI Is How You Stay Under Your Own Power"

Garry Tan: "Personal AGI Is How You Stay Under Your Own Power"

YC President Garry Tan introduces "Personal AGI," a concept where individuals own and train AI agents on their unique context, transforming personal productivity and startup creation. He shares his workflow, advocating for Markdown as code and emphasizing the critical importance of owning one's intellectual assets in the age of AI. The talk outlines a practical 5-step guide to building a personal AI system and explores the profound implications for innovation and individual empowerment.

OpenAI’s Plan to Make ChatGPT the Everything App — Akshay Nathan, OpenAI

OpenAI’s Plan to Make ChatGPT the Everything App — Akshay Nathan, OpenAI

Akshay Nathan, head of Core Product Engineering at OpenAI, discusses the journey and rationale behind ChatGPT Work. He explains how Codex's unexpected adoption by non-developers led to a unified agent harness, blurring the lines between developer and knowledge worker tools. The conversation delves into model capabilities, the role of artifacts and interactive 'Sites' in replacing traditional documents, and how AI fosters a new era of 'T-shaped' generalists. Nathan emphasizes the shift in productivity bottlenecks to 'ideas and taste' and the importance of 'quality at-bats' over mere 'motion' in an AI-powered development landscape.

Jensen Huang: The Mindset That Built NVIDIA

Jensen Huang: The Mindset That Built NVIDIA

Jensen Huang, CEO of NVIDIA, shares critical lessons from NVIDIA's journey, emphasizing how early failures and a commitment to learning new technologies, like purchasing textbooks from Fry's to pivot the company, laid the groundwork for their success. He discusses NVIDIA's strategic vision, driven by accelerating algorithm domains and seeing AlexNet as a universal function approximator, which led to a reinvention of the computing stack. Huang also explores the future of AI with agents, the importance of fine-grained control, and the "Linux moment" of open-source AI, while also forecasting the rise of physical AI and job creation. He concludes with profound advice on resilience, systems thinking, and the "how hard can it be?" mindset for aspiring entrepreneurs in this unprecedented era of technological reset.

Full Workshop: Setting Yourself Up for Success —Jason Liu, OpenAI Codex

Full Workshop: Setting Yourself Up for Success —Jason Liu, OpenAI Codex

Jason Liu from OpenAI shares advanced strategies for using Codex to automate complex workflows and manage personal information. He introduces key concepts like "compaction," dictation for input, and "appshots" for contextual awareness. The talk covers bringing context into the system via plugins and a personal memory vault, working with AI through automations, goals, and interconnected threads, and taking actions out in the real world, emphasizing the transformative power of "Computer Use" for broad system control.

Closing Keynote: Garry Tan, Y Combinator

Closing Keynote: Garry Tan, Y Combinator

Garry Tan, President of Y Combinator, details how AI-native companies are achieving unprecedented productivity and scale with lean teams. He introduces the concept of "wiring the work" by treating AI as a workforce where organizational components are encoded into markdown "skill files." Tan explains how "company brains" act as a library and librarian, managing institutional knowledge to overcome human memory limits. He emphasizes the discipline of "skillifying" every task to ensure continuous learning and calls on founders to build these new AI-native infrastructures to "boil the ocean"—tackling previously insurmountable problems.

From Writing Code to Designing Systems: How the Developer Role is Changing — Chris Noring, Microsoft

From Writing Code to Designing Systems: How the Developer Role is Changing — Chris Noring, Microsoft

This talk introduces a paradigm shift in software development, moving developers from pure code producers to system designers and agent orchestrators. It details a new workflow leveraging GitHub Copilot CLI, custom Copilot agents, and explicit guardrails like `agents.md` and skills. The focus is on how to decompose complex problems, delegate implementation to AI, and encode architectural standards and constraints directly, enabling higher consistency, quality, and accelerated delivery through a "human-in-the-loop" delegation model.