Agentic workflows

Realtime multiplayer, automation, and you! — Idan Gazit, GitHub

Realtime multiplayer, automation, and you! — Idan Gazit, GitHub

Idan Gazit, head of GitHub Next, discusses the future of AI in software development, moving beyond personal productivity to enabling group collaboration and advanced automation. He introduces two prototypes: "Agentic Workflows" for autonomous, secure code upgrades and task execution using natural language, and "ACE," a real-time collaborative development environment designed to integrate AI into team workflows, addressing the 95% of development work beyond mere typing.

How to Build a Self-Improving Company with AI

How to Build a Self-Improving Company with AI

YC General Partner Tom Blomfield explains how to move beyond the 'copilot' mindset and restructure companies as series of recursive, self-improving AI loops. He details how to make company knowledge legible to AI, creating systems that improve overnight with minimal human intervention, ultimately rendering traditional middle management obsolete.

CI/CD Is Dead, Agents Need Continuous Compute and Computers — Hugo Santos and Madison Faulkner

CI/CD Is Dead, Agents Need Continuous Compute and Computers — Hugo Santos and Madison Faulkner

Madison Faulkner and Hugo Santos explain why traditional CI/CD, built for human developers, is failing under the load of AI agents. They propose a new paradigm of 'Continuous Compute' centered on intent-driven agent loops, fast inline validation, and a pre-merge layer where humans review outcomes, not diffs, paving the way for a 'multiverse' of parallel development.

Building your own software factory — Eric Zakariasson, Cursor

Building your own software factory — Eric Zakariasson, Cursor

Eric Zakariasson from Cursor explains the shift from single-agent pair programming to managing a multi-agent "software factory". He outlines the practical steps required, from establishing a well-structured codebase with guardrails to adopting a managerial mindset that focuses on automation, asynchronous work, and scaling agent fleets to increase software development throughput and consistency.

How To Build A Company With AI From The Ground Up

How To Build A Company With AI From The Ground Up

Y Combinator Partner Diana Hu explains how to build an AI-native company where AI is the core operating system, not just a tool. She covers how to make a company queryable, the impact on team structures, and why startups have a massive edge in this new paradigm.

Full Workshop: Build Your Own Deep Research Agents - Louis-François Bouchard, Paul Iusztin, Samridhi

Full Workshop: Build Your Own Deep Research Agents - Louis-François Bouchard, Paul Iusztin, Samridhi

This hands-on workshop details the construction of a sophisticated, dual-part AI system for producing high-quality technical content. It begins with an MCP-powered deep research agent that autonomously plans, searches the web, and analyzes sources like YouTube to synthesize a grounded research artifact. The second part is a constrained, deterministic writing workflow that transforms this research into polished, non-sloppy content using an innovative "Evaluator-Optimizer" pattern for iterative refinement. The session emphasizes crucial AI engineering principles, such as choosing between agentic and workflow-based architectures, and concludes with a deep dive into implementing practical observability and evaluation pipelines to ensure the system is both measurable and improvable.