Don Syme, designer of F# and GitHub Next engineer, explains how AI agents are moving from individual productivity tools toward continuous, collaborative automation inside repositories. He introduces continuous AI and agentic ops, GitHub Agentic Workflows with their guardrails, and the factory and farm metaphors for managing software production.
Jose Palafox, a GitHub Field Copilot Specialist, walks through taking a Copilot agent from a single laptop to an organization-wide, pipeline-hosted system. Topics include how the Copilot harness and CLI work, building custom agents with the agent builder, sharing them through marketplaces, orchestrating cross-repository changes, and running headless agents in GitHub Actions through GitHub Agentic Workflows, with a focus on observability and cost control.
This presentation by Amy Kapernick at YOW! Australia 2025 details how to implement robust front-end testing using GitHub Actions. It covers the rationale for comprehensive front-end testing, the necessity of a live deployment preview, and practical steps for automating tests like Lighthouse for performance/accessibility and Playwright for UI validation. The talk also delves into continuous deployment workflows and explores GitHub Actions' broader utility for workflow automation beyond testing, such as generating issues from code comments.
Liam Hampton from Microsoft presents a practical framework for using AI agents effectively by categorizing them into three types: local, background, and cloud. He demonstrates how to run all three simultaneously from a single VS Code interface to solve separate problems in one codebase, showcasing a powerful, integrated developer workflow.
A detailed summary of a workshop on building and deploying production-minded AI coding agents using Dagger. The session covers creating controlled, observable, and test-driven agent workflows and integrating them into CI/CD systems like GitHub Actions for automated, reliable software development.