Browser agents for financial data behind logins and anti-bot protection. Covers Ramp, Bill, and Stripe case studies, why cloud browsers get blocked, how Browserbase forked Chromium for reliable data-center use, and how Stagehand's act, extract, and observe primitives keep automations resilient to site changes.
Nick Nisi and Zack Proser from WorkOS explore how to move "Beyond Done" with AI agents, ensuring their work is truly complete and reliable. They demonstrate building robust verification loops using custom CLIs, browser tools, and LLM judges, allowing agents to self-check and self-correct, preventing costly mistakes and accelerating development velocity for a technical audience.
Harald Kirschner, principal product manager on VS Code at Microsoft, explains how a small team serving more than 50 million users moved from monthly to weekly releases by rebuilding its whole delivery system around AI agents. He covers faster shipping through agent-ready codebases, skills, and a 10x faster TypeScript Go build, quality practices like mandatory AI code review, AI triage, auto-fix PRs and staged rollouts, and faster learning through VSC-Bench evals and daily prototyping.
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.
Garry Tan, President & CEO of Y Combinator, introduces GStack, an open-source toolkit that structures Claude into a complete AI engineering team. He demonstrates how GStack's skills—like 'Office Hours' for idea validation, 'Design Shotgun' for UI mockups, and browser-based QA—streamline the development process from concept to code.
Learn practical strategies to adapt third-party MCP server tools for production AI applications. This talk covers five key practices: curating tools, enhancing descriptions, implementing deterministic guardrails, composing new tools from existing ones, and leveraging tools as simple functions, all demonstrated through a real-world "Spec Reviewer" example.