Browser-Automation Agent Evaluation (Stagehand)
Overview
A small evaluation project for AI-driven browser automation using Stagehand, which extends Playwright with natural-language act, extract and observe methods. The folder is intentionally minimal, a scoped spike to assess the tool rather than a full build.
Why It Exists
Before committing to an approach for agentic web interaction, we evaluated Stagehand as a way to drive a browser with natural-language instructions (e.g. “click the sign in button”) on top of Playwright. This repo captures that evaluation context.
What We Built
Honestly, this is a near-empty evaluation scaffold: it contains a .cursorrules file documenting the Stagehand programming model (using observe to plan actions, act to perform them and extract to pull structured data) and a .env for credentials. It represents the setup and orientation phase of trialling Stagehand rather than a completed application, framed here as R&D / tool evaluation.
Technologies & Approach
Stagehand layered over Playwright, using an LLM to translate intent into concrete browser actions and to extract structured data from pages. The appeal is replacing brittle selector-based automation with resilient, natural-language-driven interaction.
Outcome / Impact
Captured the studio’s evaluation of LLM-driven browser automation (Stagehand), informing the related, more built-out browser-agent and Browserbase MCP work.
Capabilities Demonstrated
- Evaluating modern AI browser-automation frameworks
- Natural-language, LLM-driven web interaction (act/extract/observe)
- Rapid, honest tool de-risking ahead of larger builds