AI Screenshot Analysis with LLM Structured JSON Outputs
Turn screenshots into validated JSON with vision models, schemas, retries, and reliable capture workflows.
Getting Started With Qwen-Agent: Building AI Agents With Tools and RAG
Install Qwen-Agent, connect a Qwen model, add custom tools, and build a practical retrieval workflow with safety and deployment guidance.
How to Build AI Web Browsing Agents with an Open-Source Framework
Build a bounded web agent with Stagehand, understand BrowserGym evaluation, and choose the right browser runtime for production.
Browser Agent Quickstart: Build an AI Browser Agent
Build a controlled browser agent that observes pages, chooses actions, verifies results, and knows when deterministic Playwright is the better tool.
Caching Strategies for Browser Automation Agents
A practical guide to HTTP, service-worker, browser-context and AI-agent caches, with Playwright patterns, invalidation rules, isolation safeguards and code.
Computer-Using Agents for Browser Automation
Computer-using agents operate browsers through screenshots and actions. Learn how the control loop works, where it fails, how to build safer automations, and when to use browser code instead.
Build an AI Sales Bot with WebMCP Using Public Data
Build a browser-based sales research assistant with WebMCP and Census data. Includes a runnable Node.js backend, tool registration, security guidance, and troubleshooting.
AI Job Application Automation: A Practical, Safe Workflow
Learn what AI auto-apply tools really do, how to review applications safely, and how to build a reliable automation workflow without sending errors.
A Developer’s Guide to Building LLM Agents
Learn how to design, tool, evaluate, secure, and deploy reliable LLM agents with practical architectures and runnable code.
Unit Testing AI Agents in the Browser
Build browser-agent tests that produce useful evidence: deterministic Playwright checks for critical flows, controlled agent exploration, and artifacts that make failures diagnosable.
How AI Agents Can Generate PDFs with Automation Tools
Build a safe agent workflow for generating PDFs: tool design, HTML rendering, Puppeteer and Playwright code, security, troubleshooting, and ScreenshotNeo.
How to Verify AI Agents in Browser Automation
A practical framework for proving browser agents completed tasks safely, with Playwright checks, evidence bundles, benchmarks, and red-team tests.
Generating Video, PDFs, and Images with the Browser Agents MCP Server
Use Browserless MCP to capture webpages as images or PDFs and record browser sessions as WebM, with setup steps, runnable examples, and troubleshooting.
How to Self-Host a Browser Automation Service for AI Agents
Deploy a private browser automation service for AI agents with Docker, Playwright, security controls, health checks, scaling guidance, and alternatives.
How to Scale Browser Sessions for AI Agents
Scale AI agent browser work with bounded queues, isolated sessions, explicit cleanup, and measured concurrency. Includes runnable Playwright code and managed-session guidance.
How to Improve Browser Agent Speed and Accuracy
Make browser agents faster and more reliable with semantic locators, state-based waits, outcome assertions, and repeatable benchmarks.
Designing Simpler Interfaces for AI Browser Agents
Learn how semantic HTML, clear states, recovery paths, and screenshots make websites easier for AI browser agents to use reliably.
Ashby Scraping APIs for AI Agents
Use Ashby’s API for controlled job data pipelines or its MCP server for permission-aware AI workflows. Here’s how to choose, authenticate, paginate, and protect sensitive data.