Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Master multi-table text-to-SQL challenges including JOIN inference, ambiguous column resolution, query planning for complex questions, and techniques that help LLMs reason across table relationships.
Discover how plan-and-execute agent architectures split high-level reasoning from step-by-step execution, enabling robust replanning on failure and efficient handling of complex multi-step tasks.
Learn how to use Playwright's async API with Python asyncio to run concurrent browser sessions, parallelize page interactions, and build high-throughput AI agent automation pipelines.
Learn how to use Playwright browser contexts to create isolated sessions with separate cookies, storage, and authentication state for multi-account AI agents with proxy rotation.
Master Playwright's network interception API to capture API responses, log request/response data, mock endpoints, and extract structured data from XHR and fetch calls in your AI agents.
Master Playwright's interaction API for AI agents — learn how to click buttons, fill forms, select dropdowns, use keyboard and mouse actions, and implement reliable waiting strategies.
Learn how to capture full-page screenshots, element-level screenshots, and record browser session videos with Playwright, then feed them to GPT-4 Vision for automated visual analysis.
Explore every Playwright selector engine in depth — CSS, XPath, text, role-based, and custom selectors — with best practices for building resilient AI agent locators that survive page changes.
Learn how to take text-to-SQL from prototype to production with query caching, usage analytics, performance monitoring, cost optimization, and scaling strategies for high-traffic deployments.
