Evaluating Web Agents: Text-Only vs Multimodal AI

Web automation is evolving rapidly with the rise of AI agents that can browse, click, and fill out forms just like humans. But how do text-only language models compare to multimodal vision-language models when tackling real-world online tasks? This course guides you through the foundational concepts of web agents, comparing their architectures, capabilities, and limitations. You will understand how these agents perceive web pages, execute actions, and handle complex multi-step workflows like booking flights or managing online databases. What you'll learn: - Learn the core terminology and architectural differences between text-only and multimodal web agents - Understand how AI models parse HTML, DOM structures, and visual screenshots to navigate websites - Analyze performance trade-offs, accuracy, and operational costs of different agent designs - Explore prompt engineering techniques tailored for web navigation and tool-use tasks - Examine modern benchmarking frameworks used to evaluate agent reliability and safety in real environments You will start with the basic mechanics of web scraping and DOM parsing before progressing to advanced topics like vision-language processing and agent evaluation. Through clear explanations and structured text-based scenarios, you will build a solid framework for choosing the right AI agent architecture for any automation task. This course is designed for beginners, developers, and AI enthusiasts curious about the future of web automation, with no prior experience in agent development required. Start reading to discover how next-generation AI agents interact with the digital world.