{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/655148df2861630012a1d01b/67e07f9d511f1304b0eb1968?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Shuhao Zhang, founder Tiny Fish: How to Turn Any Website into an API for AI Agents","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/655148df2861630012a1d01b/1742765924585-f058c2b4-acb4-4f2f-aee3-64c82719b46f.jpeg?height=200","description":"<p>Links</p><p>- Codecrafters: https://tej.as/codecrafters</p><p>- Tiny Fish: https://tinyfish.io</p><p>- AgentQL: https://www.agentql.com/</p><p><br></p><p>Summary</p><p><br></p><p>In this conversation, we discuss AgentQL, a framework designed to enable AI agents to access the web using natural language. Together, we explore the technical aspects of AgentQL, its advantages over traditional web access methods, and the challenges faced in its development. The discussion also covers the role of TinyFish, the parent company of AgentQL, and the future direction of their products. </p><p><br></p><p>Key use cases for developers are highlighted, showcasing how AgentQL can simplify web scraping and automation tasks. We deep dive into the integration of Playwright with AgentQL, the engineering decisions behind its development, and the importance of maintaining consistency across different SDKs. The conversation also touches on the challenges of remote browsing, security concerns, and the complexities of navigating data structures. Additionally, the various operating modes of AgentQL are explored, highlighting the trade-offs between speed and accuracy. </p><p><br></p><p>Chapters</p><p><br></p><p>03:25 Introduction to AgentQL</p><p>06:33 The Technical Framework of AgentQL</p><p>09:34 Challenges with Traditional Web Access</p><p>12:35 The Role of TinyFish and Future Products</p><p>15:25 Technical Hurdles in Building AgentQL</p><p>18:26 Interacting with the DOM</p><p>21:29 Use Cases for Developers</p><p>24:21 Building with AgentQL</p><p>27:35 Disambiguation and Query Context</p><p>30:32 Balancing Precision and Flexibility</p><p>33:30 Future Directions and Enhancements</p><p>36:36 Integrating Playwright with AgentQL</p><p>38:56 Building Infrastructure for Remote Browsing</p><p>39:30 Engineering Decisions in AgentQL Development</p><p>45:05 Web Test Automation and AgentQL</p><p>45:55 SDK Development: Python vs JavaScript</p><p>47:39 Maintaining Consistency Across Languages</p><p>51:40 Cross-Browser Support with Playwright</p><p>54:17 Security Concerns in Remote Browsing</p><p>59:14 Navigating Complex Data Structures</p><p>01:03:36 Operating Modes of AgentQL</p><p>01:04:20 Understanding Browser Fingerprinting and Anti-Bot Measures</p><p>01:06:31 Exploring AgentQL's Browser Toolkit for Langchain</p><p>01:09:15 AgentQL's Potential in Automating Workflows</p><p>01:10:17 The Future of Email Automation with AgentQL</p><p>01:11:34 Navigating the Challenges of Building a Startup</p><p>01:16:20 Achieving Success on Product Hunt</p><p>01:19:30 Implementation Pitfalls for New AgentQL Developers</p><p>01:21:37 Founder's Playbook: Lessons Learned</p><p><br></p>","author_name":"Tejas Kumar"}