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UID:pretalx-pydata-london-2026-ZAR8AG@pretalx.com
DTSTART;TZID=GMT:20260605T141000
DTEND;TZID=GMT:20260605T154000
DESCRIPTION:AI systems that can autonomously navigate websites\, fill forms
 \, extract data\, and complete multi-step workflows\; are one of the most 
 exciting and practical applications of large language models in 2026. Libr
 aries like browser-use (60k+ GitHub stars) and Skyvern have demonstrated t
 heir potential\, but their abstractions can obscure the surprisingly appro
 achable fundamentals underneath.\n\nIn this 90-minute hands-on tutorial\, 
 attendees will build a browser agent entirely from scratch using only Pyth
 on\, Playwright\, and an LLM API. No agent frameworks\, no magic\; just th
 e core building blocks: extracting and structuring the DOM into an LLM-fri
 endly representation\, capturing screenshots for vision-based reasoning\, 
 building the observe-think-act agent loop\, and handling real-world challe
 nges like dynamic content\, multi-tab navigation\, and error recovery.\n\n
 By building from first principles\, attendees will gain a deep understandi
 ng of how browser agents actually work\; knowledge that transfers directly
  to using\, debugging\, and extending any browser agent framework. Every p
 articipant will leave with a working agent that can autonomously complete 
 tasks on live websites.\n\nThis tutorial is aimed at Python developers and
  data scientists who are curious about AI-driven browser automation. Basic
  Python proficiency and familiarity with async/await are expected. No prio
 r experience with Playwright\, browser automation\, or agent frameworks is
  required.
DTSTAMP:20260602T225528Z
LOCATION:Doddington Forum
SUMMARY:Building a Browser Agent from Scratch: Teach an LLM to Navigate the
  Web - Richard\, Oreolorun Olu-Ipinlaye
URL:https://pretalx.com/pydata-london-2026/talk/ZAR8AG/
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