---
title: "Behind the scenes of an AI-Driven Web Scraping System"
url: https://daily.dev/posts/behind-the-scenes-of-an-ai-driven-web-scraping-system-apsqb0lnn
source_url: https://www.ombulabs.ai/blog/ai-driven-scraping.html
type: article
source: "RUBYLAND"
published: 2026-06-30T19:24:25.976Z
updated: 2026-06-30T19:31:30.750Z
tags: ["llm", "css", "crawling"]
reading_time: 12
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Behind the scenes of an AI-Driven Web Scraping System

**[RUBYLAND](https://daily.dev/sources/rubyla)** · 12 min read · 0 upvotes · 0 comments

## Summary

A production engineering team built an AI-driven event aggregation scraper that ingests data from hundreds of partner sites. The post covers the full pipeline: handling static HTML vs SPAs vs lazy-loaded content using Playwright, using LLMs to generate CSS selectors (which fail 30-40% of the time on first attempt), reducing HTML size before sending to LLMs, preferring stable selectors like JSON-LD and data-testid over hashed class names, dealing with bot detection tiers, and implementing a human-in-the-loop correction loop with structured failure diagnosis. Key tools include Playwright, playwright-stealth, BeautifulSoup, Pydantic, and LlamaIndex. The core lesson: the LLM handles pattern recognition, while validation, retry logic, and failure diagnosis are engineering problems that wrap around it.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.ombulabs.ai/blog/ai-driven-scraping.html>

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---

Tags: [#llm](https://daily.dev/tags/llm), [#css](https://daily.dev/tags/css), [#crawling](https://daily.dev/tags/crawling)

[View this post on daily.dev](https://daily.dev/posts/behind-the-scenes-of-an-ai-driven-web-scraping-system-apsqb0lnn)
