Topic
All digests tagged Web Scraping
Suggested route
Move from earlier context through the available material to the newest signals. This route is a reading aid, not a difficulty ranking.
Browser agents are essential for accessing financial data behind logins or anti-bot walls. Browserbase demonstrates how forking Chromium and using Stagehand allows for scalable, reliable automation across thousands of different vendor portals.
Read article
Discover how to improve browser agents without changing model weights using the AutoBrowse loop. This system pairs a Doer agent with a Teacher agent to generate reusable 'skill' files, dramatically increasing reliability and reducing operational costs on complex websites.
Read article
Learn how AI agents use real-time web data from sources like Amazon and Reddit to build product intelligence recommendations. We cover the shift from brittle scraping pipelines to scalable, resilient data collection using Bright Data's MCP.
Read article
A browser agent that's 99% accurate per step succeeds only about 36% of the time over 100 steps. Here's how to beat that math.
Read article
In order to get reliable, uninterrupted access to the public web data on the internet, the knowledge layer needs to get the information from specialized tools. This is where the web data infrastructure layer comes into play.
Read article
A 200 status code does not mean the page is real. The gap was not model quality. It was the layer underneath that lets an agent work on the open web.
Read article
The web is no longer just a source of data; we can look at it as a source of context for knowledge work using AI agents. This leads to Context-as-a-Service (CaaS).
Read article
We're going to use LangSmith managed deep agents and Stagehand V4 tools. This allows us to build an agent that can interact with web pages by scrolling, clicking, and navigating across pages.
Read article