liveBook · Manning

Web search

As explained in AI for Everyday IT

Web search is the process of retrieving information from publicly available web pages through a search service.

Web search retrieves current information from multiple public web pages and combines it with an AI assistant’s existing knowledge. Citations let you verify claims and investigate sources instead of accepting generated answers automatically. section 2.1.1 section 1.6.3

Use web search for practical research tasks such as:

  • Checking current package versions, GitHub Actions, API versions, and deprecated npm packages before coding. section 2.1.1
  • Finding exchange rates, per diem rates, and subscription fees for business calculations. section 2.1.1
  • Breaking large verification jobs into smaller groups, such as checking three dependencies at a time rather than twenty. section 2.1.1

Keeping technical research current

Before asking an AI coding assistant to work, use ChatGPT’s web search to research the latest package versions and supply the cited findings to the coding tool. Review the citations and divide multi-package checks into smaller requests to reduce verification errors. section 2.1.1

Figure 1.5 Citation prompt in ChatGPT
figure

A citation prompt illustrates how web search can attach sources to an AI response. section 1.6.3

Figure 2.4 Gemini’s web search interface
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A search interface illustrates how Gemini searches Google’s index and summarizes current results inside the chat. section 2.1.3

How AI for Everyday IT covers it

How deep it goes
Explains natural-language searching, multi-page synthesis, citations, and smaller verification batches, but does not cover search internals.
Examples
Uses package versions, deprecated APIs, exchange rates, per diem rates, and subscription fees as research targets.
What you can do after
Apply it via ChatGPT or Gemini to gather current, cited information and pass verified findings to another AI tool.
How it connects
Connects AI assistants with source citations, real-time information, and AI coding assistants.

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This explainer was generated by Manning's knowledge graph from the text of AI for Everyday IT. The section links point to the parts of the book it draws on.