A research agent is only as good as the search layer behind it!
I built a Deep Research Agent using LangChain Deep Agents with a search-first architecture designed around grounded, source-backed research.
The agent plans the research in real time, breaks the work into smaller steps, searches across the web, reasons over the retrieved sources, and produces a fully cited answer.
For this project, I used Liner as the search and grounding layer.
Liner returns raw, structured search results with titles, URLs, descriptions, and dates.