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title: Best LangChain posts — July 2025 | daily.dev
description: The most upvoted LangChain posts from July 2025, curated by the daily.dev community.
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og:title: Best LangChain posts — July 2025 | daily.dev
og:description: The most upvoted LangChain posts from July 2025, curated by the daily.dev community.
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# Best of LangChain — July 2025

1. 1  
[](https://daily.dev/posts/how-to-build-an-agent-nar2dga30 "How to Build an Agent")  
Article  
![Avatar of langchain](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/0f4f2629e0724a849823f8cd0d913e13)LangChain · 1y  
How to Build an Agent  
A comprehensive framework for building AI agents from concept to production, covering six key steps: defining realistic tasks with concrete examples, creating standard operating procedures, building an MVP with focused prompts, connecting to real data sources, testing and iteration, and deployment with continuous refinement. The guide emphasizes starting small with well-scoped problems, focusing on core LLM reasoning tasks first, and treating deployment as the beginning of iteration rather than the end of development.  
163
2. 2  
[](https://daily.dev/posts/open-deep-research-rusxtzcwn "Open Deep Research")  
Article  
![Avatar of langchain](https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/0f4f2629e0724a849823f8cd0d913e13)LangChain · 1y  
Open Deep Research  
LangChain introduces an open-source deep research agent built on LangGraph that automates comprehensive research tasks. The system uses a three-phase approach: scoping (clarifying user requirements), research (using supervisor and sub-agents for parallel investigation), and writing (generating final reports). Key insights include using multi-agent architecture only for parallelizable tasks, isolating context across research topics to avoid token bloat, and implementing context engineering to manage computational costs. The agent flexibly adapts research strategies based on request complexity and is available through LangGraph Studio and Open Agent Platform.  
22

[See all LangChain archives](/sources/langchain/best-of)

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