BLOG . LANGCHAIN . COM {}

Detected CMS Systems:

Hubspot (1 occurrences)

Analyzed Page
Matching Content Categories
CMS
Monthly Traffic Estimate
How Does Blog.langchain.com Make Money
Keywords
Topics
Questions
Schema
Social Networks
External Links
Analytics And Tracking
Libraries
CDN Services

We are analyzing https://blog.langchain.com/context-engineering-for-agents/.

Title:
Context Engineering
Description:
TL;DR Agents need context to perform tasks. Context engineering is the art and science of filling the context window with just the right information at each step of an agent’s trajectory. In this post, we break down some common strategies — write, select, compress, and isolate — for context engineering
Website Age:
5 years and 7 months (reg. 2019-12-03).

Matching Content Categories {📚}

Mobile Technology & AI
Education
Real Estate

Content Management System {📝}

What CMS is blog.langchain.com built with?

Blog.langchain.com employs HUBSPOT.

Traffic Estimate {📈}

What is the average monthly size of blog.langchain.com audience?

🚦 Initial Traffic: less than 1k visitors per month

Based on our best estimate, this website will receive around 19 visitors per month in the current month.
However, some sources were not loaded, we suggest to reload the page to get complete results.

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How Does Blog.langchain.com Make Money? {💸}

We're unsure if the website is profiting.

Some websites aren't about earning revenue; they're built to connect communities or raise awareness. There are numerous motivations behind creating websites. This might be one of them. Blog.langchain.com might be earning cash quietly, but we haven't detected the monetization method.

Keywords {🔍}

context, agent, agents, tool, engineering, memories, state, langgraph, llm, calls, window, memory, task, step, perform, summarization, tools, feedback, specific, code, information, select, isolate, popular, retrieval, search, examples, tokens, scratchpad, multiagent, longterm, selection, tasks, common, write, designed, types, knowledge, ways, persist, save, object, relevant, files, apply, isolating, trajectory, strategies, compress, instructions,

Topics {✒️}

auto-generate long-term memories low-level orchestration framework multi-agent include token isolate token-heavy objects multi-agent researcher illustrates building multi-agent architecture long-term memory lets token-heavy tool calls token-heavy search tools multi-agent researcher makes post-process tool calls email subscribe sign careful prompt engineering track token-usage context engineering effort embedding-based retrieval fine-grained level long-term memory virtuous feedback loop �context engineering” playing context engineering hurts simon willison shared hard-coded heuristics return json objects hugging face noted retrieval augmented generation training context confusion superfluous context influences response context clash trained context pruner track context usage improve agent performance long-running tasks deep researcher shows apply context engineering context context distraction context disagree context long-running agent andrej karpathy puts conversations spanning hundreds drew breunig points openai swarm library undesired memory retrieval agent-agent boundaries causing model confusion fine-tuned model short-term memory langgraph memory management large-scale production agent context engineering

Questions {❓}

So, how are people tackling this challenge today?
So, how can you apply these ideas?
What are the types of context that we need to manage when building LLM applications?
[Code Agents allow for] a better handling of state … Need to store this image / audio / other for later use?

Schema {🗺️}

Article:
      context:https://schema.org
      publisher:
         type:Organization
         name:LangChain Blog
         url:https://blog.langchain.com/
         logo:
            type:ImageObject
            url:https://blog.langchain.com/content/images/2024/03/LangChain-logo.png
      author:
         type:Person
         name:LangChain Accounts
         url:https://blog.langchain.com/author/langchain-accounts/
         sameAs:
      headline:Context Engineering
      url:https://blog.langchain.com/context-engineering-for-agents/
      datePublished:2025-07-02T15:52:42.000Z
      dateModified:2025-07-03T14:24:42.000Z
      image:
         type:ImageObject
         url:https://blog.langchain.com/content/images/size/w1200/2025/07/context_eng_overview.png
         width:1200
         height:427
      description:TL;DR Agents need context to perform tasks. Context engineering is the art and science of filling the context window with just the right information at each step of an agent’s trajectory. In this post, we break down some common strategies — write, select, compress, and isolate — for context engineering by reviewing various popular agents and papers. We then explain how LangGraph is designed to support them! Also, see our video on context engineering here. Context Engineering As Andrej Karpa
      mainEntityOfPage:https://blog.langchain.com/context-engineering-for-agents/
Organization:
      name:LangChain Blog
      url:https://blog.langchain.com/
      logo:
         type:ImageObject
         url:https://blog.langchain.com/content/images/2024/03/LangChain-logo.png
ImageObject:
      url:https://blog.langchain.com/content/images/2024/03/LangChain-logo.png
      url:https://blog.langchain.com/content/images/size/w1200/2025/07/context_eng_overview.png
      width:1200
      height:427
Person:
      name:LangChain Accounts
      url:https://blog.langchain.com/author/langchain-accounts/
      sameAs:

Social Networks {👍}(6)

External Links {🔗}(3)

Analytics and Tracking {📊}

Google Analytics
Google Analytics 4
Google Tag Manager
HubSpot
Site Verification - Google

Libraries {📚}

Semantic UI

CDN Services {📦}

Jsdelivr

3.5s.