BLOG . LANGCHAIN . COM {
}
Detected CMS Systems:
- Hubspot (1 occurrences)
Title:
The rise of "context engineering"
Description:
Header image from Dex Horthy on Twitter. Context engineering is building dynamic systems to provide the right information and tools in the right format such that the LLM can plausibly accomplish the task. Most of the time when an agent is not performing reliably the underlying cause is that the
Website Age:
5 years and 7 months (reg. 2019-12-03).
Matching Content Categories {📚}
- Science
- Mobile Technology & AI
- Education
Content Management System {📝}
What CMS is blog.langchain.com built with?
Blog.langchain.com is based on 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.
check SE Ranking
check Ahrefs
check Similarweb
check Ubersuggest
check Semrush
How Does Blog.langchain.com Make Money? {💸}
We don't see any clear sign of profit-making.
Not every website is profit-driven; some are created to spread information or serve as an online presence. Websites can be made for many reasons. This could be one of them. Blog.langchain.com could be getting rich in stealth mode, or the way it's monetizing isn't detectable.
Keywords {🔍}
context, engineering, llm, tools, information, agent, prompt, model, important, langsmith, dynamic, task, data, llms, systems, format, lets, lot, built, instructions, prompts, complex, matters, good, term, langgraph, steps, langchain, read, dex, building, plausibly, accomplish, underlying, agentic, system, make, making, set, helps, formatted, communication, key, behave, access, conversation, decide, run, blog, case,
Topics {✒️}
dynamic agentic systems agentic systems mess descriptive error message large json blob email subscribe sign long term memory building dynamic systems content case studies enable context engineering controllable agent framework agent frameworks emphasize phrasing prompts cleverly restrict context engineering model absolutely affects increasingly important skill fetching information dynamically llm application observability context engineering important tools return information langchain team context building perfectly built good read 12 factor agents read minds context engineering good output absolutely matters important skill plausibly accomplish performing reliably recent takes tobi lutke ankur goyal walden yan previous interactions based solely input parameters great question mind readers helps separate failure modes mind readers developers focused applications grow providing complete magic wording key part maximally digestable expressed preferences
Questions {❓}
- Can it plausibly accomplish the task?
- How is context engineering different from prompt engineering?
- Is it failing because you haven’t given it the right information or tools?
- What is context engineering?
- Why the shift from “prompts” to “context”?
- Would you say that providing clear and detailed instructions for how the agent should behave is context engineering or prompt engineering?
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:Harrison Chase
url:https://blog.langchain.com/author/harrison/
sameAs:
headline:The rise of "context engineering"
url:https://blog.langchain.com/the-rise-of-context-engineering/
datePublished:2025-06-23T16:56:00.000Z
dateModified:2025-06-23T16:56:00.000Z
image:
type:ImageObject
url:https://blog.langchain.com/content/images/2025/06/GtRmoOqaUAEXH2i.jpeg
width:1200
height:675
description:Header image from Dex Horthy on Twitter.
Context engineering is building dynamic systems to provide the right information and tools in the right format such that the LLM can plausibly accomplish the task.
Most of the time when an agent is not performing reliably the underlying cause is that the appropriate context, instructions and tools have not been communicated to the model.
LLM applications are evolving from single prompts to more complex, dynamic agentic systems. As such, context enginee
mainEntityOfPage:https://blog.langchain.com/the-rise-of-context-engineering/
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/2025/06/GtRmoOqaUAEXH2i.jpeg
width:1200
height:675
Person:
name:Harrison Chase
url:https://blog.langchain.com/author/harrison/
sameAs:
External Links {🔗}(3)
Analytics and Tracking {📊}
- Google Analytics
- Google Analytics 4
- Google Tag Manager
- HubSpot
- Site Verification - Google
CDN Services {📦}
- Jsdelivr