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8 changes: 8 additions & 0 deletions src/oss/langchain/philosophy.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,8 @@ LangChain is driven by a few core beliefs:
- It is still very early on in that transformation.
- While it's easy to build a prototype of those agentic applications, it's still really hard to build agents that are reliable enough to put into production.

Today developers can choose how they build agents: [LangChain](/oss/langchain/overview) for flexibility and control, or [Deep Agents](/oss/langchain/overview) for a batteries-included experience with built-in planning, filesystem tools, subagents, and context management. Both are built on [LangGraph](/oss/langgraph/overview).
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With LangChain, we have two core focuses:

<Steps>
Expand Down Expand Up @@ -129,3 +131,9 @@ Given the constant rate of change in the field, LangChain has also evolved over

2. A standard message content format: Model APIs evolved from returning messages with a simple content string to more complex output types - reasoning blocks, citations, server-side tool calls, etc. LangChain evolved its message formats to standardize these across providers.
</Update>

<Update label="2026-03-15">
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This date is incorrect;

0.0.1 was published Jul 29, 2025

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I based this on when we announced it to the world. Though it's also possible we don't want this here at all until v1.0. vivek (@vtrivedy) what do you think?

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i think fine to remove date

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vivek (@vtrivedy) that's not an option, the page uses dates in this timeline.

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we can
(1) not list it here
(2) list as is
(3) list with the July 29 date

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I'll put 0.5.3 with it, I think that makes most sense

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**Deep Agents is released** as an open-source agent harness built on LangGraph.

While LangChain provides flexible building blocks for custom agent architectures, [Deep Agents](/oss/langchain/overview) offers a batteries-included option for complex, long-running tasks like research and coding. It adds built-in planning tools, a virtual filesystem with pluggable backends (in-memory, disk, LangGraph store, sandboxes), subagent spawning for context isolation, and a terminal CLI. Use Deep Agents for more autonomous agents with predefined tools; use LangChain for full control over your agent architecture.
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Not sure we should mention CLI

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</Update>
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