great q! deepagents has more "batteries included", which langchain v1 is a very minimalistic agent harness if you are doing more complex workflows (eg claude code for X) -> deepagents if you want something simple -> langchain both are customizable with middleware
@hwchase17
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Open Standards for AI Agents and Memory Access Requirements
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i agree but there are some open standards (agents.md, skills) and you at least need to be able to access the memory
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Agent SDK Design: Sandbox vs External Harness Approaches
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most of the agents we see being built do this the main cases where we see people using "agent in a sandbox" is when they are using claude agent sdk (which is poorly designed for "harness outside sandbox")
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Deep Agents Deploy: Production-Ready AI Agents with Memory
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Deep Agents deploy gets you: – Deep Agents harness
– Sandbox of your choice (
@daytonaio , @modal , @RunloopDev )
– Short and long term memory
– Agents exposed via MCP and A2A Production ready and open standards -
Form Factor Lock-in Concerns in AI Hardware Design
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its a directionally correct form factor but way too much lock in
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AI Form Factor Directionally Correct but Creates Excessive Lock-in
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its a directionally correct form factor but way too much lock in
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Isidore Miller shares hot takes on agents and evaluations
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was really fun to sit down with @isidoremiller for this one! he has a bunch of hot takes on agents and evals that you're going to want to hear!
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Open AI Architecture: Harness, Models, Memory, Protocols
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Open Harness, Model Choice, Open Memory (take it wherever you need), Open Protocols
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Memory Ownership and Open Harnesses in AI Systems
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memory ownership is why we need open harnesses blog about this coming this weekend