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#Deep Agents

9 posts

5 min read

Deep Agents SDK Beginner Course: 10 Articles to Build an AI Agent That Actually Plans

Deep Agents SDK is an agent framework from LangChain with built-in task planning, filesystem management, subagents, and long-term memory. This 10-part series takes you from zero to fully understanding and using it.

#Deep Agents#LangChain#LangGraph#AI Agent#Python#agent framework#task planning#subagents#long-term memory#AI development
5 min read

What Is Deep Agents SDK? The Design Logic Behind the Agent Framework

Deep Agents SDK is an agent framework from LangChain that addresses the missing planning, memory, and context management found in typical agent frameworks. This article explains its relationship with LangGraph and LangChain, and when you actually need it.

#Deep Agents#LangChain#LangGraph#AI agent framework#agent design#task planning#Python AI#deepagents
4 min read

Quickstart: Build Your First Deep Agent in 5 Minutes

From zero to a running Deep Agent: install deepagents, define custom tools, create an agent, run it. This article skips the fluff and goes straight to code — you'll have your first agent working in 5 minutes.

#Deep Agents#deepagents install#Python AI Agent#LangChain Agent#create_deep_agent#AI development quickstart#agent getting started
5 min read

Task Planning and write_todos: Make the Agent Think Before It Acts

Deep Agents' write_todos tool lets the agent decompose a task into steps and track progress before execution begins. This article explains the mechanics of write_todos and how it transforms complex task execution from 'doing things haphazardly' into 'advancing with a plan.'

#Deep Agents#write_todos#task planning#AI agent planning#agent task decomposition#LangChain Agent#deepagents#AI automation
5 min read

Filesystem Tools: Manage Context with Files, Don't Let Tokens Explode

Deep Agents includes a virtual filesystem, letting the agent use ls, read_file, write_file, and edit_file to manage task data without stuffing all intermediate results into the context window. This article explains the design logic and usage of the filesystem tools.

#Deep Agents#filesystem#context management#AI agent#read_file#write_file#deepagents#LangChain#token optimization
4 min read

Pluggable Backends: In-Memory, Disk, LangGraph Store, or Sandbox — How to Choose

Deep Agents' filesystem backend is a pluggable design, supporting In-Memory, local disk, LangGraph Store, and sandboxes like Modal/Daytona/Deno. This article explains the differences between backends and helps you pick the right solution for each scenario.

#Deep Agents#filesystem backend#In-Memory#LangGraph Store#Sandbox#Modal#deepagents backend#AI agent persistence
5 min read

Subagents: Delegate Complex Tasks with the task Tool

Deep Agents' task tool lets the main agent spawn subagents and hand off specific subtasks — each subagent has independent context so it doesn't contaminate the main agent. This article explains the design logic of subagents and how to use them in practice.

#Deep Agents#subagents#task tool#subagent#AI agent architecture#LangChain#deepagents#multi-agent#agent collaboration
5 min read

Long-Term Memory: Let the Agent Remember Important Information Across Conversations

Deep Agents uses LangGraph Memory Store to implement cross-conversation long-term memory, letting the agent recall user preferences, project state, and completed work in the next session. This article covers setup and the design strategy for memory management.

#Deep Agents#long-term memory#LangGraph Memory Store#AI agent memory#persistent memory#deepagents#cross-conversation memory#LangChain
4 min read

The Skills System: Teach Your Agent Your Standards and Preferences

Deep Agents CLI's Skills system lets you define the agent's behavioral guidelines in a structured way, covering development habits, project conventions, and preferred working styles. This article covers the structure of skills and when they're worth investing time to build.

#Deep Agents#skills system#AI agent customization#agent personalization#deepagents CLI#AI development best practices#LangChain#agent guidelines

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