Learn about the fundamental characteristics of Deep Agents - including planning, memory, and subagents - and how to implement your own Deep Agent for complex, long-running tasks.

Deep Agents follows a "trust the LLM" model. The agent can do anything its tools allow. Enforce boundaries at the tool/sandbox level, not by expecting the model to self-police.

We think of deepagents as an “agent harness”. It is the same core tool calling loop as other agent frameworks, but with built-in tools and capabilities. deepagents is a standalone library built on top of …

Agent harness built with LangChain and LangGraph. Equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - well-equipped to handle complex agentic tasks. - …

Jul 30, 2025 · All of the major model providers have an agent for Deep Research and for “async” coding tasks. Many startups and customers are creating versions of these for their specific vertical. I refer to …

This guide walks you through creating your first deep agent with planning, file system tools, and subagent capabilities. You’ll build a research agent that can conduct research and write reports.

Abacus AI Deep Agent is capable of all types of complex tasks. It can build apps, write reports, create presentations, and automatically connect to all your systems and perform agentic tasks.

Oct 24, 2025 · In this paper, we introduce DeepAgent, an end-to-end deep reasoning agent that performs autonomous thinking, tool discovery, and action execution within a single, coherent …

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Aug 5, 2025 · Deep Agents are an advanced agent architecture designed for handling complex, multi-step tasks that require sustained reasoning, tool use, and memory.