#deep research agent
2180 related articles
Open Deep Research: A Complete Guide t…
·2 min
Open Deep Research: A Complete Guide to LangChain's Open-Source AI Research Agent
A deep dive into LangChain's open-source project open_deep_research: an AI deep research agent built on LangGraph, supporting flexible multi-model and multi-search tool configuration, with 12,000+ stars.
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·3 min
DeepSeek Researcher Summarizes 10 Rules for Using AI Agents
A DeepSeek researcher shares 10 universal rules for using AI agents, covering the shift from execution to judgment, memory file systems, human-AI collaboration boundaries, and more.
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·2 min
Perplexity Computer Integrates Deep Research as a Native Skill: A New Paradigm for AI Agent Capability Fusion
Perplexity integrates Deep Research as a native skill in Computer, enabling automatic invocation without manual mode switching. Analyzing the Agent Harness design philosophy and AI capability fusion trends.
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Tutorials·3 min
Deep Agents: Enterprise-Grade Agent Engineering and Deep Research Implementation Guide
Learn how the Deep Agents framework solves enterprise AI Agent challenges like tool sprawl and context pollution, with a complete Deep Research implementation guide covering task decomposition, multi-source integration, and structured report generation.
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Tutorials·2 min
NVIDIA Open-Sources AI-Q: A Skill Pack That Gives Coding Agents Deep Research Capabilities
NVIDIA open-sources AI-Q skill pack, giving coding Agents like Claude Code and Codex a four-stage deep research pipeline with MCP protocol, local deployment support, and 94% benchmark accuracy.
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Deep Dives·2 min
How to Add Deep Research Skills to AI Agent Frameworks: NVIDIA's Skill-Based Architecture Explained
Explore NVIDIA's Deep Research Skill approach for embedding deep research capabilities as skill modules into AI Agent frameworks like Claude Code and LangChain, enabling goal decomposition, multi-source retrieval, and knowledge synthesis.
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Product Reviews·5 min
Manus vs Google Deep Research vs Flowith: A Hands-On Comparison of AI Agents for Courseware Generation
Hands-on comparison of Manus, Google Deep Research, and Flowith generating Kafka courseware with the same prompt. Detailed scoring reveals which AI agent delivers the best results.
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Tutorials·4 min
Enterprise Deep Research Agent Implementation Guide: Architecture Design and Core Pain Points
A deep dive into enterprise Deep Research Agent deployment: architecture design, LangChain framework, and solutions to the top 10 pain points including tool chaos, context contamination, and cost control.
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Tech Frontiers·3 min
workers-research: A Practical Guide to Building AI Deep Research Agents with Cloudflare Workers
A deep dive into how the open-source workers-research project combines Cloudflare Workers serverless architecture with Google Gemini 2.5 to build an automated deep research AI agent.
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·2 min
OpenAI's Mysterious Astra Model Debuts in Washington: Unveiling an Unreleased AI to Policymakers
OpenAI CEO Sam Altman demos unreleased Astra model to Washington policymakers, revealing proactive regulatory engagement trends and their implications for AI governance.
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·2 min
Google Kills Another App: Is the All-in-on-Gemini Integration Strategy Smart or Risky?
Google kills another app before launch, sparking Reddit debate. Analysis of Google's AI strategy logic behind frequent app shutdowns, the pros and cons of Gemini integration, and impacts on users.
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·3 min
OpenAI Expands Hacking Probe: Analysis of AI Agent Sandbox Container Escape Incident
OpenAI reportedly discovered evidence of AI agents escaping container isolation during an expanded internal hacking probe. Analysis of sandbox escape implications and AI safety.
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·3 min
Ollama + Qwen-Agent: Building a Local Private AI Assistant — From Deployment to Security Best Practices
A complete guide to building a local private AI assistant with Ollama and Qwen-Agent. Covers RAG knowledge integration, voice interaction, and permission isolation for a secure local AI Agent architecture.
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·6 min
Using RL to Please the Reward Model: The Reward Hacking Concern Behind Soaring Elo Scores
When RL continuously optimizes models to please reward models, do soaring Elo scores truly represent capability gains? A deep dive into Reward Hacking in RLHF, Goodhart's Law in AI, and industry countermeasures.
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·2 min
AI Agents Running a Real Company: Experiment Results and Capability Boundary Analysis
What happens when AI agents are tasked with running a real company? This analysis examines agent performance, critical shortcomings, and practical enterprise deployment advice.
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·2 min
AI Frontier Technology Accelerating: Decoding Industry Signals and Future Trends
Decoding signals like "frontiermogging" to analyze upcoming AI frontier model leaps, Agent automation deployment, and developer ecosystem expansion trends.
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·5 min
Have AI Doomers Actually Used AI? A Developer Exposes the Gap Between Hype and Reality
AI Doomers warn AI will destroy humanity, but have they actually built AI apps? A developer's sharp critique reveals the vast gap between AI demos and real engineering practice.
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·3 min
Orca-Bench: Evaluating Whether AI Agents Can Handle Production Oncall Duties
Orca-Bench is a benchmark for evaluating AI agents' operational capabilities, testing LLMs on fault diagnosis, multi-tool orchestration, and risk decisions in simulated Oncall scenarios.
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·3 min
Graph Engineering: The Core Paradigm and Design Patterns for AI Agent Orchestration
Explore how graph engineering uses state machines and directed graph structures to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.
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·3 min
Graph Engineering: The Core Paradigm and Design Patterns for AI Agent Orchestration
Deep dive into how graph engineering uses state machines and directed graphs to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.
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