#Agent Loops
744 related articles
Tutorials·2 min
OpenAI Codex Complete Guide: Four Tools for Building an AI Programming Workflow
Deep dive into OpenAI Codex's four core tools: IDE extension, CLI, Cloud service, and code review bot. Learn how they work together to build an efficient AI programming workflow from local coding to cloud automation.
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Tutorials·2 min
LangGraph 0.5.3 + MCP Agent Development in Practice: Security Authentication & Deployment Guide
LangGraph 0.5.3 introduces MCP server security authentication and agent deployment solutions. Combined with Qwen3 models, it provides a complete production-grade AI agent development stack.
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Product Reviews·2 min
Claude Opus 4.8 Launches on Cursor: Dual Improvements in Efficiency and Persistence
Cursor announces Claude Opus 4.8 is live. CursorBench shows significant gains in coding efficiency and task persistence. Analysis of key improvements and market impact.
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Deep Dives·3 min
memU Memory Framework Explained: Unifying Multi-Modal Agent Memory with a File System
Deep dive into the memU open-source memory framework: how it organizes Agent memory as a file system with three-layer semantic abstraction, dual-loop collaboration, and two retrieval modes.
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Research·2 min
Optimize Anything: One API to Unify Optimization of Code, Prompts, and Agent Architectures
UC Berkeley and Stanford propose Optimize Anything, a universal text optimization framework that unifies optimization of CUDA kernels, agent architectures, and prompts through one declarative API.
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Research·2 min
How GitHub Is Building a General-Purpose Accessibility AI Agent: Lessons Learned and Technical Challenges
GitHub is building a general-purpose accessibility AI Agent to automatically detect and fix software accessibility issues. Explore the technical challenges, human-AI collaboration, and industry impact.
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Industry Insights·3 min
How Jane Street Built a Custom AI Programming Toolchain for OCaml
Jane Street's AI team details how they built a custom LLM toolchain for OCaml, covering workspace snapshot training data, RL with code evaluation, and the AID editor architecture.
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Industry Insights·3 min
AI Agents Deep Dive: The Paradigm Shift from Chat Tools to Autonomous Execution Systems
Deep analysis of AI Agents vs LLMs, covering three evolution stages, four core architecture components, three penetration paths, multi-agent collaboration, and societal impact.
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Product Reviews·3 min
Zenflow Hands-On Review: Spec-Driven AI Coding vs. Pure Prompt-Based Development
In-depth review of Zenflow's spec-driven AI coding vs Google AI Studio's prompt-based approach. Covers multi-agent execution, automated validation, version rollback, and the paradigm shift in AI programming.
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Tutorials·3 min
LangGraph Multi-Agent Architecture: Graph Structure Principles and Enterprise-Level Implementation Guide
Deep dive into LangGraph's core graph structure design, single and multi-agent collaboration patterns, MCP protocol integration, and Time Travel fault-tolerance, with enterprise-level hybrid multi-agent architecture implementation.
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Product Reviews·3 min
Devin 2.0 In-Depth Review: Is the $20/Month AI Coding Agent Actually Worth It?
In-depth analysis of Devin 2.0: dropped from $500 to $20/month, 12x efficiency in code migration, but only 15% completion on complex tasks. Real test data on use cases and limitations.
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Expert Opinions·3 min
Gumloop Founder: 50 AI Agents Running Your Company? Don't Fall for It
Gumloop founder Max shares the truth about AI automation: processing 4M daily workflows taught him why 50 AI Agents running a company is a lie, and why the real AI philosophy is acceleration, not replacement.
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Tutorials·3 min
Hermes Agent + Playwright: A Practical Guide to AI-Driven Browser Automation
A complete guide to AI-driven browser automation with Hermes Agent and Playwright, covering setup, three AI modes (snapshot decisions, multi-turn dialogue, autonomous exploration), retry mechanisms, and optimization tips.
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Product Reviews·2 min
ZenFlow Hands-On: Testing the Spec-Driven Fully Autonomous AI Software Engineer
Hands-on review of ZenFlow—the first spec-driven fully autonomous AI software engineer. Multi-agent parallel collaboration with built-in verification delivers end-to-end development from ideation to production.
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Tutorials·2 min
Career Progression in AI/LLM Application Development: Four Stages from Beginner to 40K Monthly Salary
A systematic four-stage career path for AI/LLM application development: from RAG and Agent fundamentals to architecture design, helping developers transition to AI roles targeting 40K+ monthly salary.
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Product Reviews·3 min
Google Jules 2.0 Major Upgrade: Deep Dive into Seven New Features
Google's AI coding assistant Jules exits Beta with environment snapshots, Critic Agent reinforcement learning code review, interactive planning, web preview, web search, and more.
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Tutorials·3 min
SubAgent Architecture: The Core Implementation for Context Isolation
Deep dive into SubAgent context isolation architecture, covering parent-child Agent roles, tool definitions, run_subagent implementation, and differences from TodoList and Agent Teams.
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Deep Dives·3 min
Deep Dive into MCP Code Execution & Agent Skills: Compressing 150K Tokens Down to 2,000
Deep analysis of two MCP ecosystem breakthroughs: code execution compresses tool definitions from 150K to 2K tokens, and Agent Skills enable capability packaging and reuse.
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Tutorials·2 min
Complete Breakdown of Andrew Ng's LangChain Course: Five Core Components and Hands-On Guide
Deep dive into Andrew Ng and Harrison Chase's LangChain course, covering the five core components—Models, Prompts, Indexes, Chains, and Agents—to help developers master LLM app development.
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Tutorials·3 min
MCP Protocol Explained: The New Agent Communication Standard Replacing Function Calling
Deep dive into MCP (Model Context Protocol): its core concepts, three communication mechanisms, and ecosystem. Learn how MCP replaces Function Calling with Streamable HTTP and SDK 2.0.
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