#agent loop
2842 related articles
Research·2 min
Agent Loops in Practice: Transforming Token Output into Productivity from CUDA Kernels to Automated Research
Deep dive into how the Humanize framework transforms LLM tokens into engineering productivity via Agent Loops. Covers KDA winning CUDA kernel contests, virtual hardware optimization, and 50% research cost reduction.
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Tech Frontiers·1 min
SGLang Hosts Agent Loops Office Hour, Focusing on Agentic Loop Architecture Optimization
SGLang team hosts an Agent Loops Office Hour exploring inference optimization for agentic loops, covering KV Cache reuse, low-latency multi-turn dialogue, and tool calling techniques.
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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
Agent Loop Explained: Solving Code Refactoring Pain Points with the ReAct Pattern
Deep dive into Agent Loop, the core mechanism of AI coding tools. Learn how the ReAct pattern's reason-act-observe cycle enables autonomous multi-step code refactoring.
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Industry Insights·2 min
OpenAI Codex Powers a Self-Improving Tax AI Agent: A New Paradigm for Closed-Loop Evolution
OpenAI and Thrive Holdings launch a Codex-based Tax AI with closed-loop self-improvement: error tracing, auto-fixing, and test validation. A deep dive into this new AI Agent evolution paradigm.
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Industry Insights·1 min
Claude Code Architecture Deep Dive: Why a Single-Loop Design Beats Multi-Agent Systems
Deep dive into Claude Code's architecture: single-loop control, no RAG, 9,400-token tool prompts, and model tiering. The minimalist design behind a $1B AI coding tool.
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Tutorials·2 min
Replicating Manus for $30: A Practical Breakdown of Building an AI Agent's Minimum Viable Loop
A detailed breakdown of replicating the Manus AI agent platform for $30, covering Docker container integration, task orchestration, UI design, and the course-based monetization strategy.
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Deep Dives·2 min
How AI Agents Work: The Four Core Elements and ReAct Loop Decision-Making Mechanism Explained
Deep dive into AI Agent's four core elements (LLM, Tools, Prompts, Executor) and ReAct loop decision mechanism, with a weather query example walkthrough.
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Deep Dives·4 min
Agent Loop Core Mechanism Explained: Building a ReAct Loop from Scratch (With Debugging War Stories)
Deep dive into Agent Loop, the core mechanism of AI Agents, based on ReAct architecture. Covers Tool Call ID handling, context management, assistant message feedback, with full Python code and common bug fixes.
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Deep Dives·1 min
Ralph Loop: The New AI Programming Paradigm That Beats Multi-Agent Systems Through Iterative Trial and Error
Ralph Loop is a 2025 AI programming paradigm: a memoryless AI Agent repeatedly reads the same Prompt, accumulates experience via file systems, beating multi-agent architectures through iterative loops.
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Tutorials·2 min
Harness Engineering Explained: A Guide to Building a Four-Step Closed-Loop AI Agent Work System
A deep dive into the Harness Engineering four-step closed-loop principle (Goal, Action, Verification, Memory), clarifying its relationship with Prompt Engineering, Context Engineering, and MCP.
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Tutorials·3 min
AI Agent Context Management in Practice: A Complete Guide from Death Loops to Intelligent Truncation
Deep dive into AI Agent context management: a three-step strategy from naive truncation to intelligent memory, covering sub-Agent architecture and long session evals to solve LLM context bloat.
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Deep Dives·3 min
AI Agent Core Principles Explained: The Decision Loop and Three-Component Architecture
Deep dive into AI Agent core principles: the Sense-Plan-Act-Observe decision loop, and how Planning, Memory, and Tools components transform LLMs into autonomous digital employees.
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Deep Dives·4 min
Deep Dive into Claude Code Source Code: A Complete Guide to Agent Loops, Context Engineering, and Architecture Design
Deep analysis of Claude Code's source architecture: Agent loop mechanism, context engineering strategies, tool system design, and permission controls. Based on the viral GitHub project how-claude-code-works.
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Tech Frontiers·2 min
Codex CLI /goal Command Explained: AI Coding Agent Loops Automatically Until the Goal Is Done
Deep dive into Codex CLI 0.128.0's new /goal command: how prompt templates drive autonomous agent loops, token budget controls, and AI coding agents that work until the goal is done.
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·2 min
AFK: A Unified Command Center for Team-Collaborative AI Coding Agents
AFK is a team-oriented AI coding Agent management platform using Daemon local architecture, permission governance, task handoff, and BYOK to solve multi-user Agent collaboration challenges.
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·3 min
Mistral's Patent Application for Code-Based Tool Calling Sparks Controversy: The Open Source vs. Patent Paradox
Mistral AI's patent filing for "code-based tool calling" sparks developer debate. Analysis of the technology, how it differs from JSON Function Calling, and its potential impact on the AI Agent open-source ecosystem.
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·3 min
Heym: Deep Dive into a Self-Hosted Visual Agent Building Platform
Heym is a self-hostable visual platform for building agentic systems, offering multi-agent workflow orchestration, built-in observability, human approval mechanisms, and MCP protocol support.
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·2 min
Tura: A New Approach to Saving 80% of Tokens for AI Agents
An in-depth analysis of how the Tura framework helps AI Agents reduce 80% of token consumption while improving task quality through intelligent context management and structured tool calling.
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·4 min
The Creator of Claude Code Shares 10 High-Efficiency AI Coding Tips
Claude Code creator Boris shares 10 practical AI coding tips in his viral talk, covering setup, prompting, planning, team collaboration, SDK usage, and multi-instance concurrency.
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