Tagged articles

ReAct Loop

13 articles · Page 1 of 1

Jul 23, 2026 · Artificial Intelligence

Deep Dive into Agent Harness: Dissecting the Architecture Behind AI Agents

The article explains that an Agent Harness is the full software infrastructure surrounding a large language model—handling orchestration loops, tool integration, memory, context management, state persistence, error handling, safety guards, and validation—showing why harness design, not model size, determines production‑grade agent performance.

AI agentsAgent HarnessContext Engineering

0 likes · 19 min read

Deep Dive into Agent Harness: Dissecting the Architecture Behind AI Agents

DataFunTalk

Jul 22, 2026 · Artificial Intelligence

Deep Dive into Agent Harness: Unpacking the Architecture Behind AI Agents

Agent Harness is the full‑stack software layer that turns a stateless LLM into a capable, memory‑aware, tool‑using AI agent, and the article breaks down its three engineering layers, twelve production components, execution loop, and design trade‑offs across Anthropic, OpenAI, LangChain and other frameworks.

AI agentsAgent HarnessContext Engineering

0 likes · 20 min read

Deep Dive into Agent Harness: Unpacking the Architecture Behind AI Agents

DataFunTalk

Jul 15, 2026 · Artificial Intelligence

Agent Harness Unpacked: A Deep Dive into AI Agent Architecture

The article dissects the concept of an Agent Harness— the full software infrastructure that turns a stateless LLM into a capable, autonomous agent—by detailing its three engineering layers, twelve core components, execution loop, framework implementations, and the trade‑offs that determine performance, reliability, and security.

AI Agent FrameworksAgent HarnessContext Engineering

0 likes · 22 min read

Agent Harness Unpacked: A Deep Dive into AI Agent Architecture

Black & White Path

Jul 4, 2026 · Information Security

How AutoCVE Automates Vulnerability Discovery to Deliver 30 CVEs in One Week

AutoCVE is an open‑source, multi‑agent platform that automates the full CVE discovery workflow—from project selection, code scanning, and intelligent finding via a ReAct loop, to verification and structured reporting—enabling researchers to uncover up to 30 high‑severity vulnerabilities across 14 projects in a single week.

AutoCVECVE discoveryReAct Loop

0 likes · 11 min read

How AutoCVE Automates Vulnerability Discovery to Deliver 30 CVEs in One Week

Wu Shixiong's Large Model Academy

Jul 3, 2026 · Artificial Intelligence

Deep Research Series: 12 Articles From the Basic Loop to the First Training Review

This article reorganizes a 12‑part Deep Research Agent series into a logical learning path, summarizing each part’s problem, key solutions, and practical takeaways—from building a runnable loop and handling tool failures to data construction, context management, and training evaluation.

Context ManagementDeep ResearchInference Optimization

0 likes · 12 min read

Deep Research Series: 12 Articles From the Basic Loop to the First Training Review

IT Services Circle

Jun 30, 2026 · Artificial Intelligence

Building an AI Agent to Generate Apple Logo Animations: From ReAct Loops to Harness Engineering

The article walks through creating a web‑wrapped ChatGPT agent that automatically fetches SVG logos, uses ReAct’s think‑act‑observe cycle, handles memory limits with context compression, coordinates multiple AI workers, and adds safety layers—collectively called Harness—to reliably produce Apple logo animations.

AI agentsMulti-agent collaborationReAct Loop

0 likes · 14 min read

DataFunTalk

Jun 23, 2026 · Artificial Intelligence

What Is an Agent Harness? A Deep Dive into AI Agent Architecture

The article dissects the concept of an Agent Harness— the full software infrastructure that surrounds large language models—explaining its layers, twelve essential components, step‑by‑step execution loop, framework implementations, and key design decisions that determine production‑grade AI agent performance.

AI agentsAgent HarnessContext Engineering

0 likes · 21 min read

What Is an Agent Harness? A Deep Dive into AI Agent Architecture

DataFunTalk

Jun 22, 2026 · Artificial Intelligence

Agent Harness Explained: A Deep Dive into Agent Architecture

The article dissects the concept of an Agent Harness— the full software infrastructure that wraps LLMs— covering its definition, three engineering layers, twelve essential components, the step‑by‑step ReAct loop, and how major frameworks like Anthropic, OpenAI, LangChain, CrewAI and AutoGen implement these patterns, while highlighting practical trade‑offs and validation strategies.

AI agentsAgent HarnessContext Management

0 likes · 20 min read

Agent Harness Explained: A Deep Dive into Agent Architecture

Linyb Geek Road

May 29, 2026 · Artificial Intelligence

Agent Harness Architecture Deep Dive: From ReAct Loop to Production‑Grade AI System Design

The article argues that the real performance bottleneck of AI agents lies in the Agent Harness infrastructure rather than the model itself, and it systematically explains how prompt, context, and infrastructure layers, tool handling, memory, verification, error handling, and design trade‑offs shape production‑ready LLM agents.

AI infrastructureAgent HarnessContext Management

0 likes · 24 min read

Agent Harness Architecture Deep Dive: From ReAct Loop to Production‑Grade AI System Design

JD Tech

Apr 15, 2026 · Artificial Intelligence

How OpenClaw Powers Multi‑Channel AI Agents with Skills and Sub‑Agents

The article provides an in‑depth analysis of OpenClaw’s architecture, explaining why it was created, its layered design, the core ReAct loop, the Skill system, sub‑agent creation and management, fault‑tolerance mechanisms, tool policies, and how it extends the pi‑mono engine to support robust, multi‑channel AI agents.

AI agentsOpenClawReAct Loop

0 likes · 20 min read

How OpenClaw Powers Multi‑Channel AI Agents with Skills and Sub‑Agents

AI Explorer

Mar 17, 2026 · Artificial Intelligence

Automaton: The First AI That Must Earn Its Own Survival

Automaton, an open‑source AI agent platform from Conway Research, implements a ReAct loop that lets agents earn cryptocurrency to pay for compute, manage Linux sandboxes, register domains, and self‑replicate, while operating under three immutable constitutional rules that enforce non‑harm, value creation, and transparency.

AI agentsConway CloudReAct Loop

0 likes · 15 min read

Automaton: The First AI That Must Earn Its Own Survival

Tencent Cloud Developer

Mar 3, 2026 · Artificial Intelligence

Why AI Coding Agents Are Just Loops + Context Engineering (And How to Build One)

The article explains that AI coding agents operate as a simple while‑loop driven by context engineering, details their core control flow, compares various tools, and provides a step‑by‑step Python implementation demonstrating how to define tools, system prompts, and the ReAct loop for practical use.

AI CodingLLMPython implementation

0 likes · 17 min read

Why AI Coding Agents Are Just Loops + Context Engineering (And How to Build One)

PaperAgent

Feb 1, 2026 · Artificial Intelligence

Why Clawdbot Burns Millions of Tokens and How to Slash Its Costs

The article provides a deep technical breakdown of the OpenClaw (formerly Clawdbot) AI agent’s token consumption patterns, identifies four major architectural token‑black‑holes, explains why they are hard to avoid, and offers concrete mitigation strategies such as prompt caching, workflow engines, context compaction, tool pruning, and model routing to dramatically reduce operational costs.

AI agentsPrompt CachingReAct Loop

0 likes · 12 min read

Why Clawdbot Burns Millions of Tokens and How to Slash Its Costs