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This tutorial shows how to quickly deploy OpenClaw, try the built‑in agent‑browser skill, install a new Email skill from Clawhub, and verify the skill’s availability through QQBot, providing concrete prompts, UI screenshots, and practical tips for extending OpenClaw’s capabilities.
This article details the redesign of a core QQ game achievement service that suffered from low resource utilization and heavy CAS contention, describing how moving from a synchronous C++ implementation to an asynchronous Go‑Kafka pipeline eliminated lock conflicts, reduced server count by 82%, and dramatically improved latency and stability.
Clawdbot (now called OpenClaw) is a local‑first AI agent runtime that integrates large language models with system‑level tools, offering a transparent, extensible architecture, privacy‑first memory, multimodal interaction, and a ReAct‑based orchestration engine for complex automation tasks.
This tutorial walks you through deploying the AI‑powered Clawdbot agent on Tencent Cloud Lighthouse, covering server creation, SSH access, one‑click template installation, interactive onboarding configuration, model and Discord integration, gateway startup, pairing, and verification to achieve a continuously running personal AI assistant.
This article traces the evolution of large language models from the 2017 Transformer breakthrough through successive milestones such as BERT, GPT‑3, RL‑HF alignment, multimodal extensions, open‑source alternatives, and the rise of retrieval‑augmented generation, AI agents, and emerging protocols that shape modern AI applications.
This guide explains how to use advanced AI models such as Gemini, Midjourney, and Stable Diffusion to expand brief, informal user descriptions into comprehensive, high‑quality English prompts that include visual style, subject details, environment, lighting, and camera parameters for image or video generation.
Transitioning from simple chatbots to sophisticated agents, this article explains how expanding context becomes a core variable, detailing the evolution from prompt engineering to context engineering, the challenges of managing growing context, and practical solutions like structured context, tool integration, and the MCP framework for reliable AI systems.
This comprehensive guide explains microservice fundamentals, when to adopt them, key design principles, service modeling techniques, integration patterns, versioning, data handling, monolith decomposition, Conway's law, scaling tactics, and the situations where microservices may not be the right choice, providing actionable insights for building resilient backend systems.
This article walks through the end‑to‑end design of IMA's AI‑driven knowledge base, covering its definition, core business flow, architecture evolution, data ingestion pipelines, management challenges, asynchronous processing, permission modeling, and the business value demonstrated by the prototype.
This article explains the ReAct paradigm—combining reasoning, action, and observation—to turn large language models into controllable agents, detailing its core concepts, architecture, workflow, code implementation, application scenarios, advantages over other methods, and future research directions.
