#distributed inference
791 related articles
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Harness Engineering: The Core Methodology for Advanced AI Programming
Can zero-experience users replace programmers with AI tools? This article breaks down 4 core AI coding pain points and the 3-stage evolution from Prompt Engineering to Harness Engineering.
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Liang Wenfeng and DeepSeek: How an Idealist Is Disrupting Global AI with Algorithmic Efficiency
Why did DeepSeek go open-source? How does a 300-person team beat tech giants? A deep dive into Liang Wenfeng's logic: flat org, algorithmic efficiency, and open-source disruption.
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Local AI Agent in Action: Auto-Record World Cup Highlights and Stop Staying Up to Watch Soccer
A hands-on test of the AiKanQiu Agent on Flowin AIPC: auto-schedule, record, and extract World Cup highlights locally — no more staying up all night for soccer.
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·2 min
Why Banks and Hospitals Must Use Local AI: A Complete Guide to Private Large Model Deployment
Why do banks and hospitals build Local AI instead of using cloud services? This guide covers the full tech stack — Ollama, RAG, vector databases — and real-world enterprise deployment use cases.
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Codex CLI Practical Guide: From Setup to Enterprise-Level AI Development
Master OpenAI Codex CLI from setup to enterprise use: slash commands, AGENTS.md, MCP protocol, multi-agent coordination, plugin development, and RAG project implementation.
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GPT-5.5 Codex Reasoning-Token Clusteri…
·2 min
GPT-5.5 Codex Reasoning-Token Clustering Explained: Causes of Performance Regression and How to Respond
An in-depth look at reasoning-token clustering in GPT-5.5 Codex — exploring causes like reasoning budget imbalance and model iteration side effects, with prompt engineering strategies for developers.
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Full-Stack AI Development with Vercel: A Complete Guide to AI SDK, RAG, and Production-Ready Applications
Master full-stack AI development with Vercel: from LLM, RAG, and vector embeddings to AI SDK, AI Gateway, and v0 — build production-ready AI web apps end to end.
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·3 min
Programmers Pivoting to AI: Opportunities in Application Development and Pitfalls to Avoid
How can ordinary programmers break into AI? This guide breaks down the gap between algorithm engineers and AI app developers, covering Agent development, model fine-tuning, salary trends, and the three hidden risks behind the current opportunity window.
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·4 min
Tencent Marvis Hands-On: How Multi-Agent AI Takes Over Your Computer
Deep dive into Tencent's Marvis AI agent: multi-agent architecture, intelligent file organization, document analysis, cross-device sync, and local privacy mode explained.
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AI Workbench: One-Click Content Creation from Topic Research to Final Output
AI Workbenches automate the full content creation pipeline — from topic research to visual output. Multi-model routing, transparent execution, and reusable workflow templates redefine how creators work.
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·7 min
AI Agent Development: A Four-Stage Competency Model from 15K to 40K RMB Salary Growth Path
A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).
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AI Agent Practical Guide: From Content Generation to Enterprise Applications
A deep dive into AI Agent's two core directions: 2C content generation (text/images/video) and 2B enterprise applications (RAG/AutoGen/LLM integration). With real startup cases and practical methods.
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Getting Started with LangGraph Multi-Agent Development: Architecture Analysis and Three Practical Case Studies
Learn LangGraph multi-agent development covering Supervisor and Collaboration architectures, with three hands-on projects: code assistant, prompt assistant, and WebRTC digital human.
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·6 min
Getting Started with LangChain: A Deep Dive into Model and Agent Core Concepts
Deep dive into LangChain's core Model and Agent concepts, covering unified model interfaces, agent tool calling, middleware mechanisms, and key principles for building LLM applications.
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·7 min
Complete Guide to OpenCode: Installation, Configuration, and Custom Commands in Practice
A systematic guide to OpenCode, the open-source terminal AI coding tool: installation methods (including WSL), model configuration, rules files, Agent types, custom commands, and MCP tool extensions.
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·7 min
Agent Loop Explained: The Core Runtime Mechanism and Think-Act Cycle of AI Agents
Deep dive into Agent Loop mechanics: the think-act cycle, how agents differ from LLMs, termination conditions, and design principles for building autonomous AI Agent systems.
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Dify Self-Hosted Deployment in Practice: Building an Enterprise-Grade AI Application Platform from Scratch
A complete guide to self-hosting Dify, the open-source AI platform: environment setup, Docker Compose deployment, LLM integration, and app building. Runs on just 2 cores and 4GB RAM.
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·8 min
MCP Server or Agent Skills? A Clear Guide to Architecture Decision-Making
MCP Server vs Agent Skills: how to choose? This article systematically outlines an AI Agent architecture decision framework across three dimensions—essential differences, applicable scenarios, and judgment criteria.
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Has AI Coding Assistant Fable Been Ner…
·4 min
Has AI Coding Assistant Fable Been Nerfed? Developer's Routing Anomaly Report Sparks Debate
A developer questioned whether AI coding assistant Fable was nerfed, finding 4–10x more tokens routed to Opus with Fable doing ~20% of the work. A deep dive into multi-model routing, transparency, and AI trust.
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·7 min
AI Agent Memory Layer Comparison: Mem0, Zep, Letta, and Cloudflare — Four Major Solutions Evaluated
In-depth comparison of four AI agent memory layer solutions: Mem0's extract-retrieve approach, Zep's temporal knowledge graphs, Letta's self-editing memory, and Cloudflare Durable Objects as infrastructure primitives.
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