340 related articles

Generative AI is profoundly redefining the personal computer — from passive tool to intelligent collaborator. This article examines the core shifts of the AI PC era and the productivity gap created by cognitive lag.

Generative AI is profoundly redefining personal computers — from passive tools to intelligent collaborators, from deterministic computation to probabilistic reasoning. Explore the core shifts of the AI PC era.

Companies race to hire AI talent, but do traditional organizations have enough AI problems to solve? This article examines the structural mismatch in enterprise AI adoption and offers pragmatic strategy advice.

A 12-person product team shares real-world experiences with Cursor, Codex, Claude Code, and CodeRabbit—exploring efficiency plateaus, scenario matching, and selection criteria for AI coding tools that actually stick.

A detailed guide on building a full-process HR recruitment Workflow Agent with Spring AI Alibaba Graph, covering resume parsing, multi-dimensional screening, tiered questions, human-in-the-loop, and state rollback.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM basics, prompt engineering, and RAG to LangChain and multi-agent collaboration.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM fundamentals, prompt engineering, and RAG to LangChain and multi-agent collaboration.

A new solo-company paradigm: replace human staff with AI Agent teams to fully automate newsletter research, writing, publishing, and analytics. 27,000 subscribers, monthly cost slashed from $1,500 to $19.

A new one-person company model: replacing human staff with an AI Agent team to fully automate newsletter research, writing, publishing, and analytics. 27,000 subscribers, monthly cost cut from $1,500 to $19.

An in-depth look at how AI Agents execute tasks: clarifying the difference between Tools and Skills, and reconstructing the complete eight-step flow from understanding goals to delivering results.

A deep dive into how AI Agents execute tasks: clarifying the core difference between Tools and Skills, and reconstructing the complete eight-step execution flow from understanding goals to delivering results.

When your AI skill library grows to 50, repeated installs, difficult searches, and memory overload become core pain points. This article introduces an MCP-based unified management tool.

NanoClaw founder David Boyd breaks down the core engineering of enterprise autonomous Agents: a triple security isolation model, LLM Wiki memory design, and the real-world path from personal Agents to team-scale deployment.

Learn how Bilibili creator JK built an AI-automated topic selection system using Codex and Feishu — covering the three-dimension method: practice, trending topics, and benchmarking.

Can beginners really earn over 10,000 yuan in their first month with AI coding gigs? This article breaks down the four-week AI coding learning path week by week and objectively assesses the real monetization barriers.

Spring AI 1.0 is here — Java developers can now build AI apps without switching to Python. This guide covers LLM integration, RAG, intelligent customer service, and Agent patterns for enterprise deployment.

A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.

A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.

Did Claude drop ~10 benchmark points after redeployment? We dig into the safety classifier routing mechanism, Arena voting data, and developer feedback to reveal the truth.

A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.