#AI Agent
1115 related articles
Tech FrontiersUnity's Built-in AI Agent: The Era of One-Person Game Development Has Truly Arrived
Unity officially launches its native AI Agent that can directly manipulate the editor, generate scenes, and plan development paths. Combined with MCP protocol access to Claude and Gemini, game development barriers are being fundamentally reshaped.
Deep DivesAITS Intelligent Testing Platform: How AI Agents Are Transforming Test Engineers from Script Writers to AI Commanders
Explore how AITS uses AI Agents to auto-generate test cases, self-heal scripts, and run exploratory testing — helping engineers evolve from script writers to AI testing strategists.
Tech Frontiers2025 Shanghai .NET Conference: Will AI Replace Programmers? A Complete Breakdown of .NET 10 and AI Agents
2025 Shanghai .NET Conference coverage: Microsoft unveils .NET 10, roundtable debates AI replacing programmers, Clean DDD + AI Agent architecture in focus.
TutorialsLangChain v0.3 Agent Tutorial: Complete Guide to Tool Definition, Building, and Execution
Complete guide to building AI Agents in LangChain v0.3, covering @tool decorator, Agent Executor, parallel tool calls, Google Search integration, and ReAct framework with code examples.
Tech Frontiersdatasette-agent-sprites: A Deep Dive into the AI Agent Sandbox Execution Plugin
Simon Willison releases datasette-agent-sprites plugin for secure AI Agent command execution in Fly Sprites sandbox. Analysis of its architecture, use cases, and significance.
Deep DivesHarness Engineering Explained: The Underlying Principles and Practical Methods for Controlling AI Agents
Deep dive into Harness Engineering: controlling AI Agents through rules, tool configuration, and workflow design, plus feedback mechanisms and Lifelong AI Agent practices.
Tutorials7 AI Agent Money-Making Projects: A Hands-On Guide from Domain Flipping to Competitor Monitoring
7 AI Agent business projects you can start today — from domain flipping to liquidation arbitrage to cold email outreach, with full toolchains for earning $1,000-$3,000/day.
Industry Insights3,500 Enterprise AI Use Cases Reveal: Is AI Investment Actually Worth It?
Survey of 1,000+ enterprises and 3,500 AI use cases reveals: 44% see moderate ROI, 37% see high ROI. AI Agent adoption surged from 11% to 42%. Coding and risk use cases top the charts.
Deep DivesThe Rise of AI Operating Systems: How Large Models Are Evolving from Tools to OS
AI is evolving from a single tool into a complete operating system. This article analyzes AI OS core architecture, MCP/A2A protocol standardization, and how Agents are becoming the next OS paradigm.
Deep DivesGemini 3.5 Flash Deep Dive: Google's AI Agent Execution Engine
Google I/O 2025 unveils Gemini 3.5 Flash—4x faster than frontier models, outperforming its own flagship on coding and Agent benchmarks. Deep dive into its core capabilities and industry impact.
Deep DivesHow to Add Deep Research Skills to AI Agent Frameworks: NVIDIA's Skill-Based Architecture Explained
Explore NVIDIA's Deep Research Skill approach for embedding deep research capabilities as skill modules into AI Agent frameworks like Claude Code and LangChain, enabling goal decomposition, multi-source retrieval, and knowledge synthesis.
Tech FrontiersGoogle I/O 2026 Deep Dive: The Ambitions and Concerns Behind Gemini Spark and Antigravity
Deep analysis of Google I/O 2026's two core releases: AI agent Gemini Spark with deep Google ecosystem integration, and Antigravity's shift from open to closed source. Covers Prompt Injection risks and AI Agent trends.
Product ReviewsEcho Agent Deep Dive: A Self-Hosted AI Agent Operating System
Deep dive into Echo Agent, a self-hosted AI Agent OS featuring four-role collaboration, cognitive memory systems, LLM-driven security approval, and A2A/MCP protocol support.
TutorialsNingbo Bank AI Agent Interview Questions: Reasoning Optimization + Agent Debugging + Python Key Topics
Deep analysis of real Ningbo Bank AI Agent interview questions covering LLM multi-path reasoning optimization, agent debugging methodology, Python deep/shallow copy, GIL, and decorators.
TutorialsOpenClaw Agent Development in Practice: A Complete Guide to the Skill Mechanism and Production-Ready Engineering
Deep dive into OpenClaw's Skill mechanism for AI Agent development, covering Function Calling, RAG, production deployment, and resume-worthy project design.
Tutorials5 Fatal AI Agent Failure Modes: A Practical Guide to Safe Architecture Design
Deep dive into 5 fatal AI Agent failure modes: infinite loops, tool hallucination, context explosion, error cascades, and permission escalation — with practical safety architecture solutions.
Deep DivesHarness Engineering Explained: Core Methodology and Implementation Guide for Industrializing AI Agents
Deep dive into Harness Engineering methodology: Agent=Model+Harness formula, the Prompt→Context→Harness evolution path, and a developer implementation guide.
Product ReviewsGPT-5.5 Deep Dive: Coding, Automation & Agent Capabilities Tested
Deep dive into GPT-5.5: from chat assistant to autonomous agent. 20-minute coding tasks, end-to-end workflow automation, benchmarks, pricing & safety.
Deep DivesAgent 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.
Deep DivesMCP Protocol Architecture Deep Dive: Host-Client-Server Three-Layer Design and Three Core Primitives
Deep dive into MCP's Host-Client-Server three-layer architecture and its Resources, Tools, Prompts primitives. Learn how it transforms AI tool integration from M×N to M+N.