#agent engineering
3710 related articles
·2 min
Skill and MCP: The Two Pillars of Agent Engineering Architecture
Deep dive into how Skill and MCP collaborate in Agent engineering. Skills handle business logic loops while MCP provides standardized connectivity, forming the core of modern four-layer Agent architecture.
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·2 min
Skill and MCP: The Two Pillars of Agent Engineering Architecture
Deep dive into how Skill and MCP work together in Agent engineering. Skill handles business logic; MCP provides standardized connections. Together they form the core of modern Agent architecture.
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·4 min
Harness Engineering: A New Software Development Paradigm Where Humans Steer and AI Agents Execute
OpenAI engineer Ryan Lopopolo introduces Harness Engineering — a methodology where humans build constraint systems and AI agents handle all code implementation.
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·4 min
Core Principles of Coding Agents: How Perception and Context Engineering Determine AI Coding Effectiveness
Deep dive into why coding Agents differ: perception lets Agents understand projects first, context engineering precisely filters information within limited token budgets.
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Deep Dives·3 min
Deep Dive into Hermes Agent Self-Evolution: The GIPA Algorithm and Engineering Practice
Deep analysis of NousResearch's Hermes Agent Self Evolution project: GIPA genetic Pareto prompt evolution algorithm, six-step optimization loop, and five guardrail mechanisms for real-world Agent self-evolution.
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Tutorials·2 min
AI Agent + Vue 3 Full-Stack Development in Practice: Integrating the Coze Platform with Frontend Engineering
A deep dive into integrating AI agents with Vue 3 frontend development, covering Coze platform agent building, Vue3+TypeScript+Pinia stack practices, and AI content generation features.
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Deep Dives·4 min
Is Context Engineering the Core of Agent Development? A Deep Dive into Architecture and Practical Solutions
Deep dive into context engineering as the core of Agent development, covering five context modules, four pain points, and dynamic assembly solutions including compression, hybrid retrieval, multi-Agent architecture, and state machine control.
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Tutorials·1 min
Harness Engineering: Essential Architecture Guide for Agent Development
Deep dive into Harness Engineering architecture for AI agents: multi-agent collaboration, memory management, middleware design, MCP integration, and LangChain's DeepAgent framework.
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Tutorials·2 min
Is Context Engineering the Core of Agent Development? A Deep Dive into a High-Frequency Interview Question
Deep dive into a top LLM interview question: Is context engineering the core of Agent development? Covers five context modules, four pain points, and advanced solutions.
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Tutorials·3 min
Building AI Agents with Node.js: Replacing Prompt Engineering with Function Calls
Learn how to refactor a Node.js AI Agent using Function Calls instead of prompt engineering. Covers tool definition via JSON Schema, the Agent Loop, and key implementation details from analyzing Claude Code.
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Tutorials·2 min
Harness Engineering Deep Dive: Multi-Level Memory and Multi-Agent Collaborative Development in Practice
Deep dive into Harness Engineering: deconstructing Claude Code's multi-level memory, defense-in-depth, Hermes Agent autonomous evolution, and multi-Agent collaboration for industrial-grade AI development.
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Tutorials·3 min
Harness Engineering: A Practical Guide to AI Development — From Prompts to Mastering AI Agents
A deep dive into Harness Engineering's three-layer architecture: Information, Constraint, and Automation layers, covering Agent failure modes, OpenAI and Anthropic best practices, and AI tool selection strategies for controlled AI development.
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Tutorials·2 min
npcpy: An Open-Source Framework That Rethinks AI Agent Development with Software Engineering Principles
Deep dive into npcpy's four-layer architecture, multi-agent collaboration, knowledge graph lifecycle management, and deployment strategies for building stable, controllable AI Agent systems.
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Tutorials·3 min
Deep Agents: Enterprise-Grade Agent Engineering and Deep Research Implementation Guide
Learn how the Deep Agents framework solves enterprise AI Agent challenges like tool sprawl and context pollution, with a complete Deep Research implementation guide covering task decomposition, multi-source integration, and structured report generation.
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Expert Opinions·1 min
Karpathy on Vibe Coding and Agentic Engineering: A Paradigm Shift for Programmers
Karpathy explains the paradigm shift from vibe coding to agentic engineering, how LLMs reshape programming in the Software 3.0 era, and why verifiability matters.
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Industry Insights·1 min
Karpathy Joins Anthropic: An Industry Shift from Vibe Coding to Agentic Engineering
AI leader Andrej Karpathy officially joins Anthropic's pretraining team, marking his evolution from Vibe Coding to Agentic Engineering and a return to frontier AI research.
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Tutorials·1 min
Claude Code Multi-Agent Parallel Development in Practice: Post-Mortem and Engineering Pitfall Guide
Practical guide to Claude Code Agent Teams multi-agent parallel development, covering 7 common pitfalls like naming conflicts, AI-invented APIs, and token limits, with complete engineering solutions.
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Deep Dives·1 min
Harness 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.
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Tutorials·2 min
OpenAI Codex Hands-On Tutorial: A Complete Guide to Prompt Engineering, Agent Skills & Cloud Automation
Deep dive into OpenAI Codex's three core capabilities: prompt engineering for better code generation, agent skills for autonomous programming, and cloud automation for end-to-end CI/CD pipelines.
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Tutorials·1 min
Andrew Ng's New Course Explained: Agent Memory Engineering from Basics to Practice
Deep dive into Andrew Ng's Agent Memory course with Oracle: covering memory engineering concepts, memory-first architecture design, and building AI agents with persistent memory.
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