AI Agents
Curated AI Agents tutorials.
From Demo to Production: A Practical Guide to Agent Harness Engineering
Agent Harness is the engineering infrastructure wrapped around the model, determining the success or failure of AI moving from demo to production. This article systematically covers the core concepts of Harness, the ETCLOVG seven-layer architecture, the five-tier memory system, dynamic workflows, and other key designs. Combined with practical cases like Claude Code, it provides a complete methodology covering context management, tool orchestration, and security governance. Suitable for developers and technical leaders who are bringing AI into real engineering.
BeginnerAI Agent Mid-2026 Review: 6 Major Shifts Reshaping the Industry
In the first half of 2026, AI Agents have fully transitioned from 'proof of concept' to 'production deployment.' This article outlines 6 key shifts impacting the entire industry: plummeting costs, mature multimodality, standardized enterprise security, the MCP ecosystem explosion, the rise of Agent stores, and AI workflows replacing traditional SaaS.
AdvancedAI Agent Frameworks: LangChain, AutoGen & CrewAI for Production in 2025
AI agents go beyond chatbots—they use tools, maintain memory, plan multi-step tasks, and collaborate with other agents. This guide compares LangChain, LangGraph, AutoGen, and CrewAI for different use cases, covers reliable agent design patterns, tool calling best practices, memory architectures (short-term, long-term, episodic), handling errors and hallucinations, and deploying production agents with observability.
IntermediateAI Agent Prompt Engineering: The Complete Guide to Making Your Agent Truly Understand You
There is a fundamental difference between ordinary prompts and Agent prompts. This guide is specifically for AI Agent scenarios, covering System Prompt architecture design, tool call instruction writing, multi-step task decomposition prompts, and core techniques to avoid Agent hallucinations.
IntermediateAI Agent Prompt Engineering in Practice: A Complete Framework for Writing High-Quality System Prompts
Prompt quality is the decisive factor in AI Agent performance. Based on extensive Agent project experience, this article summarizes a complete System Prompt design framework covering role definition, tool usage guidelines, output format control, error handling, and key techniques to avoid common runaway behaviors.
IntermediateThe Complete Guide to AI Agent Workflow Automation: From Zero to Production Deployment
Workflow automation is one of the highest-value scenarios for AI Agents. This article uses a 'daily competitive intelligence auto-collection + summary + push' pipeline as the main thread, explaining step by step how to use n8n for orchestration, Dify for AI processing, and MCP Server for tool integration to build a truly usable automation system.
AdvancedAI Agents in Production: Architecture Patterns and Reliability Engineering
AI agents—autonomous systems that use tools and make decisions to complete multi-step tasks—are moving into production at enterprise scale. This guide covers reliable agent architecture: tool design and error handling, state management for long-running agents, human-in-the-loop patterns, observability and debugging agents, graceful failure modes, security considerations, and testing strategies for non-deterministic systems.
AdvancedBuilding Financial Analysis Agent with AI Agents: Complete Guide 2026
Building Financial Analysis Agent with AI Agents 2026 Introduction AI agents that can analyze financial data and generate investment reports are transforming how developers work. This guide shows you how to build a production-ready Financial Analys
AdvancedBuilding SQL Query Agent with AI Agents: Complete Guide 2026
Building SQL Query Agent with AI Agents 2026 Introduction AI agents that can translate natural language to SQL and execute queries are transforming how developers work. This guide shows you how to build a production-ready SQL Query Agent using Lang
IntermediateCrewAI Tutorial 2026: Build Multi-Agent Systems That Work Together
Complete tutorial for building multi-agent AI systems using CrewAI in 2026. Covers agent role design, task delegation, crew orchestration, tool integration, and building production workflows where multiple specialized AI agents collaborate on complex tasks.
AdvancedLangGraph Complete Guide 2026: Build Stateful AI Agents
LangGraph Complete Guide (2026): Build agents as state machines—State+reducer, conditional edges, checkpointer persistence (multi-turn memory/crash recovery/time travel), interrupt for human approval gates, multi-agent supervisor pattern. Includes an honest comparison of when to use it and when not to.
IntermediateLoop Engineering: The New Paradigm for AI Coding Agents
Loop Engineering is a new paradigm for AI coding agent collaboration, centered on replacing manual agent instructions with automated loops. This article dives into the five core modules (automated scheduling, worktrees, project skills, plugin connectors, sub-agents) and persistent memory, with concrete implementations in Claude Code and Codex, plus Anthropic's internal Skills taxonomy and writing tips. Ideal for intermediate to advanced developers looking to move from manual operations to systematic agent orchestration.
IntermediateBuild an AI Customer Support Agent with OpenAI Assistants API 2026
Step-by-step tutorial for building an AI customer support agent using the OpenAI Assistants API. Covers creating assistants, uploading knowledge base files, implementing function calling, managing threads, and deploying to production.
BeginnerReplit Agent Complete Tutorial 2026: AI Writes, Runs, and Deploys Your Code End-to-End
Replit Agent Complete Tutorial (2026): A conversational full-stack assistant in a real Linux environment—from a one-sentence requirement to a public URL. Includes acceptance criteria upfront prompts, Agent vs Assistant cost division, Secrets/Checkpoint engineering habits, and comparison with Bolt/Cursor.
BeginnerSkill vs Agent vs Model: Understanding the Relationship at a Glance
Clarifying Model vs Agent vs Skill in AI: the model is the base capability, an agent is an autonomous tool-using system, a skill is a reusable capability unit — with a comparison table and examples.
AdvancedWindsurf vs Devin vs SWE-agent: Autonomous Coding AI 2026
Windsurf vs Devin vs SWE-agent autonomous coding comparison (2026): ranked by autonomy—Windsurf human-in-the-loop, Devin fully autonomous AI engineer, SWE-agent open-source research framework (SWE-bench). Includes selection guide and production reliability.
IntermediateWorld Models: The Next Piece of the Puzzle from Theory to Embodied Intelligence
World models are emerging as the next technological focus after large models, aiming to enable AI to understand physical laws, predict action consequences, and plan autonomously. Starting from Yann LeCun's JEPA theory, this article explains the core definition of world models, hierarchical planning architecture, and energy model foundations. It then introduces Kairos's leading performance across four benchmarks, γ-World's multi-agent expansion capabilities, and industry practices from ForceMind, Accelerated Evolution, and Jiuwen Symbiosis. Finally, it discusses data flywheels, open-source ecosystems, and future challenges, providing developers with a panoramic view from theory to deployment.