94 related articles
Building an Agent Framework from Scrat…
Learn how to split AI Agent capabilities into four modules—Tool Registry, Message Store, Agent Runtime, and Built-in Tools—and build a reusable, extensible Agent framework using Python decorators.
AI Agent Learning Roadmap: From Beginn…
A detailed three-month AI Agent learning roadmap covering LLM basics, ReAct paradigm, LangChain, memory mechanisms, tool calling, and multi-agent collaboration with practical project suggestions.
Tech FrontiersMeta Superintelligence Labs releases Muse Spark, a native multimodal reasoning model supporting visual chain of thought, tool-use, and multi-agent orchestration. Deep dive into its capabilities and competitive positioning.
Harness Engineering: A Practical Guide…
Explore the three stages of AI programming evolution: from Prompt Engineering to Context Engineering to Harness Engineering. Master enterprise-grade AI coding with Cloud Code + VS Code.
Warp 2.0 Deep Dive: An AI Development …
Deep dive into Warp 2.0's Agent Development Environment (ADE): multi-agent parallel orchestration, terminal editor, AI coding platform, hands-on SaaS app building, and comparison with Cursor and Claude Code.
Tech FrontiersThis week's tech roundup analyzes OpenAI's Swarm Agent framework, Anthropic's Claude data visualization app, Kali Linux, Unikraft lightweight OS, and Go Blueprint — covering AI, security, and cloud computing.
Product ReviewsDeep dive into Website Cloner, a 14,000+ Star open-source project that uses a four-step AI pipeline to clone any website into a runnable Next.js project with one command.
TutorialsExplore Claude Code multi-Agent collaboration with Planner+Packager Subagents for semi-automated project iteration, plus a lite TARS orchestration concept revealing Agent inter-calling limits.
TutorialsA hands-on tutorial for building a financial report analysis AI Agent from scratch using Cursor editor, Skills definitions, and MiniMax M2.1. Covers setup, architecture, Skills methodology, and multi-language programming.
Product ReviewsDeep comparison of Qoder, Cursor, Windsurf, and Devin across autonomy, reliability, and context capabilities to help developers choose the right AI coding assistant.
TutorialsLearn how to redirect Claude Agent SDK API requests to local LLMs via LiteLLM Proxy, achieving zero-cost inference while retaining full agent framework capabilities.
Deep DivesA deep dive into AI Agent development methodology, from the ReAct theoretical framework to a four-layer enterprise tech stack covering model services, Agent types, LangChain, and production deployment.
Deep DivesDeep comparison of Claude sub-agents vs agent teams: architecture differences, use cases, and real-world results. A Pokémon RPG case study shows how agent teams achieve 95%+ feature completeness.
Deep DivesA systematic breakdown of AI's four-stage evolution from Chat Mode to Agentic AI, covering multi-agent architectures, ReAct framework, and MCP protocol.
TutorialsA systematic four-stage learning roadmap for programmers transitioning to AI Agent development, covering core theory, ReAct and classic paradigms, Prompt engineering, and hands-on projects.
Tech FrontiersDeepSeek releases OCR2 replacing CLIP with an LLM as visual encoder; Moonshot AI launches Kimi K2.5 with 100+ sub-agent cluster mode; Microsoft deploys 3nm Maia 200 chip; Alibaba releases Qwen3 Max Thinking.
TutorialsDeep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
Deep DivesWhy do longer Prompts make AI Agents less stable? This article explains the control flow first architecture, replacing natural language control flow with code orchestration to boost multi-step reliability from 40% to over 90%.
Tech FrontiersAnthropic adds custom sub-agents to Claude Code, Cursor launches code review Agent BugBot, Qwen releases 92-language translation model, and Google unveils three experimental AI products.
TutorialsDeep dive into the Three-Layer Pyramid Model for Agent development, covering autonomous agents, collaborative multi-agent systems, and universal orchestration agents with a complete learning path from beginner to industrial-grade deployment.