#cognitive framework
31 related articles
·3 min
AI Agent Learning Roadmap: A Four-Step Practical Guide from Zero to Job-Ready
A proven AI Agent learning roadmap covering four core elements, mainstream architecture patterns, multi-agent collaboration, and hands-on projects to go from zero to job-ready in three months.
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·3 min
AI Large Language Models Explained: Transformer Architecture & Practical Testing Guide
Deep dive into AI large model principles, from Transformer architecture to probabilistic inference, with practical guidance on LLM applications in testing and AI testing strategies.
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·4 min
AI Engineer Job Search: The Capability Leap from Demo to Production System
AI job demand is surging but companies can't find qualified candidates. Learn the 3 core skills—advanced RAG, local model deployment, and full-stack monitoring—to leap from demo builder to production engineer.
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·3 min
From Tokens to Agents: A Deep Dive into the Core Logic Behind AI's Key Concepts
A systematic breakdown of core AI concepts — Token, RAG, Agent, MCP, Function Call — tracing the evolution from probabilistic text prediction to autonomous agents.
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·3 min
Pangu Skill: An Open-Source Project That Distills 18 Business Leaders into Callable AI Protocols
Pangu.skill is an open-source project that distills 18 top business leaders' cognitive patterns into callable AI protocols, enabling 24/7 decision analysis.
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·3 min
AI Agent Development Tutorial: A Practical Guide from Zero to One-Person Company
A systematic guide to AI Agent development covering the three-stage learning path, core tech stack including LLM, RAG, and LangChain, plus how to build a one-person company through automated Agent workflows.
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·4 min
Core Methodology of Prompt Engineering: A Systematic Deep Dive from Principles to Practice
A deep dive into prompt engineering principles and core methodology. Master three keys to high-quality prompts: specific, rich, and unambiguous. Learn tuning techniques and advanced programming integration.
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·2 min
Claude Code vs ByteDance Codex: A Guide to Chinese Learning Resources and Choosing the Right Tool
Compare Claude Code and ByteDance Codex: their positioning, core capabilities, and use cases. Includes Chinese learning resource recommendations and beginner path selection guide for AI programming.
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·4 min
AI Large Language Model Learning Roadmap: A Complete Guide from Zero to Project Implementation
A systematic AI LLM learning roadmap covering prompt engineering, RAG, AI Agent development, and fine-tuning — with beginner-friendly paths and practical tips.
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·3 min
LangGraph Core Explained: Its Relationship with LangChain and Multi-Agent Orchestration Principles
Deep dive into LangGraph's core positioning, its relationship with LangChain, practical code comparisons of Chain vs Graph, understanding Agent essentials, and multi-agent orchestration design.
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·4 min
AI Super Week: Hundred-Billion-Dollar Capital, the Agent Revolution, Safety Crises, and China's New Landscape
Deep analysis of AI Super Week's four themes: Alphabet's $80B raise and Anthropic's IPO ignite capital markets, OpenAI Codex drives the Agent work revolution, Florida's first AI lawsuit sounds safety alarms, and China's WeChat Agent charts a differentiated path.
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Tutorials·3 min
How Ordinary People Can Build Products with AI Programming
AI programming tools let anyone build products, but zero-experience users still struggle. Learn why Python basics and key strategies help you direct AI effectively.
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Deep Dives·3 min
MCP (Model Context Protocol): Solving the Three Core Pain Points of AI Tool Calling
Deep dive into how MCP (Model Context Protocol) solves three core pain points of Tool Calling: verbose descriptions, unstable invocations, and lack of unified standards.
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Expert Opinions·3 min
Is Learning to Code Still Worth It in the AI Era? An Honest Answer from an Atlassian Engineer
Can AI write code instantly—so is coding still worth learning? An Atlassian engineer breaks down the truth behind tech leaders' claims and AI coding limitations.
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Deep Dives·3 min
How Multi-Agent Teams Solve AI Hallucination and Make AI Reliable
Deep analysis of how multi-agent architecture solves AI hallucination. From context rot to adversarial debate mechanisms, see how Anthropic, xAI, and Kimi reduce hallucination rates from 12% to 4.2%.
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Tutorials·4 min
Complete Guide to Developing WeChat Mini Programs with AI: From Zero to Launch for Just $4
Complete guide to developing WeChat Mini Programs with AI tools like Cursor and Trae: account setup, requirements docs, AI-assisted coding, debugging, and publishing—all for under $14.
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Tutorials·4 min
AI Trading Bot Battle Royale: Natural Selection Among 15 Agents to Find the Most Profitable
15 AI trading Bots each holding $1,000 compete live on Hyperliquid, with natural selection eliminating losers. Reveals real win rates, optimal strategies, and key risks of AI autonomous trading.
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Tutorials·3 min
Getting Started with FastAPI: A Comprehensive Guide to Frontend-Backend Separation and RESTful API Core Concepts
A systematic guide to core concepts for FastAPI beginners, covering frontend-backend separation architecture, RESTful API design, and JSON data format advantages for Python developers.
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Tutorials·3 min
Learn AI Agents in 30 Days: A Four-Stage Learning Roadmap from Zero to Production
A systematic breakdown of the AI Agent learning roadmap covering core architecture, ReAct/CoT paradigms, multi-agent collaboration, and Prompt optimization across four stages with quality resource recommendations.
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Tutorials·1 min
AI Agent Learning Roadmap: A Complete Guide from LLM Fundamentals to Enterprise-Level Project Implementation
A systematic AI Agent learning roadmap covering Python setup, Prompt Engineering, RAG, LangChain, multi-Agent collaboration, with enterprise medical consultation system case study and phased learning plan.
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