33 related articles

Exposing the "GPT-5.6 free trial" scam circulating on social media. Learn about data risks of third-party AI mirror platforms and how to identify AI marketing traps.

A fresh grad interviewing for a GenAI Trainer role faced prime number coding and activation function questions while the interviewer used Gemini to generate questions live — exposing AI hiring chaos.

Fake AI platforms claim to offer "GPT 5.6" and "Claude 5" — models that don't exist. Learn the real risks: data theft, scams, and how to safely use AI tools.

Demystify large language models using middle-school math: LLMs are complex functions, training solves for parameters, and inference predicts next-token probabilities.

A complete guide to AI manga production: from scriptwriting to storyboard generation. Learn the universal formula, avoid common pitfalls, and launch your first episode.

A deep dive into AI agents: core concepts, how they differ from LLMs, the Agent = LLM + Workflow + Knowledge Base formula, and a comparison of Coze, Dify, LangChain, and LlamaIndex.

What is an AI agent? How does it differ from a large language model? Learn the core concepts, the Agent formula (LLM + Workflow + Knowledge Base), and how to choose between Dify, LangChain, and LlamaIndex.

Learned Claude, n8n, or Coze but unsure how to monetize? This article breaks down the core logic of AI automation monetization: prove business value with data, build case studies, and develop a credible personal brand.

Full breakdown of a real AI testing pipeline: API collection, doc enrichment, AI test case generation, Agent-driven execution, and test reports — with Skills, RAG, and Harness engineering.

When AI coding assistant Fable sparked community frenzy, one developer admitted he 'couldn't feel the magic.' A deep look at survivorship bias, hype psychology, and rational AI tool evaluation.

A psychology study on corporate buzzword receptivity reveals the cognitive traps behind AI industry hype. Why do jargon-speakers outshine engineers? A deep dive.

A structured AI Agent learning roadmap covering fundamentals (Agent principles, Prompt engineering), advanced topics (RAG, multi-agent collaboration), and three hands-on projects — ideal for beginners.
Loving LLMs, Hating the Hype: How Engi…
Engineers love LLMs for real productivity gains but hate the hype around AGI narratives, glossed-over hallucinations, and valuation bubbles. Here's how to find the rational balance.

How to find AI courses worth paying for amid the flood of beginner content. A guide to evaluating courses on Agentic workflows, RAG, fine-tuning, and more.

Resume full of RAG and Agent but keep failing interviews? The issue is you only run demos and can't explain production engineering challenges. This article breaks down data cleaning, hybrid retrieval, hallucination protection, and agent loop breakers.

The gap between AI power users and everyone else isn't about prompt tricks — it's about understanding LLMs, multimodal models, workflows, and agents. Build your complete AI mental model here.

What exactly is the Cloud Coding Agent Silicon Valley is hyping? This article breaks down the core concept across three axes—where it runs, who watches, where tasks start—and gives users in China practical advice on local alternatives.

From Prompt Engineering to Harness Engineering, a deep dive into the core challenge of truly deploying AI Agents in enterprises. This article breaks down the six-layer architecture and shares real-world Hermes Agent practice.

Want to switch careers into LLM development but don't know where to start? This guide breaks down a four-level skill roadmap — from basics and API calls to RAG, fine-tuning, Agent development, and multimodal — to help you build real AI career value.

When "AI-powered" becomes a magic phrase for valuation premiums, are companies paying for technology or for a story? A deep analysis of AI hype cycles, the gap between narrative and reality, and how to identify genuine AI value.