Articles & Tutorials
149 technical articles covering AI, Machine Learning, Cybersecurity, Data Science, and Programming. Practical guides, tutorials, and deep dives — written for developers.
AI Agent Skills and Plugins: How Developers Should Evaluate Third-Party Extensions
Key Takeaway Not all AI agent skills and plugins are safe. Before installing any third-party extension, evaluate it across six …
AI Agent Supply-Chain Security: Protecting Models, Tools, Skills and Dependencies
Key Takeaway AI agents depend on a complex supply chain of models, packages, MCP servers, skills, plugins, repositories, and co…
Indirect Prompt Injection: When Websites and Documents Attack AI Agents
Key Takeaway Indirect prompt injection occurs when an AI agent processes untrusted external content that contains hidden malici…
Prompt Injection Explained: How AI Applications Can Be Manipulated
Key Takeaway Prompt injection is the #1 vulnerability in LLM applications (OWASP LLM Top 10 2025). It occurs when an attacker m…
MCP vs Function Calling vs Plugins: Understanding AI Tool Integration
Key Takeaway Function calling is ideal for simple, single-vendor integrations. MCP excels at scalable, cross-model tool ecosyst…
The Privacy Problem with Cloud AI
Key Takeaway --> 🎯 You can build a fully private AI agent that runs entirely on your local machine—local LLM + MCP server + local t…
The Problem: AI Without Context
Key Takeaway --> 🎯 RAG retrieves relevant knowledge from your documents. MCP connects AI agents to tools and data sources. Together…
Why Build MCP Servers?
Key Takeaway --> 🎯 The best way to learn MCP is by building. These 10 projects progress from beginner to advanced, teaching Python,…
Why MCP Security Matters
Key Takeaway --> 🎯 MCP introduces new attack surfaces for AI systems. This 25-point checklist covers authentication, authorization,…
What We'll Build
Key Takeaway --> 🎯 Building an MCP server in Python takes just 15 lines of code. The MCP Python SDK handles protocol, validation, a…
First, What Is an API?
Key Takeaway --> 🎯 APIs connect applications to services. MCP connects AI agents to tools and data. MCP isn't replacing APIs—it's a…
Why One Agent Isn't Enough
Key Takeaway --> 🎯 Multi-agent systems split complex tasks across specialized agents—planner, coder, tester, security, reviewer—eac…
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RAG Fundamentals
From embeddings to production RAG systems
Prompt Engineering
Master the art of communicating with AI
AI Security
Secure your AI applications and data
Local AI
Run AI models on your own hardware
MCP & AI Agents
Build connected AI agent systems
Data Science Pipeline
From data to insights
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📰 Latest Articles
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Hand-selected for practical valueWhy RAG Exists: The Hallucination Problem
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