Everything you need to know about AI.
Foundational knowledge, the latest tools, and how to apply them in your work — all in one place, whether you're just starting out or already use AI every day.
Featured articles
A curated selection of articles to help you understand AI more clearly and see it more deeply.
- Applications
How Does Memory Work in Claude Code?
Optimize Claude Code memory using CLAUDE.md and auto-memory systems to keep persistent project context and high instruction adherence across sessions.
Tuan Tran Van - Applications
Understanding Spec-Driven Development
Spec-driven development makes a structured specification the primary source of truth for AI coding agents, replacing vibe coding with a verifiable contract.
Tuan Tran Van - Applications
The Best Claude Code Skills to Make Claude Work Like a Senior Engineer
A lean, audited checklist of the Claude Code skills worth installing — the ones that make Claude plan, test, review, and ship like a senior engineer.
Tuan Tran Van - Applications
The GitHub Repos and Websites That Help You Master Claude Code
A hand-picked roundup of the GitHub repos and websites that help you master Claude Code and work better with AI.
Tuan Tran Van - Applications
Claude Code's /goal Command: Engineering Autonomous Cycles
The /goal command in Claude Code enables autonomous execution of long-running development tasks using an evaluator-loop and persistent completion conditions.
Tuan Tran Van - Applications
Loop Engineering: Building Software With Agent Loops
Learn loop engineering: the transition from manual prompting to designing autonomous systems that use agents to discover, implement, and verify work.
Tuan Tran Van - Applications
The Ralph Loop: Run AI Agents in a Bash Loop Until They Finish
Achieve autonomous AI coding with the Ralph Loop. Solve context rot, implement PIN systems, and use bash-scripted iterations for AFK development.
Tuan Tran Van - Applications
Harness Engineering: Build the Scaffolding Around an AI Model
Harness engineering builds the deterministic scaffolding, feedback loops, and constraints around an AI model so agents run reliably in production.
Tuan Tran Van - Knowledge
Everything you need to know about MCP
The Model Context Protocol (MCP) is an open standard connecting AI models to data and tools, replacing custom integrations with a universal 'USB-C' interface.
Tuan Tran Van - Applications
Why You Should Stop Using /init to Generate Your CLAUDE.md
Stop using /init for your CLAUDE.md. Engineering benchmarks show auto-generated files raise costs by 20% and dilute the agent's context with noise.
Tuan Tran Van - Applications
What Is Agentic Engineering? A Guide for Engineers
Agentic engineering is a disciplined practice where AI agents handle implementation while humans oversee architecture and validation to ensure reliability.
Tuan Tran Van - Knowledge
What Is an AI Agent? Components, Loop, and Types
An AI agent is an autonomous system using LLMs to reason, plan, and execute multi-step tasks independently to achieve high-level goals.
Tuan Tran Van - Knowledge
AI Models Explained
AI models are mathematical systems trained on data to recognize patterns. Learn about their internal architecture, training phases, and functional tiers.
Tuan Tran Van - Knowledge
Understanding and Managing the LLM Context Window
How the context window works as an LLM's working memory, why quadratic scaling makes it costly, and how to prevent context rot and hallucinations.
Tuan Tran Van - Applications
A Guide to Context Engineering
Context engineering is the systems discipline for managing an LLM's information state to prevent context rot and "Lost in the Middle" performance drops.
Tuan Tran Van - Applications
Software Engineer in the Age of AI
The role of a software engineer in the age of AI is shifting from writing syntax to designing robust architectures and managing complex system failures.
Tuan Tran Van - Knowledge
Artificial Intelligence: History, Machine Learning, and AI Agents
Artificial Intelligence lets machines simulate human learning and reasoning. A guide to its history, machine learning, generative models, and AI agents.
Tuan Tran Van - Knowledge
What is generative AI? Models, mechanics, and real limits
Generative AI creates new text, images, and code by learning probability distributions from massive datasets — its models, mechanics, and real limits.
Tuan Tran Van - Knowledge
What Are Large Language Models (LLMs)? How They Work
Large Language Models predict the next token from statistical patterns. How LLMs learn, the three-stage training pipeline, and why they still hallucinate.
Tuan Tran Van - Knowledge
AI Tokens and Context Windows: A Practical Guide
AI tokens are the smallest units a language model reads and writes, and the context window is the memory limit that decides how much it can hold at once.
Tuan Tran Van - Applications
The Evolution of Vibe Coding: From Trend to Discipline
Vibe coding raced from viral prototype trick to production liability, and teams are now shifting to agentic engineering where humans own the architecture.
Tuan Tran Van