Neo Kim — If You Want to Get Good at AI Engineering
- Author: Neo Kim (System Design One)
- Source: LinkedIn Post
- Tags:
system-design-one,neo-kim,ai-engineering
Overview
Neo Kim (System Design One newsletter) shares the concepts to learn to get good at AI engineering in 2026 — each linked to a deep-dive explainer:
- LLM Evals Explained
- Design a Knowledge Q&A System
- How OpenClaw Works
- AI Agent Workflow
- How MCP Works
- Design an AI Chat Assistant
- How RAG Works
- Agentic Patterns Explained
- AI Coding Workflow 101
- Machine Learning System Design 101
- Multi-Agent Architecture Explained
- How AI Agents Work
- How Vector Databases Work
- AI Agents: Memory, State & Consistency
- AI Agents Design
- Context Engineering Fundamentals
- What is Reinforcement Learning
- LLM Concepts — A Deep Dive
The throughline: evals, RAG, MCP, agentic patterns, and context engineering are the core literacy — not just calling an LLM API.
Related
- new-rules-software-engineering-ai-studio — New rules of software engineering (Beyond Coding)
- systemdesign-one-agentic-ai-use-cases — System Design One on agentic AI
- neo-kim-12-books-99-percent-engineers — Neo Kim’s 12 books for engineers