Tutorials & Code
Fine-Tuning vs RAG vs Prompt Engineering: How to Choose in 2026
The most expensive question in applied AI, answered with a decision flowchart: when prompting is enough, when you need RAG, when fine-tuning actually pays off — and the order real products layer them.
MCP Explained: The USB-C Port of AI — How Model Context Protocol Works (With Code)
Why every AI tool now advertises MCP support: the architecture, tools vs resources vs prompts,...
LangChain 1.x Tutorial (2026): A-to-Z Guide With Working Code
The complete LangChain 1.x tutorial: create_agent, tools, memory with checkpointers, RAG-as-a-tool, streaming, middleware and LangSmith...
React 19 + AI: The Complete 2026 Guide to Building AI-Powered React Apps
React 19.2 + the AI SDK is the fastest way to ship AI products in...
Verifiers v1 Explained: Prime Intellect’s New Architecture for Agentic RL Training and Evals
Prime Intellect's verifiers v1 splits agentic RL environments into tasksets, harnesses, and runtimes — with...