Reference
Glossary, cheat sheets, curated resources, and answers to frequently asked questions.
6 articles · about 56 minutes of reading
- AI Engineering Glossary: LLM, RAG, Agent, and MCP Terms ExplainedPlain-English definitions of the AI engineering terms used across this wiki, from tokens and embeddings to RAG, tool use, agents, MCP, and evals.Difficulty: Beginner12 min read
- Prompting Cheat Sheet for LLM AppsA one-page reference for writing prompts in production: system prompt skeleton, XML-tagged context, examples, structured output, tool descriptions, and anti-patterns.Difficulty: Beginner9 min read
- Claude API Cheat Sheet for TypeScript DevelopersA one-page reference for the Messages API in TypeScript: request parameters, response fields, stop reasons, streaming events, errors, and the SDK helpers you use daily.Difficulty: Beginner10 min read
- LLM Cost Cheat Sheet: Prices, Formulas, and LeversA one-page reference for LLM costs: token prices at the time of writing, the cost formula with caching and batches, quick estimates, and the levers that cut a bill.Difficulty: Beginner8 min read
- AI Engineering Resources: Official Docs and References Worth BookmarkingA curated list of primary sources for AI full-stack engineers: model and SDK docs, MCP, web stack, databases, retrieval, observability, and security, plus a link checker.Difficulty: Beginner7 min read
- AI Full-Stack Engineering FAQ: Answers to Common QuestionsAnswers to the questions learners ask most: prerequisites, time to job-ready, costs, model choice, fine-tuning versus RAG, agents, frameworks, and setup problems.Difficulty: Beginner10 min read