A series of practical AI/LLM cheatsheets for building production apps.
Start with Cheatsheet 01 — LLM Basics .
AI/LLM Cheatsheet 01 — LLM Basics
Cheatsheet: API basics, tokens, costs, model choices.
AI / LLM Cheatsheets
20 practical AI/LLM cheatsheets — LLM APIs, RAG, agents, eval.
AI/LLM Cheatsheet 02 — Prompt Engineering
Cheatsheet: prompt patterns, system messages, few-shot, CoT, role play.
AI/LLM Cheatsheet 03 — Tool Use / Function Calling
Cheatsheet: tool schemas, OpenAI + Anthropic patterns, parallel.
AI/LLM Cheatsheet 04 — Embeddings
Cheatsheet: embedding APIs, dimensions, normalization, similarity, chunking.
AI/LLM Cheatsheet 05 — RAG Patterns
Cheatsheet: RAG pipeline, chunking, retrieval, rerank, citations.
AI/LLM Cheatsheet 06 — Agents
Cheatsheet: agent loop, ReAct, tool use, memory, multi-agent.
AI/LLM Cheatsheet 07 — LangChain Patterns
Cheatsheet: LangChain LCEL, runnables, retrievers, agents.
AI/LLM Cheatsheet 08 — Streaming Patterns
Cheatsheet: SSE setup, fastapi streaming, frontend EventSource.
AI/LLM Cheatsheet 09 — Function Calling Patterns
Cheatsheet: function calling patterns and gotchas.
AI/LLM Cheatsheet 10 — Evaluation
Cheatsheet: eval frameworks, golden datasets, LLM-as-judge.