AI/LLM Cheatsheet 11 — Cost Optimization
Cheatsheet: prompt caching, batching, model selection, output limits.
Ai-Llm
AI/LLM Cheatsheet 12 — Local LLMs (Ollama, vLLM)
Cheatsheet: Ollama, vLLM, llama.cpp, when to self-host.
AI/LLM Cheatsheet 13 — Fine-tuning
Cheatsheet: when to fine-tune, LoRA, QLoRA, OpenAI fine-tune.
AI/LLM Cheatsheet 14 — Multimodal LLMs
Cheatsheet: vision LLMs, image inputs, audio, video.
AI/LLM Cheatsheet 15 — Security and Prompt Injection
Cheatsheet: prompt injection, defenses, PII, jailbreaks.
AI/LLM Cheatsheet 16 — Vector DBs Deep Dive
Cheatsheet: vector DBs, HNSW, hybrid search, sharding.
AI/LLM Cheatsheet 17 — Observability for LLMs
Cheatsheet: logging, traces, metrics, evals in prod.
AI/LLM Cheatsheet 18 — LLM Application Patterns
Cheatsheet: classification, extraction, summarization, routing, decomposition.
AI/LLM Cheatsheet 19 — Building Chat UI
Cheatsheet: chat UI, streaming, markdown rendering, code blocks.
AI/LLM Cheatsheet 20 — Production LLM App
Cheatsheet: full prod LLM app stack.