Topic
Prompt Templates & Variables
5 posts on prompt templates & variables — part of glossary on the n4n AI blog.
What is a prompt template? A practical explanation
A prompt template explained: what it is, how variable substitution works, why it matters for production LLM systems, and a concrete code example with common pitfalls.
Prompt variables explained: filling templates dynamically
Prompt variables let you inject dynamic values into prompt templates at runtime. Learn how they work, why they matter for production LLM systems, and common pitfalls to avoid.
How to version control your prompt templates
Learn how to version control prompt templates with git, schema validation, CI/CD checks, and environment-specific overrides for production LLM systems.
How to build reusable prompt templates for your app
Learn to build reusable prompt templates with versioning, validation, and variable interpolation for production LLM applications.
Common mistakes when designing prompt templates
Eight prompt template mistakes that break production LLM apps, with code patterns to fix each one.
More topics in glossary
- Structured Outputs & JSON Mode19
- AI Agents Fundamentals12
- Hallucination in LLMs11
- Sampling Parameters: Top-p, Top-k & Penalties11
- Context Window & Context Length10
- Fine-Tuning Fundamentals9
- Foundation Models: Base vs Instruct vs Chat9
- Model Families & Naming Conventions: GPT-5, Claude, Gemini 3, Llama 4, Mistral, DeepSeek, Qwen, Grok9
- Grounding & Fact-Checking in AI8
- LLM Benchmarks: MMLU, HumanEval, SWE-bench & GPQA8
- Max Tokens, Stop Sequences & Output Truncation8
- Quantization Formats: GGUF, GPTQ, AWQ & INT4/INT88