LLM & AI Literacy
Request SupportRAG basics, prompt engineering, when to fine-tune vs. use APIs, and responsible use—so you can work with LLMs effectively and safely.
Why it matters
LLMs are showing up everywhere. LLM literacy means knowing how they work well enough to use them well: when to prompt, when to add your own data (RAG), when fine-tuning might help, and how to spot limits and risks. We teach by doing so you can make better decisions at work and at home.
What we do
- Prompt engineering – Write prompts that get consistent, useful results; we cover structure, few-shot examples, and when to break a task into steps.
- RAG basics – When and how to connect an LLM to your documents or APIs; we explain retrieval, chunking, and citations in plain language.
- Fine-tune vs. API – When it’s worth training or adapting a model vs. using an API with good prompts and RAG; we help you choose based on data, budget, and control.
- Responsible use – Hallucination, bias, privacy, and compliance; we give you a mental model so you can assess risk and set guardrails.
Format
Sessions can be one-on-one or small group; we use your use cases and tools when possible so the skills transfer directly.
Next step
Tell us your role (developer, PM, writer, etc.) and what you want to do with LLMs (build a product, evaluate vendors, or just stay current). Request support and we’ll design a session or short series.