LLM (Large Language Model)explained

A Large Language Model is trained on a vast amount of text and learns the patterns of language well enough to write, summarise, answer questions, translate, and follow instructions. GPT, Claude, and Gemini are LLMs. You interact with one by giving it a prompt and reading its response.

What makes LLMs useful in a product is that they handle open-ended language tasks that used to need a human: drafting replies, extracting details from messy documents, powering a support chatbot, categorising feedback. You typically access them through an API rather than training your own.

The catch every founder should internalise: an LLM predicts plausible text, it doesn't 'know' facts. It can sound confident and be wrong — this is called hallucination. That's exactly why techniques like RAG and careful prompt engineering exist: to ground the model in your real data and keep its answers accurate and useful.