LLM (Large language model)

Why LLMs matter

LLMs make it practical to automate work that involves reading and writing: emails, documents, forms, tickets and notes. Tasks that once needed custom rules can often be handled with a well-designed prompt and checks.

How LLMs work

An LLM breaks text into tokens and predicts the most likely next token, one at a time, based on patterns learned in training. Instructions, examples and retrieved documents in the prompt steer what it produces.

Models differ in cost, speed, context length and skill, so the right model depends on the task.

Common LLM mistakes

Treating output as fact without checking. Choosing the largest model by default when a smaller one is cheaper and good enough. Sending sensitive data to a provider without reviewing its terms.

How Gr8r approaches LLMs

We pick models per task and test them against your real inputs. We treat model output as untrusted until the application checks it, and we design the interface for when the model is wrong.