How does Breezy 'know' what to say to your customers?

LLM stands for large language model, a sophisticated AI system designed to understand and generate human-like text. Imagine it as an advanced version of your phone's predictive text feature, but on a much larger scale. When you input a phrase, it doesn't just randomly guess the next word.

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Instead, it uses algorithms and patterns derived from extensive training on diverse sources like websites, books, and online discussions to predict the most appropriate continuation. This training allows it to generate coherent and contextually relevant responses. It is predicating what it thinks a human would say.

How does it “decide” what to say?

LLMs don’t decide like a person. They don’t pause, reflect, or weigh pros and cons. Instead,

• You give it a prompt, a question, instruction, or request i.e "Write a message to a customer who missed their booking"
• It looks at your prompt and its training and calculates: “What is the most likely, most useful next word in this situation?”
• It does this again and again, word by word, sentence by sentence. The result is a response that sounds smart because it follows patterns from real human writing
• This loop happens millions of times during training.

What influences Its “decision”?

Here’s what shapes what ChatGPT says back to you:

• Your prompt: Clear, detailed prompts give clearer answers. Vague prompts = vague replies
• Context: If you’ve had a long chat, it remembers the thread and responds accordingly
• Examples you give it: When you show it how you like things written (tone, style, structure), it mimics that
• The training data: Tools like Breezy do not search the web for answers. It draws on patterns it learned during training

If you’re using tools like Breezy, this is happening behind the scenes. It learns from the types of questions your customers ask, how you respond, and what leads to successful bookings, all so it can be more helpful over time.

A simple analogy

Imagine you run a bakery.

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A customer walks in and says, "I want something sweet, but not too sweet".

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You’ve served thousands of people like this. So you “decide” to suggest a raspberry scone. Why? Because over time, you’ve learned that customers who want something sweet but not overly sugary often enjoy the balance of tartness and sweetness in a raspberry scone.

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This isn't a random choice, it's based on your accumulated experience and understanding of customer preferences. LLMs operate similarly by drawing on vast amounts of data to make informed predictions.

The takeaway

Breezy doesn't know what it is saying, it also isn't making random choices. LLMs rely on extensive datasets to make informed predictions. They analyse patterns and trends from their training data to generate responses that are not only contextually appropriate but also tailored to the nuances of human communication. You can 'prompt' their responses to adapt them to your business context. Learn more about this in our post on Breezy workflows.