TL;DR
A large language model, or LLM, is a sophisticated artificial intelligence (AI) system. What it does is this:
- Takes a question or request typed by you. We would call this a “prompt.” This prompt could be a sentence or paragraph, an entire article, a short story, or even a book.
- The LLM will then look at the prompt, as well as the context it has from a massive database, and then predict what it should say to fulfill your request. This prediction is what it spits back to you.
An LLM-based search engine (like ChatGPT or Google’s AI Mode) can quote or even recommend your business when people ask questions about your service or industry.
To get this to happen, you must get your website, social media, and Google profile to speak AI’s language. There are a number of ways to do this, including putting markup on the backend of your website, establishing authority and expertise in your industry, and putting out quality content people find valuable.
How Do LLMs Work?
When you type into an LLM, it breaks your text into tiny chunks known as “tokens,” turns them into numbers, and then groups related ideas—like “dog” with “puppy” or “coffee” with “espresso.” It doesn’t understand words as we do, but it will analyze the patterns and relationships to predict which words best fit together, giving the final answer you see.
What Happens Under the Hood
- Every LLM starts with an immense amount of training data, including web pages, books, research papers, technical documentation, open-source programming languages, and customer feedback.
- Then comes the neural network, a vast, expansive web of connections that helps the AI recognize patterns in language. Each network layer is an improved version of the last one, slowly learning how people speak, write, and communicate.
- Training these systems takes significant quantities of water, electricity, and computing power.
- Computers can’t do it alone. You still need human resources. Real people clean up the data, test the results, and ensure the model behaves like it should.
What Can LLMs Do?
Reformatting Text
One of the biggest functions of a large language model is to shape and reshape text. LLMs generate, translate, summarize, answer, and analyze. Give them a contract, they’ll condense it; a messy survey, they’ll find themes; a half-written email, they’ll finish it.
LLMs are not perfect, and that’s why they often generate what’s called “hallucinations.” These are responses that seem authentic but are completely made up.
However, even given this, there is no doubt that LLMs are reshaping how language works.
Daily Business Uses
Many companies use LLMs to streamline operations. Businesses will use it to summarize data, analyze reports, and turn feedback into strategy. LLMs speed up coding, power modern chatbots, and act as AI agents when paired with CRMs or ERPs. They’re not fully autonomous yet, so you always have to double-check their output.
AI’s Limits
LLMs hallucinate, which is a huge limitation of AI in its current form. They’re powerful tools, but tools don’t have ethics; the people using them should. To prevent ethical disasters with AI, you must limit sensitive data, keep people involved, and verify outputs. The real risk isn’t the tech. It’s assuming the machine knows what it’s doing (it doesn’t).
How to Show Up in LLMs
LLMs and AI search models don’t rank you, like Google used to do. They quote you, so you need to be worth quoting. Experts are calling this new way of being quoted or cited by AI “Generative Engine Optimization” or GEO.
Having your business show up in LLMs isn’t about tricking the algorithm. It is about giving it content that the AI can justify, trust, and use.
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Principle #1 — Bring the Evidence
An LLM doesn’t recommend willy nilly. It has to somehow justify its recommendation. It builds a shortlist and gives reasons.
Your content must make clear claims supported by visible evidence, such as technical documentation, data, comparisons, and specifications, not just keywords or style. AI scans your site for substance, which means scannable, evidence-rich, and self-contained pages.
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Principle #2 — It’s Good If People Mention You
AI doesn’t know the truth; it can only gauge consistency. When credible sources repeat clear, structured content, LLMs consider it reliable. Generative Engine Optimization now favors credibility over backlinks. What this means in practice is that mentions matter as much as links. Podcasts, reviews, PR, and social chatter all help, but only if your content gives LLMs something solid to quote.
AI is biased toward established brands, but you can bridge that gap with careful planning and clever content creation. We’ve done it for ourselves and our clients.
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Principle #3 — SEO Still Matters
Think of it like this: SEO gets you discovered, and GEO decides if you are credible enough to be featured.
You can’t be cited by an LLM or AI search summary if it can’t find you. AI still relies on traditional SEO ranking signals (crawlability, relevance, backlinks, and internal linking) to discover content. Showing up and being featured locally is still essential, as many AI models reference local directories when recommending local businesses. So SEO isn’t dead but evolving, and how we do it is changing.
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Principle #4 — Structure Your Website Well
AI doesn’t browse your site like a person would. It parses, extracts, and maps it. If your structure’s a maze, it leaves. Schema, FAQs, transcripts, and policies now shape the “AI experience.” A clear, well-structured site trains future AIs, and when competitors catch on, you’ll already be their reference point.
Will AI Replace People’s Jobs?
We can’t see the future, but we predict that LLMs will replace tasks, and the people who learn to work with them will replace those who don’t.
The Bottom Line
If your business runs on communication, LLMs shape how your customers see you. Don’t write for clicks. Write effective, compelling content for credibility, with proof.
In this era where machines might quote you before people do, clarity becomes your greatest advantage.Contact Uptick if you’re ready to develop a strategy that helps AI discover and recommend you so your customers know who you are and trust what you can do for them.
