LLM (Large language model)
An LLM is software trained on huge amounts of text so it can predict what word comes next. LLM stands for large language model. That makes it good at drafting, summarizing, and talking through a problem in language. On its own it knows nothing about your ad accounts, your prices, or your customers.
Theodor Lindfors, Founding Marketer ·
How a large language model works
Let's take a software company as an example. They sell a subscription tool to plumbing companies. Leads come from Google and LinkedIn, and a salesperson closes the deal. The marketing team writes ads, replies to questions, and summarizes call notes. A large language model is the engine behind the chat tools they already tried. It is trained to predict the next token in a sequence, over an enormous volume of text. The pattern-matching that emerges from that training is what feels like understanding.
A large language model is genuinely useful and genuinely different from a database lookup. The model produces language, not retrieved facts. That is also why it can be wrong with total confidence. Let's take a software company as an example. They sell a subscription tool to plumbing companies. Ask a model the close rate and it may invent 22%. There is no internal check against the company's customer records unless you give it one.
What LLMs are good at in marketing
Large language models are good at drafting variations of ad copy and landing page text. Summarizing long documents, call transcripts, and research. Turning a messy question into a structured query. Explaining what a chart is showing. Writing the first version of anything, which is usually the slow part. Let's take a software company as an example. They sell a subscription tool to plumbing companies. A marketer can paste a plumber's objection and get five reply drafts in a minute.
Large language models are also good at reading across formats. A model can hold a brief, a performance export, and a brand guideline at once, which is awkward for a human and impossible for a dashboard. What a model cannot do alone is know that a software company's $99 plan closed 40 deals last month. That number lives in the CRM (customer relationship management software).
Why a model alone is not a marketing tool
A large language model needs your data. It needs to know your definitions, because a qualified lead at a software company selling to plumbers is a booked demo with a plumbing company, not a newsletter signup. And it needs permissions, because reading a report and changing a Google budget are different levels of trust.
That is the gap MCP (Model Context Protocol: a way for ChatGPT, Claude, Cursor, or n8n to read your marketing data) and agentic AI address: one gives a model a standard way to reach tools and data, the other lets it plan and act over multiple steps rather than answering once. An AI co-worker is the version of that a marketing team can actually work with day to day. Lemonado connects to 3,000+ tools, keeps the company's context, and can execute in connected accounts when you ask. MCP connections stay read-only.
Common LLM mistakes in marketing teams
- Pasting a software company's performance export into a chat window and treating the answer as analysis.
- Asking a large language model for benchmarks. The model will produce plausible numbers with no source.
- Expecting a large language model to remember last week's context when nothing is storing that context.
- Giving a large language model write access to Google Ads before anyone has reviewed what it does with read access.
Lemonado
How Lemonado uses language models
The model is the engine, not the product. Lemonado gives it your connected platforms (3,000+ tools), your definitions, and your client history, so the answer is about your Google leads rather than about marketing in general.
Ask a question in plain language and it queries live data across the stack instead of guessing from training data. MCP (Model Context Protocol) connections to outside AI tools stay read-only. Lemonado itself can execute and write in the accounts you connect.