Context Is Everything — Whether You're Marketing to Google or to a Bot

The big question with LLMs right now isn't whether llms.txt is worth doing. It's simpler and more uncomfortable: what do these tools actually know about your company? And how consistent is that across all of them?

For almost every brand, the honest answer is that nobody knows — and there's always something the model is missing, because no one remembered to explain it.

That's not a new problem. It's the oldest problem in SEO, with a bigger audience.

Teaching Google was always the job

Years ago, when I worked SEO for complicated products, I figured out something that shaped how I've worked ever since: if I cared about SEO, Google was one of the audiences I was marketing to. Not a channel. An audience. And if I didn't market to Google directly, I wasn't going to get the SEO I wanted.

So I treated it like one. The products I worked on were technical enough that Google couldn't make sense of them on its own — it couldn't see how the technology related to other technology, which is the part that actually matters. So I went into the schema and made sure it understood. That's not the standard marketer's instinct. It takes a technical digital marketer comfortable enough to get into the structured data and confirm the machine understood the relationships, not just the words.

That was the whole job. Give the machine context.

The audience didn't change. It multiplied.

Here's the only thing that's actually different now.

For years, that audience was effectively singular: Google. Today it's Google, Gemini, Claude, ChatGPT, and hundreds of other AI tools and systems answering questions about your company. The audience I always marketed to didn't go away. It grew — from one to many.

llms.txt is just one way to speak to that audience. It's a plain-language definition of who you are, who you are not, what you do, and how it all relates — written so a model can find the signal without crawling your whole site. Same instinct as schema. New, much larger room to address.

Treat the bot as an ICP

This is the shift in thinking worth sitting with: a bot is now one of your ideal customer profiles.

You already obsess over whether your messaging lands with the people you want to reach. The crawlers and models deserve the same treatment, because they're increasingly the thing standing between your brand and the human asking about it. If your messaging doesn't work for them, it doesn't reach the person behind them.

Things are changing fast, and I won't pretend the adoption picture is settled. But the direction doesn't depend on any single file or format. Whether it's traditional SEO or an LLM answering a question, the crawler has to understand what you do. That requirement isn't going anywhere. Context is the constant.

What this means if you run an agency

Make context something you manage on purpose, not something you hope a model infers. A few practical places to start:

• Audit what the tools already say about you and your clients. Ask the same questions across Google's AI overviews, ChatGPT, Gemini, and Claude. Note where the answers disagree — inconsistency is the signal that no source of truth exists.
• Write down what a model needs to get right: what the company does, who it serves, what it does not do, its category, and its competitors. The "does not do" and "how it relates to competitors" lines are the ones brands forget — and the ones that prevent a model from miscategorizing you.
• Put that definition somewhere machine-readable. Structured data, a clear about page, and yes, an llms.txt file. The container matters less than the discipline of declaring it.
• Recheck it on a schedule. This audience updates constantly. Your messaging to it should too.

The agencies that win the next few years will be the ones already treating machines as an audience worth marketing to — because they've been doing it since the only bot in the room was Google.

Context was everything then. With a hundred tools answering questions about your brand, it's everything now.

Try it yourself this week

You don't need a tool budget to start. Open the major models and ask them about your brand directly. Run the same prompts across each one — the disagreements are where the work is.

Where to look:

• ChatGPT, Claude, and Gemini — ask each the same questions and compare the answers
• Google AI Overviews — search your brand and category, see what gets summarized
• Perplexity — useful because it cites sources, so you can see where the model is pulling its understanding from

Prompts worth running:

• "What does [company] do, and who is it for?"
• "What does [company] not do?"
• "Who are [company]'s main competitors, and how is it different from them?"
• "What category or industry would you put [company] in?"
• "If a client asked you whether [company] is a good fit for [specific need], what would you say?"

Read the answers the way a prospect would. Where a model hedges, guesses, or gets your category wrong, that's a gap in the context you've given it — not a flaw in the model.