Marketers, beware: The AI model you rely on today might not be the one you can rely on tomorrow.
Powerful AI models have been pulled offline over security concerns. Flat-fee access has quietly shifted to pay-as-you-go. Governments are floating ownership stakes in the labs. Prices swing, capabilities grow every few weeks, and the “best” model changes as quickly as you master the last.
For a marketing team trying to build durable workflows on top of these tools, this volatility is a real challenge. If your entire operation is wired into one provider’s chat window, one interface, one subscription, you’re vulnerable.
There’s a better way to think about it, and it starts with a mindset shift: the model isn’t your advantage. Your context is.
Focus on Context, Not Tools
Frontier models are becoming interchangeable: ChatGPT, Claude, Gemini. Each new release trades the lead, matches the others on the benchmarks that matter to most business users, and gets cheaper over time. For everyday marketing work — drafting, research, analysis, repurposing, planning — you can increasingly swap one capable model for another and get comparable results.
So if the model is commoditized, where is your true advantage?
It lives in what you bring to the model: Your brand voice. Your positioning. Your customer research. Your campaign history, your naming conventions, the way your team actually gets things done. Palantir’s leadership has a word for this in the enterprise context — they call it your “alpha,” the proprietary advantage that’s uniquely yours.
Feed a generic model your specific context and it stops giving you generic output. That combination — a capable model plus your context — is the competitive advantage.
So stop investing all of your energy in mastering a tool, and start investing in making your work legible to any capable model, and portable so you can move it wherever you need.
“Portable context” in practice
On a recent episode of The Artificial Intelligence Show, Mike Kaput walked through a personal version of this idea. Spooked by models getting yanked offline and aware of rising usage costs, he set out to build a personal “context layer” — a collection of accounts, documents, and instructions that any reasonably capable model could use and provide consistent value. The upside? If one tool disappeared, he wasn’t starting over.
You don’t need to be a developer to create this. Here’s how the same thinking translates for a marketing team.
1. A “read me first” file for AI. The foundation is a single document that orients any AI tool to how you work: who you are, what you’re trying to accomplish, where the important information lives, and how you want things done. Think of it as onboarding docs for an AI collaborator. Any new model or any new team member should be able to read it and immediately understand the lay of the land instead of you re-explaining your world from scratch each time.
2. A folder of playbooks. The next layer is a set of step-by-step guides for the tasks you do over and over. For example, how you write a launch email, how you brief a blog post, how you turn a webinar into social content, how you assess a campaign for quality before it launches. Written in plain language and saved as simple text files, these become reusable “playbooks” you can hand to any model: Here’s exactly how we do this, now go. The payoff is consistency. Your processes stop living only in people’s heads and start living somewhere AI can execute.
3. A data layer of connections. The final layer is giving AI safe, structured access to the information it needs: Your document storage, your knowledge base, your approved brand assets. Mike’s version connected AI to his personal files and, notably, gave it read-only access to sensitive accounts so it could pull real-time information without being able to change anything. That read-only instinct is a smart governance principle for marketers too: give AI the access it needs to be useful, not dangerous.
Put those three layers together and you’ve built something that isn’t tied to a single AI model. It’s yours. When a better or cheaper model shows up next month, you give it your context and keep moving.
How to Get Started
You don’t need to build the whole system at once. Start small:
- Write one “read me” doc for how your team or function works, and try feeding it to your AI tool before your next few tasks. Notice how much less re-explaining you do.
- Document one repeatable workflow as a plain-language playbook — pick the task you do most — and use it as a reusable prompt.
- Audit your access. What information would make your AI dramatically more useful if it could see it? What’s the minimum, safest way to give it that access?
- Run a portability test. Take a task you normally do in one model and run it in a different one using the same context. If the output holds up, you’ve proven the point: your value travels with you.
To listen to this full episode of The Artificial Intelligence Show, visit: https://podcast.smarterx.ai/shownotes/224
For more on building AI-ready marketing teams, explore AI Academy at academy.smarterx.ai.
