GPT-5. Claude 4. Gemini 2.0 Ultra. o3. Whatever dropped last week.
You have access to it. So does your competitor. So does the startup that launched yesterday. So does the enterprise that's been around for 50 years.
The model is a commodity.
The Arms Race Nobody Wins
Every few months there's a new model. Better benchmarks. More parameters. Faster inference. The tech press goes wild. LinkedIn fills up with "game changer" posts.
And then... everyone has it. The advantage lasts about six weeks.
If your AI strategy is "use the best model," your strategy expires every quarter. You're not building an advantage. You're renting one.
Meanwhile, the actual hard problem hasn't changed.
The Question AI Still Can't Answer
Ask GPT-5 to write code. It's incredible.
Ask it to explain quantum physics. Mind-blowing.
Ask it: "Why is our billing slow this month?"
Silence. Or worse — confident nonsense.
It doesn't know your billing system. It doesn't know that you migrated databases in March. It doesn't know that "slow" for your business means something different than "slow" for a SaaS startup. It doesn't know that the last time this happened, it was a timezone bug in the batch processor.
The model is brilliant. But it's generally brilliant. And your problems are specifically yours.
The 90% Nobody's Selling
Here's the breakdown:
- The model — the LLM itself — is maybe 10% of what makes AI useful for your business.
- The context — your data, your processes, your history, your relationships — is the other 90%.
Everyone's fighting over the 10%. The model providers are in an arms race. Billions of dollars. Massive GPU clusters. Impressive benchmarks.
Almost nobody is working on the 90%.
Because the 90% is hard. It's not a product you can download. It's not an API you can call. It's the messy, specific, accumulated knowledge of how YOUR business actually works.
Your customers. Your workflows. Your exceptions to the rules. Your "we do it this way because of something that happened in 2019." Your tribal knowledge that lives in the heads of people who've been there for a decade.
That's the context. And without it, AI is just a very sophisticated autocomplete.
What "AI Strategy" Actually Means
A ChatGPT subscription isn't an AI strategy. It's a tool purchase.
An AI strategy answers: How do we make AI understand our business well enough to be useful?
That means:
- Mapping your entities — customers, products, processes, systems, and how they connect
- Capturing your history — what happened, why, and what you learned
- Encoding your rules — the policies, exceptions, and "how we do things here"
- Building feedback loops — so the system gets smarter as you use it
This is the knowledge layer. The context. The 90%.
Once you have it, the model almost doesn't matter. GPT-5, Claude 4, whatever comes next — they're all good enough. The differentiator is what you feed them.
Most companies ask: "Which AI model should we use?" The better question: "What context do we need to build so that ANY model becomes useful?"
The Moat Is the Map
Your competitors can license GPT-5. They can't license your business knowledge.
They can hire AI engineers. They can't hire the 15 years of decisions, mistakes, and learnings that shaped how your company actually operates.
That institutional knowledge — mapped, structured, and queryable — is the moat. Not the model. The model is a utility. The map is the asset.
The companies that figure this out will use AI to answer questions their competitors can't even ask. Not because they have better AI. Because they've built the context that makes AI actually useful.
So What Now?
Stop chasing models. Start building context.
The next version of GPT will be impressive. It won't know your business any better than the last one did.
The question isn't which model to use. It's whether you've built something worth feeding it.
