Does Your AI Strategy Have a Version Problem?

Last fall I was in a room with two founders and their advisor at an AI-native company. Early in the conversation, I asked each of them to take a few minutes and write down the company's strategy in two sentences. Separately, no comparing notes.

One founder listed capabilities. The platform could do this, the platform handled that, and here were the integrations. The other wrote that they wanted to grow to $50M and get funded. The advisor focused on the reliability question: what AI can deliver reliably today, and what it cannot.

Three people who had been building together for months. None of them wrote the same thing.

None of them were wrong. That's the part worth sitting with. Each answer made sense from that person's perspective. The technical co-founder sees the platform. The business-oriented founder sees the destination. The advisor sees the constraint that matters most to them. All reasonable. None of them were the same answer, and none were specific enough to tell the team what to build next.

When strategy only lives in conversation, that's what you get. Not confusion, not disagreement, just three genuine interpretations of the same direction, each shaped by a different vantage point. It feels good enough to manage when you're small. It can get expensive when you're trying to make decisions fast.

What changed about eighteen months ago

Before AI coding tools, an idea required real engineering time to test. That friction did something useful. Not every request survived the cost of exploration, and the list of competing AI priorities stayed shorter by default.

Now anyone on the team can have a working prototype by Monday morning. The idea exists, has a person behind it with energy and a customer story, and now a demo. But someone has to decide what to do with it.

When strategy lives in three different versions across the leadership team, there's no principled basis for that decision. You can slow the request down. You can ask questions. But when the conversation gets to "why not this one," the honest answer is that there's no written logic to point to. The conversation becomes a negotiation about what the strategy actually means, which is really a proxy argument for whose version is right.

That argument happens every week, and the number of inputs that trigger it keeps growing.

The aspiration trap

Most teams that recognize this problem try to write the strategy down: a slide, a paragraph in a product brief. They share it, feel better, and three months later, the same arguments are back.

The problem is almost always specificity.

"We will use AI to improve the customer experience" is a direction. It's true. Everyone agrees with it. Nobody can use it to push back on a feature request because it doesn't exclude anything. It's written at the level of aspiration rather than at the level of decision.

When I challenged the technical founder on his list of capabilities, I told him directly: "That's a description of a cool platform, not a strategy.” The platform capabilities were driving the positioning, but capabilities don't tell you which problem to solve first or which customers to build for.

That exchange is what makes this expensive. The strategy felt real to him. It existed in his head as a coherent picture. But it had no mechanism for filtering the next request.

What written strategy actually has to do

A written strategy that serves as a decision filter has to answer a specific question: where does AI make this product harder to replace?

That means getting concrete about which customer workflows people are genuinely dependent on, where switching costs are high enough that customers stay even when a comparable alternative shows up, and what the product does that customers have built their own processes around.

When the strategy answers those questions in writing, anyone on your team can evaluate a request against it and get a consistent answer. Either the request strengthens the position, or it doesn't. That conversation can happen without the CEO in the room, because the decision logic is no longer dependent on the CEO to translate it.

Getting to those answers requires more honest work than most teams have done. If you can't articulate where your product is genuinely hard to replace, writing your strategy down will expose that. It can be very uncomfortable. It's also necessary.

Why it keeps getting deferred

Writing strategy down forces decisions that verbal strategy lets you avoid. You have to name what you are not building, say which market segment actually leads rather than just which ones look interesting, and commit to a position someone can later point to and argue with.

Verbal strategy has a lot of inertia. It is just easier than writing it down. Writing it down requires more work up front, and it doesn't feel necessary in the moment. The cost of not doing it is not felt until it is.

The cost shows up quietly. Roadmap churn. Priorities that shift whenever a vocal stakeholder gets in the room. A CEO who is still the translation layer between the strategy and every real decision. And eventually, a board conversation where "we are doing AI" is the whole answer, because there is no written logic underneath it.

Writing it down does not eliminate the hard work. It just means the hard work happens once, in a room, rather than being re-litigated every time a new request shows up.