Does this create depth or breadth?

Depth means you are building a competitive moat, something that compounds over time, gets harder to replicate, and changes the nature of your category. Breadth means you are expanding the territory where you play. Both can be 10x moves, but they require completely different execution muscles.

Are you building open or closed?

This is not a technical question. It is a strategic one. Open bets on ecosystem gravity and distribution scale. Closed bets on proprietary data, proprietary models, and defensible differentiation. A wrong read here is expensive not because the technology fails, but because the strategy was never coherent to begin with.

AI fluency is a tactic. Judgment is the strategy.

Rachel Windzberg
Jun 4
2 min read

Most leaders are sprinting to close the AI knowledge gap. That is the wrong race.

Here is something worth sitting with: every one of your competitors is sending their teams to the same AI trainings, reading the same AI newsletters, and deploying Copilot on the same schedule. If the race is "who learns AI fastest," you are not going to win by much. And even if you do, it is a race to a commodity.

The leaders who will separate themselves in the next three years are not the most AI-fluent. They are the ones who use AI to ask better strategic questions and who build organizations that can act on the answers.

Finding the right questions to ask by applying 10X thinking

When most product leaders approach AI strategy, they ask: how do we make our existing workflows 10 to 20 percent faster? That is 2x thinking. Add AI to your spec process. Use it to summarize research. Generate test cases automatically. These are fine. They are also exactly what your competitors are doing.

10x thinking starts with a different question: what does this unlock that was previously impossible? Not faster briefs, but a feedback loop between content production, ad performance, and brief construction that did not exist before. Not faster search, but always-on discovery that makes a product stickier between purchase cycles. The difference is not the technology. It is the frame you bring to it.

The two strategic dimensions that matter

When you are evaluating where to invest in AI, two questions cut through the noise:

Does this create depth or breadth? Depth means you are building a competitive moat, something that compounds over time, gets harder to replicate, and changes the nature of your category. Breadth means you are expanding the territory where you play. Both can be 10x moves, but they require completely different execution muscles.
Are you building open or closed? This is not a technical question. It is a strategic one. Open bets on ecosystem gravity and distribution scale. Closed bets on proprietary data, proprietary models, and defensible differentiation. A wrong read here is expensive not because the technology fails, but because the strategy was never coherent to begin with.

Where most leaders get stuck

If you confuse the tactic for the strategy, you are chasing your own tail. "We are an AI-first company" is not a strategy. It is an aspiration. "We are using AI to be the only platform that can close the loop between creator output and brand ROI in real time" is a strategy. The difference is specificity about what you are building and why it is defensible.

AI fluency is table stakes. Strategic judgment about where AI creates durable advantage for your specific business is the work. And it is work most leaders have not yet done in a disciplined way.

What are you building that will look like a moat in 2027? If the answer is not clear, that is the question worth spending time on this quarter.