It's a mistake to make 'using AI' the strategy itself. Fundamental business drivers like customer lifetime value (LTV), retention, and engagement remain unchanged. AI is a powerful new method for influencing these timeless metrics, but it is not a replacement for a sound business strategy focused on customer value.

AI tools have the "half-life of a flea." Instead of chasing the latest platform, product managers should focus on mastering fundamental techniques—like context engineering or problem-solving—which are transferable and will outlast any single tool.

Many AI initiatives fail because they focus on implementing technology rather than understanding and enhancing the specific customer interactions they aim to improve. A 'customer moment-first' approach grounds the strategy in real-world business outcomes and value.

Predicting the future is hard. Instead, focus on foundational truths that will remain constant. Bezos knew customers would always want lower prices and faster delivery. Building a business around these unchanging principles is a more robust strategy than chasing fleeting trends.

Successful AI strategy development begins by asking executives about their primary business challenges, such as R&D costs or time-to-market. Only after identifying these core problems should AI solutions be mapped to them. This ensures AI initiatives are directly tied to tangible value creation.

Citing Jeff Bezos, a more effective business strategy is to identify and serve fundamental, unchanging human needs—like the desire to be informed and entertained. This provides a stable foundation, whereas constantly reacting to the latest technological change is a less reliable approach.

With categories constantly shifting, focusing on present-day feature fights is a losing game. Halliday advises founders to use competitive pressure as fuel for excellence, but to aim their product strategy at what the buyer's life will look like in 18-24 months to skate where the puck is going.

Implementing AI tools in a company that lacks a clear product strategy and deep customer knowledge doesn't speed up successful development; it only accelerates aimless activity. True acceleration comes from applying AI to a well-defined direction informed by user understanding.

Leveraging AI requires a dual focus. Leaders must apply AI to solve genuine customer problems, not just for the sake of technology. Simultaneously, they must upskill their teams and re-engineer internal development processes to reduce handoffs and accelerate the entire product cycle.