Figma's expansion into multiple products (FigJam, Slides) wasn't based on abstract strategy but on observing users pushing the main design tool to its limits for unintended use cases. Identifying these 'hacks' revealed validated market needs for dedicated products.

Instead of inventing new features, Prepared identified its most lucrative expansion opportunity by seeing users' painful workarounds. They noticed 911 dispatchers manually copy-pasting foreign language texts into Google Translate—a clear signal of a high-value problem they could solve directly.

The biggest opportunities often address needs that don't appear on a customer's "calendar" because no good solution exists. Products like Lovable for web design unlock latent demand by finally providing an accessible way to accomplish a goal that was previously too difficult.

Intentionally create open-ended, flexible products. Observe how power users "abuse" them for unintended purposes. This "latent demand" reveals valuable, pre-validated opportunities for new features or products, as seen with Facebook's Marketplace and Dating features.

Users often develop multi-product workarounds for issues they don't even recognize as solvable problems. Identifying these subconscious behaviors reveals significant innovation opportunities that users themselves cannot articulate.

Identify how users are already "hacking" your product for unintended purposes (e.g., using Facebook Groups for commerce), then build dedicated features to serve that existing intent. You can't make people do new things, but you can help them do what they already want to do more easily.

When customers actively work around your product's intended functionality to solve a different problem, it's a powerful indicator of a more significant market need. Following this user behavior can lead to a successful pivot.

A new product development principle for AI is to observe the model's "latent demand"—what it attempts to do on its own. Instead of just reacting to user hacks, Anthropic builds tools to facilitate the model's innate tendencies, inverting the traditional user-centric approach.

Innovation isn't random. Pampers' wetness indicator solves a clear problem: parents need to know if a diaper is wet, but the existing option (taking it off) is inefficient. By identifying this unavoidable task and its bad workaround, the exact shape for a winning new feature becomes clear.