Founders often mistakenly market "AI" as the core offering. Customers don't buy AI; they buy solutions to their long-standing problems (e.g., more leads, better service). Frame your product around the problem it solves, using AI as the powerful new tool in your solution space that makes it possible.

Enterprise buyers are drawn to the vision of full automation ("the sizzle"), but their immediate need is improving existing human workflows ("the steak"). A startup must offer both. The visionary product gets them in the door, while the practical agent-assist tool delivers immediate value and gathers necessary data for future automation.

Visionary founders often try to sell their entire, world-changing vision from day one, which confuses buyers. To gain traction, this grand vision must be broken down into a specific, digestible solution that solves an immediate, painful problem. Repeatable sales come from a narrow focus, not a broad promise.

Large enterprises don't buy point solutions; they invest in a long-term platform vision. To succeed, build an extensible platform from day one, but lead with a specific, high-value use case as the entry point. This foundational architecture cannot be retrofitted later.

A truly "AI-native" product isn't one with AI features tacked on. Its core user experience originates from an AI interaction, like a natural language prompt that generates a structured output. The product is fundamentally built around the capabilities of the underlying models, making AI the primary value driver.

A successful brand 'wedge' isn't a mission statement like 'better ingredients.' It’s a specific, tangible reason—a unique ingredient, a novel form factor—that makes a customer choose you over 47 other options. If you can't state it in a single sentence, you don't have one.

Robotics company Matic intentionally used its vacuum cleaner as a "data wedge." The goal was to get a device inside the home, earn customer trust, and build a brand. This allows them to collect the privacy-sensitive, real-world data necessary for training more advanced future robots, similar to Tesla's strategy with its cars.

Moonshot AI's CEO effectively sells his product by "vision casting"—framing it not as an e-commerce tool but as a partner that enables businesses to thrive. This focus on the ultimate outcome, rather than product features, resonates deeply with customers and powerfully articulates the value of a complex AI solution.

To compete with giants like Amazon, Spangle didn't build a full platform. They found a niche "connector" problem: the loss of context between an Instagram ad and the e-commerce site. This focused wedge delivered immediate value that incumbents had overlooked, creating a crucial entry point.