Over-diligencing for well-rounded perfection is a mistake. The best companies rarely excel in every area initially. Instead, investors should identify the one "spike"—the single dimension where the company is 5-10x better than anyone else—as this is the true indicator of outlier potential, rather than looking for a company that is A+ across the board.

True innovation requires building features customers don't yet know to ask for. Bloomberg's success came from providing functionality users hadn't imagined was possible with computers, rather than just reacting to their explicit requests.

Startups like NextVisit AI, a note-taker for psychiatry, win by focusing on a narrow vertical and achieving near-perfect accuracy. Unlike general-purpose AI where errors are tolerated, high-stakes fields demand flawless execution. This laser focus on one small, profound idea allows them to build an indispensable product before expanding.

The most lucrative exit for a startup is often not an IPO, but an M&A deal within an oligopolistic industry. When 3-4 major players exist, they can be forced into an irrational bidding war driven by the fear of a competitor acquiring the asset, leading to outcomes that are even better than going public.

In a crowded market, the most critical question for a founder is not "what's the idea?" but "why am I so lucky to have this insight?" You must identify your unique advantage—your "alpha"—that allows you to see something others don't. Without this, you're just another smart person trying things.

As AI models become commoditized, the ultimate defensibility comes from exclusive access to a unique dataset. A startup with a slightly inferior model but a comprehensive, proprietary dataset (e.g., all legal records) will beat a superior, general-purpose model for specialized tasks, creating a powerful long-term advantage.

Companies controlling proprietary data, even if publicly accessible but hard to collect (like FlightAware), can use AI to deliver a 'finished meal' instead of just the 'raw vegetables.' This moves them up the value chain from a data provider to a solutions provider, unlocking significant pricing power.

The path to $50k MRR for a mobile app isn't a feature-rich platform. It's an obsessive focus on doing one job perfectly for a specific group with a recurring need. Examples include 'value this vinyl,' 'create this logo,' or 'summarize this text.'

The Bloomberg terminal's breakthrough was not simply displaying data, but integrating the tools needed to analyze and act on it. It was built around the user's entire workflow—calculating, graphing, and messaging—which existing data screens completely ignored.