Instead of treating consulting and product as separate, CNX uses feedback from services projects to inform new features. A requested customization is often built directly into the core Valence product, benefiting all customers and creating a tight feedback loop.

Preparing a company for acquisition can lead founders to make short-term decisions that please the acquirer but undermine the brand's core agility, setting it up for failure post-sale. The focus shifts from longevity to a transaction.

For established software companies with sluggish growth, the path forward is clear: find a way to become relevant in the age of AI. While they may not become the next Harvey, attaching to AI spend can boost growth from 15% to 25%, the difference between a viable public company and a sale to a private equity firm.

The founders were building a new UI for their own internal software. It was their external marketing firm, not them, who recognized the tool could be packaged and sold as a standalone modernization product, which became their flagship offering.

In 2006, while evaluating UI technologies, the founder discovered the ext.js framework. Within five minutes, he had a "eureka moment," becoming convinced it was the future of all web applications. He made a high-conviction bet to go all-in on the nascent technology, which became the foundation of their flagship product.

Enterprise leaders aren't motivated by solving small, specific problems. Founders succeed by "vision casting"—selling a future state or opportunity that gives the buyer a competitive edge ("alpha"). This excites them enough to champion a deal internally.

The origin of CNX wasn't a meticulously planned venture. The two co-founders were colleagues who, frustrated with their boss, impulsively quit their jobs together. The company was born out of that moment with no plan and no money, forcing them to be resourceful from day one.

For incumbent software companies, an existing customer base is a double-edged sword. While it provides a distribution channel for new AI products, it also acts as "cement shoes." The technical debt and feature obligations to thousands of pre-AI customers can consume all engineering resources, preventing them from competing effectively with nimble, AI-native startups.

Instead of dismissing harsh criticism, extract the underlying truth. A brutal investor rejection focused Gamma on intertwining product and growth from the very beginning, acknowledging the difficulty of competing against incumbents. This became a foundational part of their strategy.