For professionals in declining fields like Hollywood production, reinvention requires abstracting core skills. A line producer's expertise in organization, vendor management, and execution is directly transferable to a growth sector like high-end event planning, which capitalizes on the consumer shift from things to experiences.

In fast-moving industries like AI, achieving product-market fit is not a final destination. It's a temporary state that only applies to the current 'chapter' of the market. Founders must accept that their platform will need to evolve significantly and be rebuilt for the next chapter to maintain relevance and leadership.

Adding new offerings is a smart growth strategy, but only if your primary business is stable and systemized. Launching a new service to escape existing chaos will only amplify it. Instead, treat the new offering as a separate, dedicated division to maintain focus and quality.

When a startup finally uncovers true customer demand, their existing product, built on assumptions, is often the wrong shape. The most common pattern is for these startups to burn down their initial codebase and rebuild from scratch to perfectly fit the newly discovered demand.

Pivoting isn't just for failing startups; it's a requirement for massive success. Ambitious companies often face 're-founding moments' when their initial product, even if successful, proves insufficient for market-defining scale. This may require risky moves, like competing against your own customers.

Before a major business pivot, first identify what can be let go or scaled back. This creates the necessary space and resources for the new direction, preventing overwhelm and ensuring the pivot is an extension of identity, not just another added task on your plate.

Rather than making an abrupt turn, Sure managed its pivot from a B2C app to a B2B platform gradually. They kept the original mobile app running while they built and validated the new B2B distribution model, only sunsetting the app once the new strategy proved viable and began to ramp up.

In the age of AI, 10-15 year old SaaS companies face an existential crisis. To stay relevant, they must be willing to make radical changes to culture and product, even if it threatens existing revenue. The alternative is becoming a legacy player as nimbler startups capture the market.

When growth flattens, data companies must expand their value proposition. This involves three key strategies: finding new end markets, solving the next step in the customer's workflow (e.g., location selection), and acquiring tangential datasets to create a more complete solution.