Product-market fit is no longer a stable milestone but a moving target that must be re-validated quarterly. Rapid advances in underlying AI models and swift changes in user expectations mean companies are on a constant treadmill to reinvent their value proposition or risk becoming obsolete.

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.

The 'never give up' mantra is misleading. Successful founders readily abandon failed products and even entire startups. Their unwavering persistence is not tied to a specific idea, but to the meta-goal of finding product-market fit itself, no matter how many attempts it takes.

The idea that startups find product-market fit and then simply scale is a myth. Great companies like Microsoft and Google continuously evolve and reinvent themselves. Lasting success requires ongoing adaptation, not resting on an initial achievement.

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.

Unlike traditional software where PMF is a stable milestone, in the rapidly evolving AI space, it's a "treadmill." Customer expectations and technological capabilities shift weekly, forcing even nine-figure revenue companies to constantly re-validate and recapture their market fit to survive.

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.

Sure's journey shows that PMF is not binary. The company achieved initial PMF with its prototype, then again with its first product, and again after its pivot. However, launching auto insurance with a major EV brand created a "literal rocket ship" moment that represented a completely different order of magnitude of PMF.

PMF isn't a fixed state achieved once. It's a continuous process that must be re-evaluated at every stage of growth—from $1M to $1B. A company might have PMF for one scale but not for the next, requiring a constant evolution of strategy and product.