Many founders become too attached to what they've built. The ability to unemotionally kill products that aren't working—even core parts of the business—is a superpower. This prevents wasting resources and allows for the rapid pivots necessary to find true product-market fit.
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The belief that your current product is "a giant piece of shit" is a powerful motivator. This mindset ensures you are constantly seeking limitless opportunities for improvement. If you can't see flaws and feel a degree of humiliation about what you offer the public, you shouldn't be designing the product.
The goal of early validation is not to confirm your genius, but to risk being proven wrong before committing resources. Negative feedback is a valuable outcome that prevents building the wrong product. It often reveals that the real opportunity is "a degree to the left" of the original idea.
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.
Since startups lack infinite time and money, an investor's key diligence question is whether the team can learn and iterate fast enough to find a valuable solution before resources run out. This 'learning velocity' is more important than initial traction or a perfect starting plan.
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.
Deciding which products or services to cut can be an emotional process for founders. Amy Porterfield advises removing the "drama" by relying on data. By tracking metrics for each offer, she could make objective decisions to retire those that didn't make business sense, simplifying her path to growth.
Founders embrace the MVP for their initial product but often abandon this lean approach for subsequent features, treating each new development as a major project requiring perfection. Maintaining high velocity requires applying an iterative, MVP-level approach to every single feature and launch, not just the first one.
