A company found its top engineers were "difficult." Before changing hiring criteria to favor this trait, they checked their worst-performing engineers and found they were also difficult. The trait was common to all engineers, not a signal of success, revealing a classic survivorship bias.

In domains with extreme outcomes (music, startups), success is heavily influenced by luck, making it difficult to replicate. A more effective strategy is to study the common failure modes of the vast majority of talented people who tried. This provides a clearer roadmap of what to avoid than trying to copy a lucky winner.

Despite internal failures and employees questioning why the outdated, aspirational model wasn't removed from public view, Spotify continued to leverage the hype. The vision of autonomous 'squads' was a powerful magnet for attracting talent, even if it didn't reflect the operational reality.

When evaluating others' success, ask if their strategy would work for most people who adopt it, or if it relied heavily on luck. If a strategy isn't reproducible and leaves many casualties behind, it's not a model to be learned from, regardless of the impressive outlier outcome.

Disagreeing with Peter Thiel, Josh Wolf argues that studying people who made willful mistakes is more valuable than studying success stories. Analyzing failures provides a clear catalog of what to avoid, offering a more practical and robust learning framework based on inversion.

Founders who succeed by randomly trying ideas rather than using a systematic process don't learn repeatable skills. This lucky break can be detrimental, as it validates a flawed strategy and prevents the founder from learning the principles needed for consistent, future success.

While no single path guarantees startup success, the phrase "there's no one right answer" is dangerous. It implies all approaches are equally valid, leading founders to choose easy methods over proven, difficult ones. In reality, only a handful of paths are viable, while the vast majority ensure failure.

Startup valuation calculators are systematically biased towards optimism. Their datasets are built on companies that successfully secured funding, excluding the vast majority that did not. This means the resulting valuations reflect only the "winners," creating an inflated perception of worth.

The famed organizational design was merely an aspirational "wishlist" that Spotify never fully adopted. Companies copying it are chasing a fantasy primarily used for recruiting, not a proven operational model that the company itself ever ran on.