Founders are trained to believe that outcomes are the result of decisions. It’s a useful belief. It creates accountability, urgency, and focus. But it is also, to a significant extent, an illusion.

One of the central ideas in The Psychology of Money is that luck and risk are far more influential than we are comfortable admitting. This is not because people are irrational, but because outcomes, especially in complex systems, are shaped by factors that are only partially visible and rarely repeatable.

Startups are a textbook example of such a system and a crucial realization for rational and reasonable startup decision-making .

1. When Success Becomes A Story

In hindsight, successful startups tend to look inevitable because their paths are reconstructed into clean narratives. These stories are not necessarily false, but they are incomplete.

In his book, Morgan Housel illustrates this dynamic through the example of Bill Gates. Gates is often described as exceptionally intelligent, driven, and technically gifted. But Housel points out a less frequently emphasized factor: Gates attended one of the very few high schools in the late 1960s that had access to a computer terminal. This early exposure gave him thousands of hours of practice at a time when most of his peers had none.

The point is not to diminish Gates’ ability. It is to highlight how a critical advantage was partly a function of circumstance. Without that early access, the trajectory might have been very different. Yet most retellings focus almost exclusively on decisions and traits, not on the conditions that made those decisions possible.

A similar pattern appears in startup ecosystems. Once a company succeeds, every step along the way is interpreted as part of a coherent strategy. Decisions that could have gone either way are reframed as foresight. Uncertainty is rewritten as intent.

This creates a dangerous feedback loop: founders study these narratives and attempt to replicate them, assuming that the visible actions were the primary drivers of success.

2. The Survivorship Bias In Startup Advice

The problem is not just that success stories are incomplete. It’s that they systematically exclude failures.

For every company that successfully raises a large round, scales aggressively, and dominates its category, there are many others that follow a similar path and fail. Those stories are less visible, less analyzed, and rarely turned into frameworks.

Consider the case of WeWork. For years, it was held up as a model of bold vision and rapid scaling. The company expanded globally at an extraordinary pace, raised significant capital, and was celebrated for redefining office space.

Many of the strategic decisions that later drew criticism - aggressive expansion, high burn, charismatic leadership - were initially interpreted as strengths. They fit the prevailing narrative of what a high-growth startup should look like.

When conditions changed and the company’s underlying economics came under scrutiny, the same decisions were reinterpreted as obvious mistakes.

What changed was not the past, but the lens through which it was viewed.

This is the core issue with survivorship bias: it does not just hide failures; it distorts our understanding of success. Founders end up learning from a filtered dataset where luck is invisible, and risk is underrepresented.

3. Designing Decisions For An Uncertain World

If outcomes are partly driven by factors outside of a founder’s control, the implication is not that strategy is irrelevant. It is that strategy must be designed with uncertainty in mind.

This begins with a shift in perspective: from trying to be right to trying to be robust.

A robust strategy acknowledges that forecasts will be wrong, timelines will slip, and external conditions will change. Instead of optimizing for a single expected outcome, it builds in flexibility and margin for error. Financially, this might mean maintaining additional runway, pacing hiring more conservatively, or avoiding commitments that require perfect execution to succeed.

It also requires a more critical approach to learning from others. Rather than asking, “What did this successful company do?” a more useful question is, “What range of outcomes could have resulted from these decisions?” This reframing helps separate repeatable principles from context-dependent luck.

Finally, founders benefit from explicitly accounting for luck in their own thinking. This does not mean attributing success or failure entirely to chance, but recognizing that outcomes are influenced by variables that cannot be fully predicted or controlled. Such awareness tends to produce more cautious, adaptable decision-making - qualities that are often more valuable than bold but fragile strategies.