The Three Stages of a Startup

Definition

Every startup passes through three distinct stages. Stage 1, Problem/Solution Fit, asks "Do I have a problem worth solving?" — resolved through qualitative interviews before investing in a build. Stage 2, Product/Market Fit, asks "Have I built something people want?" — measured once a minimum viable product exists and customers are signing up, staying, and paying. Stage 3, Scale, asks "How do I accelerate growth?" The book adds a sharp before/after split: before product/market fit the startup should be architected to maximize learning and pivots; after it, the focus shifts to growth and optimization.

In the Book

Chapter 1 lays out the three stages directly beneath the "identify the riskiest parts of your plan" meta-principle, defining a "problem worth solving" as one that clears three tests: is it something customers want (must-have), will they pay for it or who will (viable), and can it be solved (feasible). The chapter then borrows Eric Ries's definition of a pivot — "a change in direction of a startup while staying grounded in learning" — to distinguish pivot experiments (finding a plan that works) from optimization experiments (accelerating a plan that already works), arguing this distinction "has a significant impact on both strategic and tactical execution."

Why It Matters

It gives a stage-appropriate definition of success, which prevents two common failures: optimizing a conversion funnel before anyone has confirmed the underlying problem is real, and continuing to pivot the core model after the evidence already shows product/market fit and calls for scaling instead. The same staging logic applies to any initiative where "did we build the right thing" and "are we now running it well" are different questions requiring different behavior.