Validation Labs exists to test a simple idea: “Most startups fail not because they are poorly built, but because they are poorly tested.”
We approach startup creation as an experimental discipline. Problems, solutions, markets, distribution, and defensibility are treated as testable variables—not matters of belief or founder conviction.
Our working hypothesis is that disciplined validation can materially reduce the time and capital required to launch a business, while increasing the return on founder effort and investor capital.
What We Believe
Evidence over Mythology
Startup success is primarily driven by disciplined validation, observable customer behavior, and defensible advantages that compound over time. We do not believe success is primarily driven by passion, vision, or founder mythology.
Predicting the Bad to Find the Good
While a small number of companies will always succeed by chance, we are not focused on low-probability outcomes that rely on timing or luck. Our goal is to develop methods that allow founders, operators, and investors to predictably identify bad ideas early so that focus and energy can be spent on good ideas sooner.
In an environment where software is cheap and fast to build, execution alone is not a defense. Sustainable businesses require validated demand and a credible path to defensibility.
How We Work
We treat company creation as a sequence of structured tests. Each question must be answered with evidence before additional resources are committed.
Problem Reality
Is the problem real, observable, and persistent?
Willingness to Pay
Are people already paying to solve it? Does behavior indicate willingness to pay?
Advantage & Compounding
What advantage exists today? What advantages could compound tomorrow?
Distribution Fit
Can distribution work within real constraints?
Progress is earned. Failure is expected. Stopping is a valid outcome.
How We’re Different
Validation Labs is not a venture fund, incubator, or traditional venture studio.
Open Methodology
We do not claim to “know” what works. We claim that we are learning and will publish what we are testing.
Radical Transparency
Our models, playbooks, and assumptions are shared openly. They are expected to change as evidence accumulates. You will see experiments, failures, revisions, and refinements in public.
This is intentional. Scientific progress requires transparency, scrutiny, and revision. We invite experienced founders, operators, and investors to challenge our thinking and help falsify our assumptions.