Separate Empirical Signals From Key Assumptions
The founder conducts a rigorous audit of their fit diagnostic to segregate facts backed by hard data from untested hypotheses. They categorise every claim regarding market access, customer receptivity, and technical authority into validated or assumed columns.
Completing this action eliminates optimism bias and reveals the true risk profile of the founder's market position. It protects the overall venture evaluation by ensuring strategic decisions are made on empirical proof rather than founder wishful thinking.
The founder must generate a two-column evidence ledger explicitly listing each capability claim alongside its supporting validation, such as signed letters of intent, historical P&L responsibility, or third-party endorsements. Any unverified assertion must be flagged as a high-risk assumption.
Five questions an expert would ask when reviewing your output
Use these to challenge assumptions, pressure-test your logic, and check the quality of this action's output in the context of the parent task and wider venture development.
- 1
Which of your claimed market connections are based on actual historical commercial transactions rather than casual warm leads?
- 2
What concrete validation proves that prospective customers view you as a credible authority in this space?
- 3
Why have you classified your regulatory understanding as validated when you lack formal compliance certifications?
- 4
How significantly would your market-fit thesis collapse if your top three unverified assumptions prove false?
- 5
What specific, low-cost experiment can you run immediately to convert your critical assumptions into empirical signals?