Founders often try to convince themselves they have PMF. The actual moment of achieving it feels like a sudden, unmistakable change—a switch, not a spectrum—making it clear that all previous feelings were just wishful thinking.
Unlike other software, security product value is hard to prove. If a tool finds nothing, it's unclear if the tool failed or if there were no issues to begin with. This shared uncertainty for both buyer and seller makes it difficult to assess true value.
Marketplaces are chaotic, recursive systems. Running A/B tests often reveals unexpected second-order effects that invalidate strong hypotheses. This process forces 'epistemic modesty' by teaching operators the limits of their own knowledge and the necessity of experimentation.
Believing there's a way to multiply a company's value, like a hacker seeking a vulnerability, can be a self-fulfilling prophecy. This mindset forces you to relentlessly identify and solve the highest-leverage problems, leading to an outsized impact.
Years ago, founders could rely on a relatively stable underlying tech system. Today, the core assumption is that the entire market, product, and competitive landscape can change every three months, requiring a much higher level of alertness and paranoia to survive.
FAIR experimented with various value propositions. The breakthrough wasn't a new technical feature but rebranding their existing 'net terms plus returns' policy into the simple, compelling phrase 'Try Before You Buy,' which customers immediately understood.
The old security adage was to be better than your neighbor. AI attackers, however, will be numerous and automated, meaning companies can't just be slightly more secure than peers; they need robust defenses against a swarm of simultaneous threats.
Manually analyzing 30 data points builds deep intuition and overcomes the tech industry's bias for big data. It's enough to distinguish a major signal (e.g., a 60% rate) from a minor one (10%) and inform immediate action without complex analysis.