Conventional wisdom suggests attacking an incumbent's weak points. Serval did the opposite with ServiceNow, targeting its core strength: configurability. By using AI to make customization drastically faster and easier, they offered a superior version of the feature that locks customers in, creating a compelling reason to switch.
Building an AI-native product requires betting on the trajectory of model improvement, much like developers once bet on Moore's Law. Instead of designing for today's LLM constraints, assume rapid progress and build for the capabilities that will exist tomorrow. This prevents creating an application that is quickly outdated.
Intense early customer love from a small, specific niche can be a false signal for product-market fit. Founders must distinguish between true market pull and strong fit within an unscalable sub-market before they saturate their initial user base and growth stalls.
Founders who have experienced failure develop healthy skepticism, preventing them from acting on weak signals. They require an overwhelmingly high bar of evidence, like ten consecutive successful demos, before believing they've truly achieved product-market fit and are not deluding themselves.
Founders without product-market fit constantly optimize small things, believing better execution is the key. In contrast, with PMF, solid execution yields disproportionate results. Sales calls close without "Jedi mind tricks" because customers want the product.
Traditionally, startups attack the mid-market due to the complexity of enterprise products. Serval's founder argues GenAI enables small teams to build feature-complete, enterprise-grade platforms quickly. This unlocks a go-to-market motion of directly displacing incumbents from the start.
Jake Stauch and his co-founder spent five years at hyper-growth company Verkata, where they were paired to build new product lines. This acted as a multi-year, real-world "test drive" of their dynamic, de-risking one of the biggest challenges in starting a company.
Initially, customers often "round down," focusing on missing features. A key sign of product-market fit is when they start "rounding up"—their faces light up in demos, and they imagine the product's future potential, forgiving current limitations because they believe in the core value.
Generic discovery questions like "what's your pain point?" yield generic answers. A better question is, "If you hired someone to sit next to you, what would you have them do?" This reveals the tedious, unglamorous tasks that are ripe for an automation-focused product solution.