To manage an infinite stream of feature requests for their horizontal product, Missive's founders relied on a simple filter: "Would I use that myself?" This strict dogfooding approach allowed the bootstrapped team to stay focused, avoid feature bloat, and build a product they genuinely loved using.

In early stages, the key to an effective product roadmap is ruthlessly prioritizing based on the severity of customer pain. A feature is only worth building if it solves an acute, costly problem. If customers aren't in enough pain to spend money and time, the idea is irrelevant for near-term revenue generation.

The old product leadership model was a "rat race" of adding features and specs. The new model prioritizes deep user understanding and data to solve the core problem, even if it results in fewer features on the box.

Datycs' initial product, a patient chart summarizer for physicians, faced slow adoption from health systems. The company found a more viable business model by pivoting to solve an urgent problem for payers: processing massive volumes of unstructured documents for back-office operations.

Raw customer feedback is noise. To make it actionable for Product, organize it along two dimensions: impact and frequency. This simple framework separates signal from noise, distinguishing high-priority, high-impact issues from niche requests and creating a clear basis for roadmap decisions.

Avoid the trap of building features for a single customer, which grinds products to a halt. When a high-stakes customer makes a specific request, the goal is to reframe and build it in a way that benefits the entire customer base, turning a one-off demand into a strategic win-win.

Instead of waiting for experience teams to request an API, platform teams should analyze top-level business goals and proactively propose services that unlock new use cases. This shifts the dynamic from a reactive service desk to a strategic partner.

CEO Srini Rawl explains that while many companies focused on structured healthcare data, Datycs targeted complex, unstructured documents. This challenging niche became their competitive advantage, creating a significant data and experience moat after processing over 15 million clinical charts.

The rapid evolution of AI makes traditional product development cycles too slow. GitHub's CPO advises that every AI feature is a search for product-market fit. The best strategy is to find five customers with a shared problem and build openly with them, iterating daily rather than building in isolation for weeks.