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Product Engineering with Jobs-to-be-Done and Kano Model

2 videos · Oct 2026

What this trail covers

This post contributes to the field of product engineering by detailing how to translate user requests into actionable engineering tasks using frameworks like Jobs-to-be-Done and the Kano model. It emphasizes understanding the functional, social, and emotional dimensions of user needs, and how these map to architectural decisions and prioritization. The content highlights the importance of validating ideas before metrics exist, handling demanding customers, and the role of technical expertise in guiding product development. This part focuses on customer discovery habits and technical ownership, setting the stage for subsequent stages of product development.

All AI Engineer trails
  1. Build the Right Thing: Product Engineering (Part 2) — Kent C. Dodds, EpicProduct.engineerThis post introduces two key frameworks for product engineering: Jobs-to-be-Done (JTBD) and the Kano model. For JTBD, it demonstrates how to move beyond superficial feature requests (e.g., facial recognition for workshop entry) to understand the underlying user need (e.g., efficient workshop entry without missing content). This involves dissecting needs into functional, social, and emotional dimensions, which then inform engineering decisions about system design and user experience. For the Kano model, it illustrates how to categorize user requests (e.g., for a food delivery app) into basic needs (reliable confirmations), performance gradients (delivery estimates), delighters (discounts), and unexpected features (GPS tracking). This categorization guides architectural effort, prioritizing reliability for basic needs, measurement for performance, and reversible experiments for delighters. The post also touches on handling feature prioritization, validating ideas, and the relationship between technical expertise and product judgment.
  2. Build the Right Thing: Product Engineering (Part 1) — Kent C. Dodds, EpicProduct.engineerThis post contributes to the field of product engineering by emphasizing the importance of customer discovery and technical ownership in building the right thing. It introduces frameworks like 'The Mom Test' to gather behavioral evidence from users, distinguishing it from superficial compliments. The talk highlights how understanding user needs and validating problems before implementation directly influences architectural choices and the prioritization of engineering effort. It advocates for a product engineer's role in connecting customer needs to data models, workflows, and the smallest useful slice of a system, ensuring that technical execution aligns with genuine user value.