What is Continuous Discovery Habits about?

Continuous Discovery Habits is Teresa Torres's practical guide to making product discovery a sustainable, weekly team practice rather than a periodic research event. Torres has coached product teams at companies including Spotify, IBM, and Twilio, and the book synthesizes what she has observed separates teams that consistently build the right things from those that execute efficiently on the wrong things.

The core argument is that product discovery — the work of determining whether a potential solution will create value for customers and the business — needs to happen continuously alongside delivery, not in separate phases. The habit Torres recommends is simple in structure: interview at least one customer per week, as a team. Not a monthly focus group, not an annual user research project — a weekly, ongoing, lightweight touch with real customers. The frequency is the point: it creates a cadence that keeps the team's understanding of customers current rather than stale.

The main analytical tool Torres introduces is the Opportunity Solution Tree — a visual framework that organizes the relationship between a desired business outcome, the customer opportunities that could achieve it, and the solutions being considered for each opportunity. The tree keeps the team focused on outcomes rather than features, makes explicit the assumptions behind each solution, and prevents the common problem of fixating on a single solution without considering the range of opportunities that could address the desired outcome.

Torres also addresses assumption testing and experiment design. She distinguishes between product risks — will customers want this, can we build it, should we build it, and can we grow the business with it — and provides a framework for designing experiments that test the most critical assumptions first with the least investment. The book's practical orientation extends to story mapping, assumption mapping, and a specific cadence for how discovery and delivery work should fit together in a typical sprint cycle.