---
title: "Product decisions: what to build, in what order, and what to cut"
description: "How the product role moves when AI makes building cheap, how discovery runs with a model as the second reader, and how to specify an AI feature so it can be tested."
url: https://torn.studio/en/topics/product-decisions
locale: en
---

# Product decisions: what to build, in what order, and what to cut

> **Short answer:** The product decisions shelf gathers the questions that settle what gets built: where the role moves when AI makes production cheap, how discovery runs with a model as the second reader, how an AI feature is specified as test cases, and how a prioritization decision is written down so it holds. Every article carries a decision the studio made and what it cost, or a measurement with its method stated.

## Insights

- [AI in product discovery: do the synthesis yourself first](https://torn.studio/en/insights/ai-in-product-discovery) — How should a product team use AI in discovery? — Use AI in product discovery as a second reader. A person synthesizes every interview first, a model synthesizes it second, and the two readings are compared. Teresa Torres’s December 2025 rule is that dumping transcripts into a model is no shortcut. Models are good at desk research, clustering and drafting, and they miss what a customer left unsaid.
- [Evals are the spec for an AI feature](https://torn.studio/en/insights/evals-are-the-spec) — How do we specify an AI feature so it can be tested? — An AI feature is specified as an eval: a written set of cases the feature must handle, the cases where it must refuse, and a tolerance for how often it may miss, agreed before the first prompt. Hamel Husain’s March 2024 finding: unsuccessful AI products almost always share one root cause, no robust evaluation. The product role writes the eval.
- [When building gets cheap, deciding gets expensive](https://torn.studio/en/insights/when-building-gets-cheap) — What happens to the product role when AI makes building cheap? — AI tooling has made producing software cheap, and the gain is smaller than it feels: METR’s 2025 trial found experienced developers 19% slower with AI while believing they were 20% faster. The constraint moves to deciding what to build, how to know it worked, and whether users can trust it. That is the product role, and it got harder.
- [Case: a gynecology clinic, its care flows and its website](https://torn.studio/en/insights/case-clinic-care-flows-and-website) — What does a real engagement look like, from kickoff to launch? — A Swedish women’s health clinic opened its physical and digital practices at once. The care flows in the platform came before the website: visit types, questionnaires, booking and fees were ready for opening day on 15 December 2023, and the website was rebuilt over the three months that followed. The order was a decision that cost visibility during the launch.
- [Deciding what to build next](https://torn.studio/en/insights/deciding-what-to-build-next) — How do I decide what to build next? — A prioritization decision holds when it is written down: what gets built, which problem it solves, what is set aside, and what has to be true in two months for the decision to have been right. One page per decision is enough, read aloud at the next review.