Why traditional PRD doesn't save AI features in 2026: what to add to the spec

Product managers and developers of AI products face a new problem: the familiar PRD with user stories and acceptance criteria no longer works for features based on LLM — they start breaking down at the stage when the team tries to describe what exactly it is going to do.

Why the old PRD format doesn't fit

The behavior of a classical software feature is deterministic: with identical input, the system produces identical output, and acceptance criteria can be formulated as a clear checklist. The behavior of an AI feature based on LLM depends on a much larger number of variables — from the prompt formulation, the chosen model, the quality of the data against which the result is evaluated, and many edge cases that are difficult to enumerate in advance. A specification written in the old format simply does not cover these sources of uncertainty.

• The problem manifests at the stage of task description, not only at the release stage
• The classical PRD does not account for the dependence of feature behavior on the prompt and model
• It does not account for data for quality assessment and edge cases of LLM features
• It is proposed to expand the specification with new sections to address these risks

What to add to the specification

The main idea is to supplement the PRD with sections that describe not only the desired behavior of the feature, but also how the team will measure the quality of the model's answers, what data to use for evaluation, and how to respond to deviations after launch in production. This shifts part of the work that used to happen after an incident occurs to the planning stage — the team in advance writes down which edge cases are considered critical and how to track them.

What does this mean

The transition from deterministic features to LLM-based products changes product description practices themselves: instead of fixed acceptance criteria, teams move to quality metrics, test datasets, and risk monitoring plans right in the specification. This reflects a wider industry shift — AI products require not just new features in the PRD, but a new document format altogether.