AI-Powered Product Review: Enhancing Decision-Making at Uber
In the fast-paced world of product development, ensuring that every decision is well-informed and contextually rich is crucial. At Uber, we've been on a journey to streamline this process, and one of the key innovations we've developed is the AI-powered PRD Evaluator. This tool is designed to enhance the quality of Product Requirement Documents (PRDs) before they reach the review stage, ultimately improving the overall decision-making process.
The Challenge: Contextual Gaps in PRDs
Product managers (PMs) often face the challenge of assembling a comprehensive view of a product's context, including adjacent impacts, partner concerns, prior experiments, and hidden dependencies. This can lead to PRDs reaching the review stage with unsupported assumptions, blind spots in system effects, or unexamined second-order effects. The review process then becomes a lower-level discovery effort, slowing down teams and consuming reviewer attention on issues that could have been addressed earlier.
Our Solution: The PRD Evaluator
The PRD Evaluator is an AI-powered reviewer that starts with a PRD and assembles a broader knowledge base around it. It links documents, related decks, meeting notes, prior experiments, cross-functional artifacts, and preloaded Uber-specific context. This context is then used to return a structured assessment of launch readiness, focusing on strengthening the PRD before it reaches high-cost review forums.
Key Features of the PRD Evaluator
- Expanding the Field of View: The evaluator connects the PRD to prior artifacts, adjacent efforts, pre-existing hypotheses, and missing questions, providing a comprehensive view of the product's context.
- Structured Self-Review: It helps PMs identify the most important gaps in a draft, surface adjacent impacts and cross-functional dependencies, and uncover prior learnings that may not be obvious to the current team.
- Actionable Scorecard: Instead of a wall of comments, the evaluator produces a structured scorecard with a launch-readiness rating, dimension-by-dimension assessments, and clear pointers to the most important fixes.
The Value for PMs
The PRD Evaluator significantly changes the quality and timing of product thinking. It expands a PM's field of view, making self-review more structured and improving the quality of review rooms. By turning critique into usable revision, the evaluator ensures that PMs can bring the tool into their normal drafting and review workflow, strengthening the fidelity of what enters review and helping reviewers focus on higher-signal questions.
Lessons Learned
- Frameworks Beat Generic Critique: Broad comments rarely help teams move faster. The leverage comes from a framework tied to actual decision criteria and failure modes.
- Context Matters: Richer context often reveals a different set of blind spots than the document alone.
- Hard Boundaries Make Output More Honest: Defining a small set of critical gaps helped the evaluator avoid calling a PRD review-ready when the fundamentals were missing.
- Prioritization is Part of the Product: A review tool that flags everything as important isn't helping. The evaluator's value comes from telling PMs what to fix first.
- The Best AI Output Improves Human Conversations: The strongest sign the evaluator was working was that later review discussions became sharper and faster.
Where Human Judgment Still Matters
The PRD Evaluator doesn't aim to make final manual approval decisions or replace domain experts. It is most useful when it strengthens the artifact before expert review, ensuring that the right people make the right decisions at the right time, using an artifact strong enough to support those decisions.
Conclusion
The hardest part of product development is getting the right people to make the right decisions at the right time, using an artifact strong enough to support those decisions. AI has real leverage here as a structured thought partner that expands context, surfaces blind spots, and sharpens judgment before a decision reaches a high-cost forum. This pattern will matter well beyond one company or one tool, and we're excited to see how it continues to evolve and enhance decision-making processes globally.
