Granola · AI product · Senior · 45 to 60 minutes

How should Granola handle meeting capture?

Granola is a product that uses AI to help people take notes from meetings and conversations. Answer this product management case and get it graded line by line against a weighted rubric.

Product strategy
User insight
AI product judgment
Prioritization
Risk management

The situation

Granola's founders ask you, a senior PM, to recommend the product strategy for the next stage of growth in AI meeting notes. The category is getting crowded with tools that join calls as visible bots and then send summaries after the meeting. Some customers like the automation, but others, especially in roles with sensitive conversations, worry that a visible bot changes behavior, creates privacy concerns, or makes delicate meetings awkward. Granola believes strong notes could be especially valuable in those higher stakes settings, but the team cannot invest equally in every path. Assume Granola can deeply support one core meeting capture model and one primary market story over the next two quarters. You need to decide what user problem Granola should solve first, how the product should capture meeting context, which customers to target, and how to validate the bet without damaging trust. The hard part is balancing note quality and ease of use against user comfort, privacy expectations, and competitive pressure from more obvious, more automated rivals.

What to produce

Write a 1 to 2 page product strategy memo.

Your answer must

State the decision you recommend on Granola's core meeting capture approach and the user promise behind it.
Identify the primary target users and meeting types to prioritize first, and explain why they are the best wedge.
Analyze the main tradeoffs, including user comfort, privacy and consent, note quality, ease of use, and competitive differentiation.
Propose a validation plan with leading indicators, research methods, and success metrics for the first rollout.
Describe key second order effects and risks, and how you would mitigate them in product, policy, or go to market choices.

Constraints

You cannot assume Granola can build and maintain two fully supported capture experiences in parallel.
The recommendation must work in workplaces where some conversations are sensitive or high stakes.
Trust is part of the product, so privacy and consent concerns cannot be treated as a later legal cleanup.
Granola is competing in a market where more automated, bot-centric alternatives already exist.

Format

Use five sections: decision, target users, tradeoffs, validation plan, risks and sequencing.

How Granola actually played it

Analyzes Granola's approach to AI meeting notes without a visible bot, including privacy-first design and its rollout inside a firm where most staff adopted it within months. It looks at the offer, the user and the competitive choices.

Avoid bots in the meeting to protect user comfort
Design for discretion in sensitive workplaces
Fast internal adoption is a signal worth studying

Built from Granola's Revolutionary AI Strategy That Crushes Meeting Bots In Crucial Conversations by Michael Goitein (Product Strategy Decoded).