Comparison
AI for output vs AI for input in product management
A comparison of the two ways product teams use AI. On the output side it drafts PRDs, specs and summaries faster, but every document still rests on whatever understanding of the customer the team already had. On the input side it removes the cost and delay of talking to customers, so research stops being rationed and teams ask before they decide. Koji works on the input side, with AI-moderated interviews and automatic thematic analysis.
Where this appears
What's in this comparison
AI for output
- Drafting PRDs and specs faster
- Writing summaries of what you already know
- Speeds up documenting a decision
- Rests on whatever customer understanding you had
AI for input
- Removes the cost and delay of talking to customers
- Research stops being rationed to once a quarter
- You ask customers before deciding, not after
- Takes on the synthesis that used to take weeks
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<a href="https://www.koji.so/visuals/ai-for-output-vs-input-product-management"><img src="https://www.koji.so/visuals/ai-for-output-vs-input-product-management/ai-for-output-vs-input-product-management.png" alt="Comparison of AI for output, like drafting PRDs and summaries, against AI for input, like cutting the cost of talking to customers before deciding." width="1200" height="695" /></a>
<p>Source: <a href="https://www.koji.so/visuals/ai-for-output-vs-input-product-management">AI for output vs AI for input in product management</a>, Koji</p>
