Domain Expertise
What is domain expertise?
Domain expertise refers to deep knowledge and understanding of a specific field, problem area, or customer context. In the context of building AI products, domain expertise is crucial for tasks like error analysis, writing effective prompts, and creating evals, because it helps you understand what "good" looks like, what customer use cases to account for, and how to properly contextualize the AI's work.
This knowledge becomes essential for bridging the gap between technical AI capabilities and real customer needs.
Why does domain expertise matter for AI product development?
To get an AI to perform reliably, you need to provide the right context. Domain expertise helps you know what that context should be. When engineers write prompts without sufficient domain expertise, they may not account for the nuances of customer use cases or understand what quality looks like in that specific field.
Product managers often have deeper domain expertise than engineers, which is why they need to be involved in AI product work from beginning to end—not just in defining requirements, but in hands-on tasks like prompt engineering and error analysis.
What AI product tasks require domain expertise?
Domain expertise becomes critical for several key activities. Writing prompts requires understanding how customers actually use your product and what problems they're trying to solve. Conducting error analysis means knowing when the AI's output misses the mark in subtle but important ways.
Building evals depends on domain expertise because you need to define what "good" outputs look like. You can't effectively judge AI quality without understanding the domain well enough to recognize correct, helpful, and appropriate responses across different scenarios.
Learn more:
- Behind the Scenes: Building the Product Talk Interview Coach
- Building My First AI Product: 6 Lessons from My 90-Day Deep Dive
- Building AI Products - All Things Product Podcast with Teresa Torres & Petra Wille
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