Agentic Loops Study: Move Fast and Be Responsible
The first step in building agentic products is knowing what to build. Survey data is useful, but it should not be treated as a direct instruction list. My thought is that the goal is to study the data carefully, understand how it changes your beliefs about users, and refine my mental model of what they actually need.
If we simply build whatever users say they want, we may end up with something narrow, confusing, or not widely accepted. The better approach is to use feedback as evidence, then make a higher-level product decision from a clearer understanding of the user.
A responsible agentic product loop should include:
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Study the survey data carefully
Look for patterns that change your beliefs about users, not just isolated requests. -
Refine your mental model
Use the data to better understand what users want, what they struggle with, and what they may not be able to clearly express. -
Make higher-level product decisions
Our role is not only to follow feedback directly. It is to define a clear product vision and decide what should actually be built. -
Prototype with agents without causing harm
Move fast, but think about how to test ideas safely before shipping them broadly. -
Use clear specifications and evals
Define what the system should do, then compare performance using datasets, benchmarks, or other evaluation levels. -
Create external feedback loops
Start with friends, then a small group of trusted users, then maybe 10 reviewers, and later 100 alpha testers.
The core principle is simple: move fast, but be responsible. Use data to update your beliefs, prototype safely, and expand testing only as confidence grows.
