Feedback Loop
What is a feedback loop?
A feedback loop is an iterative process where you make a change, measure its impact, and use that information to inform the next change, creating a continuous cycle of improvement. In the context of AI product development, evals enable fast feedback loops by allowing developers to quickly test modifications—like prompt changes, model changes, or temperature adjustments—run evaluations to measure their impact, and decide whether to release or discard the changes.
This concept is fundamental to both product discovery and AI development, as it creates a systematic way to learn and improve through rapid experimentation.
How do feedback loops work in AI development?
The feedback loop follows a cycle: analyze, measure, improve, reanalyze. You start by analyzing your data, looking at your traces to understand what's happening. You put metrics around it through evals so you can measure performance. Then you make an improvement and reanalyze to see if it worked.
This process mirrors the scientific method. Every time you make a change—whether to your model, prompt, temperature, or chunking strategy—you run your evals to see if your grid gets more green. If it doesn't improve, you can identify which error category is failing more often and target that specific problem. This fast feedback loop enables hundreds of experiments and continuous refinement.
Why does breaking feedback loops create problems?
Feedback loops work when elements inform each other bidirectionally. For example, defining a problem impacts the range of solutions available, and exploring solutions refines your understanding of the problem. This two-way flow generates valuable insights.
When you sever the feedback loop—by splitting activities into separate steps performed by different people or creating long delays between changes and measurement—you lose this learning. In AI development, without evals providing fast feedback, you're forced to rely on slow, manual testing or gut feel rather than systematic measurement. The speed of your feedback loop directly impacts how quickly you can improve your AI product.
Learn more:
- Behind the Scenes: Building the Product Talk Interview Coach
- How I Designed & Implemented Evals for Product Talk's Interview Coach
- Product Managers Don't Own the Problem (And Designers Don't Own the Solution)
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