Loop Engineering: Designing and Observing the Loops That Run Your Agents With Opik

A prompt encodes one way to solve a problem. Change that input and that path often breaks. Loop engineering targets the process instead. You design the cycle the agents runs: it acts, checks the result, and decides whether to keep going. The agent finds a path rather than following one you scripted. This talk covers how to design those loops deliberately. We'll walk through the anatomy of an agent loop, why stopping conditions deserve to be treated as a first-class design decision, how to tell a recoverable error from a hard blocker, and why the most reliable exit conditions lean on deterministic checks rather than asking the model to grade its own work. The other half of the problem is visibility. A loop you can't see inside is a loop you can't debug. Using Opik, an open-source observability and evaluation platform, we'll instrument an agent's loop so you can trace what happens at each iteration, measure where it breaks down, and set up the evaluation that tells you whether a change actually made things better. You'll leave with a clear mental model for loop design and a practical workflow for observing and improving agent behavior before it reaches your users.