How an AI Coding Agent Helped Debug a Kotlin-Spring Boot-Kafka Payments System

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A developer debugging a Kotlin and Java payments system using Spring Boot and Kafka uncovered multiple defects from a single visible symptom, roughly half of which were unrelated to the original issue. The session was conducted using Explyt's AI agent inside a JetBrains IDE, with a frontier language model in regular chat mode. All defects shared a common invariant: any operation on a terminal ID must follow a single asynchronous path and keep two downstream systems, TMS and EMV, in sync. The AI agent played a tactically supportive role — proposing SQL queries, flagging code risks, and explaining logic — but the developer drove every diagnostic and fix decision manually. The case was reviewed by Explyt's product manager through session logs as part of an ongoing study into how developers debug with AI agents in practice.

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