qa exploration
How I think through an issue once it's reported: a symptom feeds forward through the categories most likely to explain it, then through the tools I use to confirm which one it actually is.
Nodes are stages of investigation, not literal weighted connections. Read left to right.
→ Sentry payload trace
Usually a sign the request itself was malformed, unauthenticated, or rate-limited before it reached business logic. I check auth tokens, payload shape, and headers first, using Sentry to see exactly what the client sent.
→ Datadog service trace
These point further upstream: a crashed process, an unhealthy dependency, or a timeout somewhere in the chain. I use Datadog traces and logs to isolate which service actually failed, rather than assuming it's the one that returned the error.
→ Manual & automated repro
Harder to catch, because the request often succeeds and the response is just wrong. These need careful reproduction (same data state, same sequence of actions, same timing) until the bug shows itself reliably.
→ Root cause confirmed / regression coverage added
How I actually catch the categories above before release: manual exploratory sessions on new features, a Playwright regression suite for known-critical paths, and Claude to help draft and maintain test cases as coverage grows.