API checks, automation and AI in QA

I use Cursor and ChatGPT to draft API collections in Bruno and performance scenarios in k6. That buys back hours. It does not tell anyone whether a release is safe.

These notes cover the technical layer as a functional tester should own it: a small set of API checks tied to user journeys, automation that guards what is already understood, and a firm rule that a fluent answer from a model is not evidence.

3 notes on api checks and ai

P213 Oct 20267 min read
API smoke checks functional QA should own
You do not need to become an SDET to protect integrations. A small set of API smoke checks anchored to user journeys catches a class of surprises before UI testing starts.
P021 Aug 20267 min read
When more automation hides a broken user journey
Pipelines get greener while users still struggle. Why automated tests pass over a broken journey, and how I keep functional truth ahead of technical coverage.
P118 Aug 20267 min read
AI in QA without fake confidence
I use AI to speed up API and performance work. I do not let a model decide that a release is safe. Where it helps in QA, and where a fluent answer gets mistaken for evidence.