Systems | Development | Analytics | API | Testing

A conversation with Gastón Marichal, QA Manager at QAlified, on why the hardest part of agentic QA has nothing to do with the technology. In the first installment of this series, we heard from Huy Tieu, a Katalon product manager building an AI quality companion from the inside. This time we wanted the other side of the table: someone who has to make agentic QA work for real client teams, on real delivery timelines, with real consequences if it goes wrong.

I’ve watched enough production incidents get traced back to a "small" API change to know this: contract testing tools exist because integration bugs are expensive, and most teams find that out the hard way. One service changes a response field, nobody notices until a downstream consumer breaks in production, and now three teams are on a call at 11 PM figuring out whose change caused it. Most "best contract testing tools" lists just dump fifteen names on you with no structure.

Your frontend can look flawless — fast search, clean filters, a map view that renders in under a second — and none of it will matter the day you connect your fifth MLS. Somewhere between the second and third regional feed, most PropTech teams hit the same wall: the code that worked beautifully for one market starts breaking in ways nobody predicted. A field that was always a number is suddenly a string. A boolean flag for “has pool” shows up as free text in the new feed.

A React Native build is really two builds stacked on top of each other. On Android, Gradle compiles your Kotlin and Java, then drops down into cmake and ndk-build to compile the C++ that ships inside Hermes, Folly, ReactCommon, and your own turbo modules. On iOS, Xcode does the equivalent: Swift and Objective-C on top, the same C++ underneath via Clang. Two build systems, two languages on top, one shared set of C++ underneath.

This post is the technical follow-up, written for solution architects and developers wanting to take the next step on leveraging Kong Konnect Metering & Billing's new prepaid credits in addition to post-consumption invoice billing.

If your brand does not appear when buyers ask ChatGPT, Perplexity, or Google AI Overviews for recommendations, you are invisible to hundreds of millions of potential customers. ChatGPT alone now reaches 900 million weekly users. The shift is clear: buyers now get answers directly from AI engines rather than clicking through to websites.

Buying the devices is the easy part. The other 90% of the work is what nobody builds into the budget.

AI coding agents have quickly become part of the daily workflow for Node.js developers. Whether you're using Claude Code, Codex CLI, OpenCode, Antigravity CLI, or Pi Agent, these tools are great at generating code, explaining implementations, and automating development tasks. But debugging production systems is a different challenge.

Most agencies compare plans by scanning feature grids. The ones that pick the right plan on the first try do arithmetic instead.

The decision is not which product to choose. It is whose performance you are reporting on.