ENGINEERING BLOG

AIQualityInsights

Data-backed guides on AI quality engineering, LLM testing, and shipping AI systems that behave reliably in production.

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AI-Assisted Test Automation That Passes Code Review

AI Quality Engineering

Oct 17, 2026

5 min read

AI-Assisted Test Automation That Passes Code Review

AI test automation passes code review when the assistant knows your rules and checks locators on the live app. How we built it with Claude Code and MCP.

Kulish Kulshrestha

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Flaky Tests in CI: How to Take Over a Red Pipeline

Test Automation

Oct 17, 20265 min read

Flaky Tests in CI: How to Take Over a Red Pipeline

Flaky tests in CI usually trace back to shared-environment leaks and unmanaged failures. How to quarantine, clean up run by run, and take over a red pipeline.

By Kulish Kulshrestha

API Testing

Oct 17, 20265 min read

GraphQL API Testing: Four Gaps That Let Broken Mutations Pass

GraphQL API testing fails when mutations are checked only by their own response. Four gaps that let broken mutations pass, and how to close each one.

By Kulish Kulshrestha

How to Fix Flaky Playwright Tests: Wait on the Network, Not the Clock

Test Automation

Oct 17, 20265 min read

How to Fix Flaky Playwright Tests: Wait on the Network, Not the Clock

Flaky Playwright tests come from guessed waits, fragile locators and inline data. Learn to wait on the network instead, with lessons from a real engagement.

By Kulish Kulshrestha

How to Choose an AI Testing Partner in 2026

Buyer Guides

Jun 29, 20269 min read

How to Choose an AI Testing Partner in 2026

A buyer-focused guide to evaluating an AI testing or quality engineering partner, including the seven criteria that matter, the build versus buy versus partner decision, and the red flags to walk away from.

By Kulish Kulshrestha

How to Test an LLM Before Production: A Readiness Guide

LLM Testing

Jun 22, 202610 min read

How to Test an LLM Before Production: A Readiness Guide

A practical guide to evaluating a large language model feature before you ship it, covering the input categories to cover, the metrics that matter, realistic thresholds, and the methods that hold up under scrutiny.

By Kulish Kulshrestha

AI Quality Engineering

Jun 15, 20268 min read

What Is AI Quality Engineering? A Working Definition and Field Guide

AI Quality Engineering is the practice of validating non-deterministic AI systems for safety, accuracy, robustness, and drift before and after production. Here is what it covers, how it differs from traditional QA, and what good looks like.

By Kulish Kulshrestha

Have an AI system to validate?

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