// The State Of Quality
Engineering In The Age Of AI.

“The question is no longer 'can it?' - it's 'how do you govern it?'”

LLMs writing test cases is moving from experiment to standard practice. Teams are grappling with quality gates and guardrails.

“Teams that treat shift left as tooling fail, and as culture succeed.”

Shift-left has matured beyond pipelines to become an organizational practice grounded in cultural alignment.

“The pipeline is the QA process.”

CDCT is gaining adoption in microservices orgs but remains poorly understood. Requires paradigm shift in API testing.

“Most teams deploying LLM features don't have a prompt testing discipline yet.”

As LLM-integrated features proliferate, dedicated testing practices for prompts and output validation are critical.

“Most teams deploying LLM features don't have a prompt testing discipline yet.”

As LLM-integrated features proliferate, dedicated testing practices for prompts and output validation are critical.

“Production telemetry is becoming a core QE input.”

QE teams increasingly leverage observability data, logs, and metrics as primary inputs for quality regressions.

“From nice-to-have to ship-blocking.”

WCAG and ADA enforcement are driving accessibility from optional to mandatory. QE teams are now accountable.

“Requires its own QE discipline.”

Synthetic data generation solves privacy and GDPR friction in test environments. Emerging as specialized field.