QA engineers must think like adversaries

What happens when Ramp-testing a vehicle happens around the assembly line, earlier-faster-deeper-and-smarter than before? And as ruthless as a crash-test?

- By Pratima H

Shrish Ashtaputre, Senior Technical Director Engineering, Calsoft takes us around this new software 'proving ground' that shows how AI is influencing shift-left testing, AI-assisted quality engineering, preventive testing mindsets, security-integrated validation, intent validation, synthetic monitoring, API-level load simulations and edge-case testing; while he also confronts the dangers of automation, jailbreaking/ prompt manipulation risks and the challenges of skeuomorphism.

What has changed about QA in the last four to five years; and how proactive, shift-left, Already, Al-driven and security-sharp is this frontier becoming?

QA used to come in at the end, checking if things worked. Now it's part of how things are - built in the first place - driving quality decisions instead of just verifying them. We've seen the rise in shift-left testing, Al-assisted quality engineering, and security-integrated validation. Test engineers are now expected to understand pipelines, cloud-native architectures, and even prompt engineering for AI tools. The mindset has become more preventive than detective. AI has become part of QA’s toolkit, helping predict weak spots and optimise testing. At the same time, QA must validate the integrity and fairness of AI systems — making it both a user and a guardian of AI.

Are QA and testing blurring their boundaries with Development- specially in the early phases of application-builds? What is changing here with DevOps and SecOps?