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2026-09-10 · Source：TechRadar
As AI accelerates software development, independent and repeatable visual testing is framed as essential to quality assurance that engineering teams can trust.
TechRadar's argument, compressed into its headline 'AI can't mark its own homework,' is straightforward: as artificial intelligence accelerates software development, quality assurance cannot safely depend on the same generative systems that produce the code. The outlet contends that independent, repeatable visual testing is becoming essential to quality assurance that engineering teams can actually trust. The framing captures a widening tension in modern software practice — the tools that generate the work are increasingly being asked to judge it as well.
The logic rests on acceleration itself. If AI shortens development cycles, the volume of changes flowing toward production grows with it, and the verification layer has to keep pace. On the source's reasoning, testing that depends on manual effort or one-off judgment struggles to scale alongside machine-speed output. What replaces it, the report suggests, is testing that is repeatable — capable of being run identically, on demand, against every build — so that results remain comparable over time rather than dependent on who happened to run the check.
The specification of visual testing is deliberate. Interfaces are the surface where software meets its users, and visual checks give teams a consistent reference point for how an application should look and behave across releases. Independence is the other half of the equation: a verification step that shares origins with the code it evaluates cannot serve as an outside referee. Separating generation from assessment is what makes the resulting sign-off meaningful rather than self-confirming.
For engineering leaders adopting AI-assisted development, the takeaway is that confidence in what ships must be earned at the verification stage. Independent, repeatable visual testing is presented as the mechanism that lets teams move quickly without surrendering assurance in their releases. The homework metaphor lands precisely: the author of the work should not also be its examiner, and trustworthy quality assurance begins where generation ends.
Mots-clés: Visual Testing · Quality Assurance · AI Software Development · Software Testing · Developer Tools
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