Why AI dev quality needs systems thinking and community building
Quality Assurance (QA), or testing, has evolved over the years alongside better automation and development processes. Ideally, developers test as much as possible as they build. The old saw is that the cost of fixing quality and security grows tenfold at every gate from the developer's desktop to the running app. Now, in the agentic development age, AI "guidance" runs the risk of confidently scaling quality debt at an unprecedented rate. The core problem is that human-written code fails in recognizable patterns that can usually be traced back to a documented assumption. Agent-generated code tends to look coherent on the surface and fail differently underneath.
QA has typically taken a back seat to software development on budget and prestige because it's not as visible or glamorous. Leapwork CEO Ken Ziegler observes:
The asymmetry held because creation is visible and validation isn't. Enterprises optimized what they could measure easily, and for...
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