#coding-transformation

#coding-transformation

The most dangerous assumption in quality engineering right now is that you can validate an autonomous testing agent the same way you validated a deterministic application. When your systems can reason, adapt, and make decisions on their own, that linear validation model collapses.

We will be retiring the beta shortly and will be removing the button to get to it and ceasing support for it. The beta garnered negative feedback from the Stack Overflow community, including observations that it looked more like a general discussion site such as Reddit and was losing the essence of what made it successful: precise questions and community-validated answers.

Legacy software, often described as 'big balls of mud,' has accumulated over decades, becoming difficult to maintain and understand. These systems rely on extensive teams to function, despite their outdated technology.

Modern web applications are no longer just "sites." They are long-lived, highly interactive systems that span multiple runtimes, global content delivery networks, edge caches, background workers, and increasingly complex data pipelines. They are expected to load instantly, remain responsive under poor network conditions, and degrade gracefully when something goes wrong.

This extends to the software development community, which is seeing a near-ubiquitous presence of AI-coding assistants as teams face pressures to generate more output in less time. While the huge spike in efficiencies greatly helps them, these teams too often fail to incorporate adequate safety controls and practices into AI deployments. The resulting risks leave their organizations exposed, and developers will struggle to backtrack in tracing and identifying where - and how - a security gap occurred.

Software development used to be simpler, with fewer choices about which platforms and languages to learn. You were either a Java, .NET, or LAMP developer. You focused on AWS, Azure, or Google Cloud. Full-stack developers learned the intricacies of selected JavaScript frameworks, relational databases, and CI/CD tools. In the best of times, developers advanced their technology skills with their employer's funding and time to experiment. They attended conferences, took courses, and learned the low-code development platforms their employers invested in.

One thing I always do when I prompt a coding agent is to tell it to ask me any questions that it might have about what I've asked it to do. (I need to add this to my default system prompt...) And, holy mackerel, if it doesn't ask good questions. It almost always asks me things that I should have thought of myself.

Just as software finished eating the world, zero interest rates ended. Companies optimized for cash and slowed hiring. The market didn't shrink, but stopped growing at the breakneck pace we all expected. The result: a glut of entry level talent groomed for jobs that never materialized. This would explain a more competitive entry level market. But it doesn't explain the entry-level market shrinking, despite overall industry growth. In short: demand for senior talent is rising, but has fallen off a cliff for juniors.