Manish Saini

AI has rewritten the rules of software delivery. Entire modules can now be produced in minutes. Features that once took weeks emerge as suggestions in seconds. Development speed isn't just "fast" anymore - it's exponential. But here's the reality check: velocity without quality is chaos. When every line of code can be shipped instantly, the critical question changes.

Modern software teams thrive on speed. Features move from idea to production in days, sometimes hours. But rapid delivery comes with a catch: testing must keep pace. If feedback loops are slow, flaky, or unreliable, confidence drops and delivery stalls. The key isn't running all tests in every pipeline run - it's structuring pipelines for instant, high-value feedback. Why Testing in CI/CD Is Different In traditional environments, testing was a separate stage, often at the end.

I was reading an article in The Washington Post that stopped me in my tracks. It said employers now expect employees to be "AI-literate" - comfortable using tools like ChatGPT, Canva AI, and more - even for non-technical roles. And it doesn't stop there. One-third of executives are planning to include AI skills in performance reviews and hiring decisions. That hit me hard because I remembered a time not too long ago when simply learning a new testing framework felt like a huge leap.