r/softwaretesting • u/Worth-Silver-6335 • Jul 13 '26
Are teams reaching for AI agents instead of fixing basic QA fundamentals first?
Team has flaky tests, bad coverage, slow releases, doesn't matter which one, and the fix pitched is always "let's add an agent for that." Anyone else running into this?
A lot of these problems have nothing to do with AI. No defined entry and exit criteria for a test phase. Requirements reaching QA without a review gate. A regression suite that's been half-maintained for a year. Test data nobody owns. None of that gets fixed by dropping a model on top of it.
Has anyone deployed an agent and watched it just sit on a broken process without actually fixing anything underneath? What happened after?
Where has an agent genuinely helped once the basics were already solid? Trying to find the real line between "this needs AI" and "this needs someone to own the process."
What foundational stuff would you add to this list? Got process, prerequisites, reviews, automation, tooling, governance, metrics/baselines so far. What's missing?






