Is AI tool stability keeping up with the pace of new releases?
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As a software engineer, I love how fast AI tools are advancing. But lately, keeping up with constant API updates, shifting model outputs, and breaking changes in frameworks feels overwhelming.
Are you finding that the rapid pace of AI releases is making your codebase less stable, or have you found a good way to manage it?
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i love the pace of AI development, but I don’t want every new release to become a reason to rewrite working code. Sometimes the older version is good enough.
It got shaky for me too, until I stopped trusting "it works". I've been running products for 22 years, so a silent break really hurts.
What helped: my main project has about 150 Playwright end to end tests, and nothing counts as done until someone has looked at it on the real screen. My agent also has a hook that blocks it from saying "fixed" unless it states what it actually confirmed, which caught more than I expected.