Test a new tool on the lowest stakes work first

Before trusting a new AI tool with anything that matters, run it through the least important task you can find, something where a bad result costs you nothing but a few minutes. I check a new tool this way myself before I recommend it to anyone, since low stakes work is where its real habits show up first. This might mean testing it on an old, already-finished project instead of a live one, or on an internal note nobody outside the team will ever see. Low stakes testing lets you learn how the tool behaves, where it tends to slip up, and what kind of instructions it needs, all without any real risk attached. Only after it proves itself here should it move toward anything with real consequences attached to a wrong answer. Skipping this step is how teams end up surprised by a tool's weak spots at the worst possible moment.

Try this today: pick your least important task from this week and test your newest tool on it before using that tool anywhere it could actually cause a problem.