There is a difference between recognising a familiar pattern and assuming you already know the answer. Experience makes the first easier. It can occasionally tempt us into the second.
The value of having lived through earlier technology shifts is not that every new tool is the same. It is that you have a library of questions worth asking.
Use the analogy. Then test its limits.
A new AI workflow may remind you of an earlier automation project. That can help you anticipate training needs, ownership problems and brittle handovers. It does not tell you exactly how this system will behave.
Use the old lesson to design a better experiment, not to skip the experiment.
Choose one real task.
You do not need to master every tool. Pick something small that you understand well enough to evaluate. Try it, record what worked and note where you needed to intervene.
Compare notes across generations.
Someone newer to the industry may spot a possibility you have dismissed too quickly. You may recognise a practical consequence they have not encountered yet. The productive conversation makes room for both.
Keep a “changed my mind” list.
When a result surprises you, write down what you expected and what happened. It is a simple way to separate what you know from what you have merely become used to believing.
“Experience, still updating” is a commitment to staying useful. Bring what you have learned. Leave room for what you have not.