Several people objected with "what if XYZ left the company two years ago?" That points to a process opportunity in how we treat both comments and offboarding.

But first, she& #39;s now Katie. That& #39;s the name I used in my head. Katie knows this code best. https://twitter.com/hillelogram/status/1309200884535042052">https://twitter.com/hillelogr...

If Katie is the go-to person for an area of the codebase, that means there& #39;s a lot of implicit knowledge in her head that& #39;s not written down. Fair enough.

But there& #39;s another layer of implicit knowledge: that Katie is the expert! People don& #39;t automagically know that!

Once Katie leaves, not only are you losing the implicit code expert, you may not *know* you& #39;ve lose the expert. You& #39;ll burn a ton of time asking everybody else what they know.

And Katie isn& #39;t going to be an expert in just one thing. How many other things will be like this?

But if we read

# Katie knows this code best

We now immediately know who the code expert is. If she& #39;s here, great, if she left, we know we have to start understanding it from scratch.

But why wait until we read it? Handle it while she& #39;s offboarding!

Katie puts in her two weeks notice. We immediately sweep the codebase for any mentions of "Katie knows this code best" to figure out what implicit knowledge we& #39;re about to lose, so we can preemptively have Katie transfer knowledge. Turn "obsolete" comments to our benefit.

The adoption barriers, though: First, we need to make it easy to do analytics on comments. Seems not to bad, it just means adding structured metadata to comments. Maybe

# !EXPERT: Katie Hu {ref-id} {date}

To make grepping easy

Bigger barrier is this requires companies to be remotely competent at offboarding, and hoo boy Edmodo left me with AWS keys and github repo access for a year after I left, and that& #39;s nowhere near the worst horror story I& #39;ve heard

Get your offboarding shit together everyone