I think I'll reword it to make it clear that there are approaches that use more than just a training and test set without actually mentioning a validation set as an example (so I don't have to explain it further).
Just for this conversation (not the blog), later in the article there's an example of regression using an $l_1$ prior. The coefficients $c_i$ are optimizable directly from the test data, so they're parameters. However $\lambda$ you can't meaningfully optimize at the same time but have to do that by testing a whole classifier on some different data (the validation set), so it's a meta-parameter.
Changes should be done when you start re-editing tomorrow.