Just listening to @empiricalcycling podcast about ampk & was reminded of this cool little app that tells you about how much amp kinase activation a given workout will generate. Maybe not 100% useful since most of us don’t have a real good handle on what our muscle glycogen is before or after a workout…but it gives you a feel for what types of activity generates more activation.
https://rothschild.shinyapps.io/AMPK_dashboard/
You can hear some commentary from the author here:
Thanks for that, @The_Cog!
Just some additional commentary on the original post…the author found some correlation between ampk activation & muscle glycogen levels at the end of a bout of exercise. Not a great correlation. Same with the absolute muscle glycogen consumed during a bout of exercise. Some correlation with ampk activation, not a great correlation.
Now, here’s my own commentary, I think that’s just a secondary artifact of the stronger correlation between an individual’s absolute work rate during a bout of exercise and subsequent ampk activation. But who knows.
Also, nobody should consider that widget anything other than a plaything. It’s a model. It’s not going to be predictive. Particularly as you get closer to the boundaries. But it is a great tool to understand the relative importance of different factors that can impact ampk activation.
And the main point I wanted to make was that generally speaking the more intense the workout, the more ampk activation. Which, you know, coaches have kind of known for a while but just didn’t have the vocabulary. 
But, by all means, let’s keep this thread going with more fun links. My wife’s here in the room and if I stop typing she’ll think I’m not doing anything and try to make me do chores.
Too bad there’s no error ranges given. Or that the actionable data from that dashboard is approximately zero.
If anybody is interested (most aren’t) you can stroll to the bottom of the page and use pull down menus to look at a graph of each metric. Each graph is a scatter plot of a variable and an ampk marker with a grey dotted line representing a linear regression…that line is surrounded by a lighter grey region which isn’t explicitly labeled but I believe it represents a confidence interval.
So you can get an additional feel for the relationship there.