Dr. Violet Howard explains parallelization using a cooking analogy: three turkeys in one oven takes 90 minutes, but three ovens takes 30. The technique speeds up workflows by running tasks at once, though API limits and error handling when some tasks fail complicate the approach.
Today I'm going to be talking about an automation technique that I hardly see anyone talking about on YouTube, and I've actually never covered it on this channel either. Understanding parallelization and sub-workflows is really going to level up your automation game. Okay, so what parallelization is, besides a mouthful, is that you're running multiple tasks at the same time instead of one after another. And just in case it hasn't quite stuck yet, pretend that we want to cook these 3 turkeys and they each will take 30 minutes to cook, but we only have 1 oven to use. So without parallelization, we'd cook the first one and then we cook the second one and then we'd cook the third one and it would take a total of 90 minutes. But if we're able to use parallelization, which means we would have 3 ovens that can all run at the same time, the whole cook time of these 3 turkeys would only be 30 minutes and it's just going to be a lot more efficient. Now let's quickly talk about drawbacks and considerations of using parallelization. Resource limits. So for example, in our flow where we're calling Perplexity to do some research, we may have a limit where you can't do more than 20 per minute or something like that. And if you do run into an issue like that, then you do have to consider looping individually through each item or sending over batches of 20 or something like that. You can't process 100 items all in parallel. Another thing to think about would be error handling. So if you're running 50 items in parallel and one of them errors, how do you handle just that one that errored? And what do you want to do with the rest of the ones? Okay, so that's drawbacks and considerations of parallelization. And so clearly you don't always want to go straight for parallelization, but it's really important to understand still to use subflows because subworkflows are really valuable. If you wanna watch that full breakdown, click on that play button right here and I'll see you guys over there.
