As you might've noticed in the new risk API announcement, we've added the ability to use multiple pipelines in algorithms. One example of that is to use the risk loading pipeline along with another pipeline that you define, as seen in the attached algorithm.
Multiple pipelines can easily lead to a slowdown in your algorithm, because the pipeline machinery can optimize your data fetching within a single pipeline, but does not optimize data fetching across separate pipelines. In general, it's better to use a single pipeline. Some anti-patterns are putting each of your terms into its own pipeline, or having shared terms across multiple pipelines.
However, there are a few select use cases where multiple pipelines do work, like when you have disjoint sets of computations that you'd like to run and think about differently (if, for example, you have one pipeline for your risk loadings, and another pipeline for your alpha factors).