A recommendation engine can work without complex machine learning. Instead, it can be built using straightforward connections between content to suggest things users might like.
Using an API from a platform like Are.na allows easy access to user content and helps find connections between different channels, making recommendations more relevant.
It's important to filter out content that users already know or follow to give them fresh and exciting recommendations. Regular updates to the recommendations can also help keep things interesting.