If you are unable to describe, on paper, what your problem domain actually is, then you have no business opening up an IDE and typing out a single line of code.
I will take that further. If, with your domain model, you are unable to craft a query that projects a needed fact from an instance of the model, the you should probably start over. Dimensionality and normalization are a big deal with your model. You have to be really careful about nesting collections of things within other things if you want to allow for higher-order logic to project required views. This is something we struggled with for a really long time. Every rewrite conversation began something like "well customer and account need each other in equal measure...". And it took us god knows how many iterations to figure out the relationship should not be an explicit property either way.
Put shortly, Modeling is the core of it all. Start with simple top-level collections of things. E.g. instead of modeling Customer.Transactions[], model Customers, Transactions and CustomerTransactions. This fundamental principle of keeping your model dimensions separated by way of relational types can help to un-fuck the most problematic of domains. These will start to look a lot like EF POCOs for managing SQL tables...
At the end of the data, data dominates, and SQL is the king of managing data. If you embrace these realities, you might be encouraged to embed SQL a lot deeper into your applications. I spent a long time writing a conditional expression parser by hand. Feels like a really bad use of time in retrospect, but I did learn some things. Now I am looking at using SQLite to do all of this heavy-lifting for me. All I have to do is define a schema matching my domain model, insert data per instance of the model, and run SQL against it to evaluate conditionals and produce complex string output as desired.