This is just a consequence of the PK being a clustered index in InnoDB which has both pros and cons. One of the big cons is that all of the columns of the PK are implicitly added to every secondary index as the row identifier. That isn't a big problem if your PK is a single column int, but if it's multiple columns, that often results in unnecessary bloat in your secondary indexes. Ideally (as in, dare I say, MS SQL Server), you'd have the option of a clustered or non-clustered PK for your table so you could choose the optimal index structure for your workload on a per-table basis.
For an application in which most queries need a secondary index lookup, using heap organized tables is more efficient because the database needs to traverse only one B-tree (for the secondary index) that gives the physical position of the row in the heap. When using index organized tables, the database needs to traverse 2 B-trees (the secondary index first, then the primary index). Making the primary key short by using an auto incrementing integer helps, but doesn't remove this overhead.
Heap vs. Index organization is a classic tradeoff of database design.
Now, if you're saying "it would be really nice if Postgres had the option of index-organized tables" I'd agree with you. I'd love to have that, as an option.
Being able to force the execution plan is more useful in MySQL than PostgreSQL because MySQL's optimizer is not very good at planning queries.
If you do a lot of PK lookups, then you don't need to force the execution plan.
We (Pinterest, I wrote most of the MySQL automation) make heavy use of MySQL replication which is vastly simpler to manage than PG. All queries still flow through SQL and unlike PG, we can force whatever execution plan we need. We do lots of PK lookups, and InnoDB is really good at that. In InnoDB all the data is stored in the PK while in PG it is just a pointer.