diff --git a/performance.md b/performance.md
index b23a0fd..635ff71 100644
--- a/performance.md
+++ b/performance.md
@@ -353,9 +353,16 @@ Choose the simplest reasonable data structure and move on. CS 101, writing
 "not-slow software". Don't be dumb. This should be your default development
 mode.  If you know you need random access, don't choose a linked-list.
 If you know you need in-order traversal, don't use a map.
+Requirements change and you can't always guess the future. Make a reasonable
+guess at the workload.
 
 http://daslab.seas.harvard.edu/rum-conjecture/
 
+Data structures for similar problems will differ in when they do a piece of
+work. A binary tree sorts a little at a time as inserts happen. A unsorted
+array is faster to insert but it's unsorted: at the end to "finalize" you
+need to do the sorting all at once.
+
 When writing a package to be used to by others, avoid the temptation to
 optimize up front for every single use case. This will result in unreadable
 code. Data structures by design are effectively single-purpose. You can
@@ -497,6 +504,7 @@ Cache common cases: Your cache doesn't even need to be huge.
   Random cache eviction is fast and sufficiently effective.
      - only put "some" items in cache (probabilistically) to limit cache size to popular items with minimal logic
   Compare cost of cache logic to cost of refetching the data.
+  A large cache can increase gc pressure and keep blowing processor cache
 
 I've done experiments with a network trace that showed even an optimal
 cache wasn't worth it. Your expected hit ratio is important. You'll want to