diff --git a/performance.md b/performance.md
index 5af4d95..7e02814 100644
--- a/performance.md
+++ b/performance.md
@@ -531,6 +531,15 @@ well-studied by researchers.  Then you can apply the more general solution to
 your specific problem.  Mapping your problem into a domain that already has
 well-researched implementations can be a significant win.
 
+
+TODO:
+  improve worst-case behaviour at slight cost to average runtime
+  linear-time regexp matching
+  randomized algorithms
+    improve worse-case running time
+    skip-list, treap, randomized marking,
+    primality testing, randomized pivot for quicksort
+
 ### Benchmark Inputs
 
 Know how big each of your input sizes is likely to be in production.
@@ -556,6 +565,9 @@ keep them around than to recompute them. If your benchmark data consists of
 only the same repeated request, your cache will give an inaccurate view of
 the performance.
 
+TODO: randomized inputs may have nice properties but not be representative of
+real-world inputs (random graphs, random trees, etc)
+
 Also note that some issues that are not apparent on your laptop might be
 visible once you deploy to production and are hitting 250k reqs/second on
 a 40 core server.